&&&& RUNNING TensorRT.trtexec [TensorRT v8001] # /usr/src/tensorrt/bin/trtexec --onnx=onnx_model.onnx --saveEngine=TRTBS2.trt --explicitBatch --verbose --fp16
[07/19/2022-12:59:20] [I] === Model Options ===
[07/19/2022-12:59:20] [I] Format: ONNX
[07/19/2022-12:59:20] [I] Model: onnx_model.onnx
[07/19/2022-12:59:20] [I] Output:
[07/19/2022-12:59:20] [I] === Build Options ===
[07/19/2022-12:59:20] [I] Max batch: explicit
[07/19/2022-12:59:20] [I] Workspace: 16 MiB
[07/19/2022-12:59:20] [I] minTiming: 1
[07/19/2022-12:59:20] [I] avgTiming: 8
[07/19/2022-12:59:20] [I] Precision: FP32+FP16
[07/19/2022-12:59:20] [I] Calibration: 
[07/19/2022-12:59:20] [I] Refit: Disabled
[07/19/2022-12:59:20] [I] Sparsity: Disabled
[07/19/2022-12:59:20] [I] Safe mode: Disabled
[07/19/2022-12:59:20] [I] Restricted mode: Disabled
[07/19/2022-12:59:20] [I] Save engine: TRTBS2.trt
[07/19/2022-12:59:20] [I] Load engine: 
[07/19/2022-12:59:20] [I] NVTX verbosity: 0
[07/19/2022-12:59:20] [I] Tactic sources: Using default tactic sources
[07/19/2022-12:59:20] [I] timingCacheMode: local
[07/19/2022-12:59:20] [I] timingCacheFile: 
[07/19/2022-12:59:20] [I] Input(s)s format: fp32:CHW
[07/19/2022-12:59:20] [I] Output(s)s format: fp32:CHW
[07/19/2022-12:59:20] [I] Input build shapes: model
[07/19/2022-12:59:20] [I] Input calibration shapes: model
[07/19/2022-12:59:20] [I] === System Options ===
[07/19/2022-12:59:20] [I] Device: 0
[07/19/2022-12:59:20] [I] DLACore: 
[07/19/2022-12:59:20] [I] Plugins:
[07/19/2022-12:59:20] [I] === Inference Options ===
[07/19/2022-12:59:20] [I] Batch: Explicit
[07/19/2022-12:59:20] [I] Input inference shapes: model
[07/19/2022-12:59:20] [I] Iterations: 10
[07/19/2022-12:59:20] [I] Duration: 3s (+ 200ms warm up)
[07/19/2022-12:59:20] [I] Sleep time: 0ms
[07/19/2022-12:59:20] [I] Streams: 1
[07/19/2022-12:59:20] [I] ExposeDMA: Disabled
[07/19/2022-12:59:20] [I] Data transfers: Enabled
[07/19/2022-12:59:20] [I] Spin-wait: Disabled
[07/19/2022-12:59:20] [I] Multithreading: Disabled
[07/19/2022-12:59:20] [I] CUDA Graph: Disabled
[07/19/2022-12:59:20] [I] Separate profiling: Disabled
[07/19/2022-12:59:20] [I] Time Deserialize: Disabled
[07/19/2022-12:59:20] [I] Time Refit: Disabled
[07/19/2022-12:59:20] [I] Skip inference: Disabled
[07/19/2022-12:59:20] [I] Inputs:
[07/19/2022-12:59:20] [I] === Reporting Options ===
[07/19/2022-12:59:20] [I] Verbose: Enabled
[07/19/2022-12:59:20] [I] Averages: 10 inferences
[07/19/2022-12:59:20] [I] Percentile: 99
[07/19/2022-12:59:20] [I] Dump refittable layers:Disabled
[07/19/2022-12:59:20] [I] Dump output: Disabled
[07/19/2022-12:59:20] [I] Profile: Disabled
[07/19/2022-12:59:20] [I] Export timing to JSON file: 
[07/19/2022-12:59:20] [I] Export output to JSON file: 
[07/19/2022-12:59:20] [I] Export profile to JSON file: 
[07/19/2022-12:59:20] [I] 
[07/19/2022-12:59:20] [I] === Device Information ===
[07/19/2022-12:59:20] [I] Selected Device: NVIDIA Tegra X2
[07/19/2022-12:59:20] [I] Compute Capability: 6.2
[07/19/2022-12:59:20] [I] SMs: 2
[07/19/2022-12:59:20] [I] Compute Clock Rate: 1.3 GHz
[07/19/2022-12:59:20] [I] Device Global Memory: 3825 MiB
[07/19/2022-12:59:20] [I] Shared Memory per SM: 64 KiB
[07/19/2022-12:59:20] [I] Memory Bus Width: 128 bits (ECC disabled)
[07/19/2022-12:59:20] [I] Memory Clock Rate: 1.3 GHz
[07/19/2022-12:59:20] [I] 
[07/19/2022-12:59:20] [I] TensorRT version: 8001
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::GridAnchor_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::GridAnchorRect_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::NMS_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Reorg_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Region_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Clip_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::LReLU_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::PriorBox_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Normalize_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::ScatterND version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::RPROI_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::BatchedNMS_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::BatchedNMSDynamic_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::FlattenConcat_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::CropAndResize version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::DetectionLayer_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::EfficientNMS_ONNX_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::EfficientNMS_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Proposal version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::ProposalLayer_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::PyramidROIAlign_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::ResizeNearest_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::Split version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::SpecialSlice_TRT version 1
[07/19/2022-12:59:20] [V] [TRT] Registered plugin creator - ::InstanceNormalization_TRT version 1
[07/19/2022-12:59:21] [I] [TRT] [MemUsageChange] Init CUDA: CPU +240, GPU +0, now: CPU 258, GPU 2505 (MiB)
[07/19/2022-12:59:21] [I] Start parsing network model
[07/19/2022-12:59:21] [I] [TRT] ----------------------------------------------------------------
[07/19/2022-12:59:21] [I] [TRT] Input filename:   onnx_model.onnx
[07/19/2022-12:59:21] [I] [TRT] ONNX IR version:  0.0.4
[07/19/2022-12:59:21] [I] [TRT] Opset version:    9
[07/19/2022-12:59:21] [I] [TRT] Producer name:    tf2onnx
[07/19/2022-12:59:21] [I] [TRT] Producer version: 1.10.1 a37f29
[07/19/2022-12:59:21] [I] [TRT] Domain:           
[07/19/2022-12:59:21] [I] [TRT] Model version:    0
[07/19/2022-12:59:21] [I] [TRT] Doc string:       
[07/19/2022-12:59:21] [I] [TRT] ----------------------------------------------------------------
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::GridAnchor_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::GridAnchorRect_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::NMS_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Reorg_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Region_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Clip_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::LReLU_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::PriorBox_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Normalize_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::ScatterND version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::RPROI_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::BatchedNMS_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::BatchedNMSDynamic_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::FlattenConcat_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::CropAndResize version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::DetectionLayer_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::EfficientNMS_ONNX_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::EfficientNMS_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Proposal version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::ProposalLayer_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::PyramidROIAlign_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::ResizeNearest_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::Split version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::SpecialSlice_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Plugin creator already registered - ::InstanceNormalization_TRT version 1
[07/19/2022-12:59:21] [V] [TRT] Adding network input: input_1 with dtype: float32, dimensions: (2, 3, 224, 224)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: input_1 for ONNX tensor: input_1
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/sequential_4/dense_4/MatMul/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Importing initializer: sequential/reshape/Reshape_shape__548
[07/19/2022-12:59:21] [07/19/2022-12:59:21] [V] [TRT] Importing initializer: const_fold_opt__533
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/reshape/Reshape [Reshape]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: input_1
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/reshape/Reshape_shape__548
[07/19/2022-12:59:21] [V] [TRT] sequential/reshape/Reshape [Reshape] inputs: [input_1 -> (2, 3, 224, 224)[FLOAT]], [sequential/reshape/Reshape_shape__548 -> (4)[INT32]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/reshape/Reshape for ONNX node: sequential/reshape/Reshape
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/reshape/Reshape:0 for ONNX tensor: sequential/reshape/Reshape:0
[07/19/2022-12:59:21] [V] [TRT] sequential/reshape/Reshape [Reshape] outputs: [sequential/reshape/Reshape:0 -> (2, 224, 224, 3)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 [Transpose]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/reshape/Reshape:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 [Transpose] inputs: [sequential/reshape/Reshape:0 -> (2, 224, 224, 3)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 [Transpose] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0 -> (2, 3, 224, 224)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0 -> (2, 3, 224, 224)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_weights_fused_bn -> (32, 3, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D_bias_fused_bn -> (32)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 3, 224, 224)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (2, 2), prepadding: (0, 0), postpadding: (1, 1), dilations: (1, 1), numOutputs: 32
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 32, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/bn_Conv1/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/bn_Conv1/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/bn_Conv1/FusedBatchNormV3:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/bn_Conv1/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/bn_Conv1/FusedBatchNormV3:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0 -> (2, 32, 112, 112)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_weights_fused_bn -> (32, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise_bias_fused_bn -> (32)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 32, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 32
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 32, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_BN/FusedBatchNormV3:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_BN/FusedBatchNormV3:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0 -> (2, 32, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0 -> (2, 32, 112, 112)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_weights_fused_bn -> (16, 32, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D_bias_fused_bn -> (16)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 32, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 16
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 16, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0 -> (2, 16, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0 -> (2, 16, 112, 112)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D/ReadVariableOp:0 -> (96, 16, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 16, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 96, 112, 112)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D:0 -> (2, 96, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D:0 -> (2, 96, 112, 112)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp:0 -> (96)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/ReadVariableOp_1:0 -> (96)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (96)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (96)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3:0 -> (2, 96, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3:0 -> (2, 96, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0 -> (2, 96, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad [Pad]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad [Pad] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0 -> (2, 96, 112, 112)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad [Pad] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad:0 -> (2, 96, 113, 113)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad:0 -> (2, 96, 113, 113)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_weights_fused_bn -> (96, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise_bias_fused_bn -> (96)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 96, 113, 113)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (2, 2), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 96, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_BN/FusedBatchNormV3:0 -> (2, 96, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_BN/FusedBatchNormV3:0 -> (2, 96, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0 -> (2, 96, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0 -> (2, 96, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_weights_fused_bn -> (24, 96, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D_bias_fused_bn -> (24)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 96, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 24
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 24, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0 -> (2, 24, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0 -> (2, 24, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D/ReadVariableOp:0 -> (144, 24, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 24, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 144
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 144, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D:0 -> (2, 144, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp:0 -> (144)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/ReadVariableOp_1:0 -> (144)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (144)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (144)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_weights_fused_bn -> (144, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise_bias_fused_bn -> (144)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 144, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 144
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 144, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_weights_fused_bn -> (24, 144, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D_bias_fused_bn -> (24)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 144, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 24
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 24, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_project_BN/FusedBatchNormV3:0 -> (2, 24, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0 -> (2, 24, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_2_project_BN/FusedBatchNormV3:0 -> (2, 24, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0 -> (2, 24, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0 -> (2, 24, 56, 56)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_weights_fused_bn -> (144, 24, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D_bias_fused_bn -> (144)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 24, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 144
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 144, 56, 56)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_BN/FusedBatchNormV3:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad [Pad]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad [Pad] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0 -> (2, 144, 56, 56)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad [Pad] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad:0 -> (2, 144, 57, 57)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad:0 -> (2, 144, 57, 57)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_weights_fused_bn -> (144, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise_bias_fused_bn -> (144)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 144, 57, 57)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (2, 2), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 144
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 144, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_BN/FusedBatchNormV3:0 -> (2, 144, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_BN/FusedBatchNormV3:0 -> (2, 144, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0 -> (2, 144, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0 -> (2, 144, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_weights_fused_bn -> (32, 144, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D_bias_fused_bn -> (32)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 144, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D/ReadVariableOp:0 -> (192, 32, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D:0 -> (2, 192, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp:0 -> (192)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/ReadVariableOp_1:0 -> (192)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (192)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_weights_fused_bn -> (192, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise_bias_fused_bn -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_weights_fused_bn -> (32, 192, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D_bias_fused_bn -> (32)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_4_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0 -> (2, 32, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_weights_fused_bn -> (192, 32, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D_bias_fused_bn -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_weights_fused_bn -> (192, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise_bias_fused_bn -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_weights_fused_bn -> (32, 192, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D_bias_fused_bn -> (32)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0 -> (2, 32, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_5_project_BN/FusedBatchNormV3:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0 -> (2, 32, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0 -> (2, 32, 28, 28)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_weights_fused_bn -> (192, 32, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D_bias_fused_bn -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 32, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 28, 28)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_BN/FusedBatchNormV3:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad [Pad]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad [Pad] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0 -> (2, 192, 28, 28)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad [Pad] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad:0 -> (2, 192, 29, 29)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad:0 -> (2, 192, 29, 29)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_weights_fused_bn -> (192, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise_bias_fused_bn -> (192)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 29, 29)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (2, 2), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 192, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_BN/FusedBatchNormV3:0 -> (2, 192, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0 -> (2, 192, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0 -> (2, 192, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_weights_fused_bn -> (64, 192, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D_bias_fused_bn -> (64)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 192, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D/ReadVariableOp:0 -> (384, 64, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp:0 -> (384)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/ReadVariableOp_1:0 -> (384)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (384)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_weights_fused_bn -> (384, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_weights_fused_bn -> (64, 384, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D_bias_fused_bn -> (64)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_7_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_weights_fused_bn -> (384, 64, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_weights_fused_bn -> (384, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_weights_fused_bn -> (64, 384, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D_bias_fused_bn -> (64)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_8_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_weights_fused_bn -> (384, 64, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_weights_fused_bn -> (384, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_weights_fused_bn -> (64, 384, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D_bias_fused_bn -> (64)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_9_project_BN/FusedBatchNormV3:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0 -> (2, 64, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0 -> (2, 64, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_weights_fused_bn -> (384, 64, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 64, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_weights_fused_bn -> (384, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise_bias_fused_bn -> (384)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_BN/FusedBatchNormV3:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0 -> (2, 384, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_weights_fused_bn -> (96, 384, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D_bias_fused_bn -> (96)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 384, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D/ReadVariableOp:0 -> (576, 96, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D:0 -> (2, 576, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp:0 -> (576)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/ReadVariableOp_1:0 -> (576)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (576)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_weights_fused_bn -> (576, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise_bias_fused_bn -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_weights_fused_bn -> (96, 576, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D_bias_fused_bn -> (96)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_11_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0 -> (2, 96, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_weights_fused_bn -> (576, 96, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D_bias_fused_bn -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_weights_fused_bn -> (576, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise_bias_fused_bn -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_weights_fused_bn -> (96, 576, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D_bias_fused_bn -> (96)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0 -> (2, 96, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_12_project_BN/FusedBatchNormV3:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0 -> (2, 96, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0 -> (2, 96, 14, 14)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_weights_fused_bn -> (576, 96, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D_bias_fused_bn -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 96, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 14, 14)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_BN/FusedBatchNormV3:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad [Pad]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad [Pad] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0 -> (2, 576, 14, 14)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad [Pad] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad:0 -> (2, 576, 15, 15)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad:0 -> (2, 576, 15, 15)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_weights_fused_bn -> (576, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise_bias_fused_bn -> (576)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 15, 15)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (2, 2), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 576, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_BN/FusedBatchNormV3:0 -> (2, 576, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0 -> (2, 576, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0 -> (2, 576, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_weights_fused_bn -> (160, 576, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D_bias_fused_bn -> (160)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 576, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D/ReadVariableOp:0 -> (960, 160, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp:0 -> (960)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/ReadVariableOp_1:0 -> (960)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp:0 -> (960)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3/ReadVariableOp_1:0 -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_weights_fused_bn -> (960, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise_bias_fused_bn -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_weights_fused_bn -> (160, 960, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D_bias_fused_bn -> (160)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_14_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0 -> (2, 160, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_weights_fused_bn -> (960, 160, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D_bias_fused_bn -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_weights_fused_bn -> (960, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise_bias_fused_bn -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_weights_fused_bn -> (160, 960, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D_bias_fused_bn -> (160)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add [Add]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add [Add] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0 -> (2, 160, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_15_project_BN/FusedBatchNormV3:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add [Add] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0 -> (2, 160, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0 -> (2, 160, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_weights_fused_bn -> (960, 160, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D_bias_fused_bn -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 160, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_weights_fused_bn -> (960, 1, 3, 3)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise_bias_fused_bn -> (960)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_BN/FusedBatchNormV3:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_weights_fused_bn
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_bias_fused_bn
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0 -> (2, 960, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_weights_fused_bn -> (320, 960, 1, 1)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D_bias_fused_bn -> (320)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 960, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 320
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 320, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0 -> (2, 320, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D [Conv]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D [Conv] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0 -> (2, 320, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D/ReadVariableOp:0 -> (1280, 320, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Convolution input dimensions: (2, 320, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D
[07/19/2022-12:59:21] [V] [TRT] Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 1280
[07/19/2022-12:59:21] [V] [TRT] Convolution output dimensions: (2, 1280, 7, 7)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D [Conv] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D:0 -> (2, 1280, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3 [BatchNormalization]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp_1:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3 [BatchNormalization] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D:0 -> (2, 1280, 7, 7)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp:0 -> (1280)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/ReadVariableOp_1:0 -> (1280)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp:0 -> (1280)[FLOAT]], [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3/ReadVariableOp_1:0 -> (1280)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3 [BatchNormalization] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3:0 -> (2, 1280, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 [Clip]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 [Clip] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3:0 -> (2, 1280, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 for ONNX node: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0 for ONNX tensor: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 [Clip] outputs: [sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0 -> (2, 1280, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/average_pooling2d_4/AvgPool [AveragePool]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/average_pooling2d_4/AvgPool [AveragePool] inputs: [sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0 -> (2, 1280, 7, 7)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/average_pooling2d_4/AvgPool for ONNX node: sequential/sequential_4/average_pooling2d_4/AvgPool
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/average_pooling2d_4/AvgPool:0 for ONNX tensor: sequential/sequential_4/average_pooling2d_4/AvgPool:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/average_pooling2d_4/AvgPool [AveragePool] outputs: [sequential/sequential_4/average_pooling2d_4/AvgPool:0 -> (2, 1280, 1, 1)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/flatten_4/Reshape [Reshape]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/average_pooling2d_4/AvgPool:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: const_fold_opt__533
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/flatten_4/Reshape [Reshape] inputs: [sequential/sequential_4/average_pooling2d_4/AvgPool:0 -> (2, 1280, 1, 1)[FLOAT]], [const_fold_opt__533 -> (2)[INT32]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/flatten_4/Reshape for ONNX node: sequential/sequential_4/flatten_4/Reshape
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/flatten_4/Reshape:0 for ONNX tensor: sequential/sequential_4/flatten_4/Reshape:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/flatten_4/Reshape [Reshape] outputs: [sequential/sequential_4/flatten_4/Reshape:0 -> (2, 1280)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/dense_4/MatMul [MatMul]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/flatten_4/Reshape:0
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/dense_4/MatMul/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/dense_4/MatMul [MatMul] inputs: [sequential/sequential_4/flatten_4/Reshape:0 -> (2, 1280)[FLOAT]], [sequential/sequential_4/dense_4/MatMul/ReadVariableOp:0 -> (1280, 4)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/dense_4/MatMul/ReadVariableOp:0 for ONNX node: sequential/sequential_4/dense_4/MatMul/ReadVariableOp:0
[07/19/2022-12:59:21] [V] [TRT] GEMM: using FC layer instead of MM because all criteria were met.
[07/19/2022-12:59:21] [V] [TRT] Original shape: (2, 1280), unsqueezing to: (2, 1280, 1, 1)
[07/19/2022-12:59:21] [07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/dense_4/MatMul for ONNX node: sequential/sequential_4/dense_4/MatMul
[07/19/2022-12:59:21] [V] [TRT] Original shape: (2, 4, 1, 1), squeezing to: (2, 4)
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential/sequential_4/dense_4/MatMul:0 for ONNX tensor: sequential/sequential_4/dense_4/MatMul:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/dense_4/MatMul [MatMul] outputs: [sequential/sequential_4/dense_4/MatMul:0 -> (2, 4)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Parsing node: sequential/sequential_4/softmax_4/Softmax [Softmax]
[07/19/2022-12:59:21] [V] [TRT] Searching for input: sequential/sequential_4/dense_4/MatMul:0
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/softmax_4/Softmax [Softmax] inputs: [sequential/sequential_4/dense_4/MatMul:0 -> (2, 4)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Registering layer: sequential/sequential_4/softmax_4/Softmax for ONNX node: sequential/sequential_4/softmax_4/Softmax
[07/19/2022-12:59:21] [V] [TRT] Registering tensor: sequential_4_0 for ONNX tensor: sequential_4
[07/19/2022-12:59:21] [V] [TRT] sequential/sequential_4/softmax_4/Softmax [Softmax] outputs: [sequential_4 -> (2, 4)[FLOAT]], 
[07/19/2022-12:59:21] [V] [TRT] Marking sequential_4_0 as output: sequential_4
[07/19/2022-12:59:21] [I] Finish parsing network model
[07/19/2022-12:59:21] [I] [TRT] [MemUsageChange] Init CUDA: CPU +0, GPU +0, now: CPU 267, GPU 2532 (MiB)
[07/19/2022-12:59:21] [I] [TRT] [MemUsageSnapshot] Builder begin: CPU 267 MiB, GPU 2532 MiB
[07/19/2022-12:59:21] [V] [TRT] Applying generic optimizations to the graph for inference.
[07/19/2022-12:59:21] [V] [TRT] Original: 118 layers
[07/19/2022-12:59:21] [V] [TRT] After dead-layer removal: 118 layers
[07/19/2022-12:59:21] [V] [TRT] ShuffleShuffleFusion: Fusing sequential/reshape/Reshape with sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14
[07/19/2022-12:59:21] [V] [TRT] ShuffleShuffleFusion: Fusing sequential/sequential_4/flatten_4/Reshape with (Unnamed Layer* 113) [Shuffle]
[07/19/2022-12:59:21] [V] [TRT] Removing sequential/sequential_4/flatten_4/Reshape + (Unnamed Layer* 113) [Shuffle]
[07/19/2022-12:59:21] [V] [TRT] ShuffleShuffleFusion: Fusing (Unnamed Layer* 115) [Shuffle] with (Unnamed Layer* 116) [Shuffle]
[07/19/2022-12:59:21] [V] [TRT] Removing (Unnamed Layer* 118) [Shuffle]
[07/19/2022-12:59:22] [V] [TRT] After Myelin optimization: 113 layers
[07/19/2022-12:59:22] [V] [TRT] Convert layer type of sequential/sequential_4/dense_4/MatMul from FULLY_CONNECTED to CONVOLUTION
[07/19/2022-12:59:22] [V] [TRT] Removing shuffle_between_sequential/sequential_4/average_pooling2d_4/AvgPool:0_and_sequential/sequential_4/dense_4/MatMul
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_BN/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] Fusing convolution weights from sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D with scale sequential/sequential_4/mobilenetv2_1.00_224/Conv_1_bn/FusedBatchNormV3
[07/19/2022-12:59:22] [V] [TRT] After scale fusion: 106 layers
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] PaddingConvolutionFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad with sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] PaddingConvolutionFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad with sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] PaddingConvolutionFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad with sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] PaddingConvolutionFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad with sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvEltwiseSumFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise with sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] ConvPointWiseClipFusion: Fusing sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D with sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6
[07/19/2022-12:59:22] [V] [TRT] After vertical fusions: 57 layers
[07/19/2022-12:59:22] [V] [TRT] After dupe layer removal: 57 layers
[07/19/2022-12:59:22] [V] [TRT] After final dead-layer removal: 57 layers
[07/19/2022-12:59:22] [V] [TRT] After tensor merging: 57 layers
[07/19/2022-12:59:22] [V] [TRT] After concat removal: 57 layers
[07/19/2022-12:59:22] [V] [TRT] Graph construction and optimization completed in 0.0707974 seconds.
[07/19/2022-12:59:22] [I] [TRT] ---------- Layers Running on DLA ----------
[07/19/2022-12:59:22] [I] [TRT] ---------- Layers Running on GPU ----------
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/average_pooling2d_4/AvgPool
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/dense_4/MatMul
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] (Unnamed Layer* 115) [Shuffle] + (Unnamed Layer* 116) [Shuffle]
[07/19/2022-12:59:22] [I] [TRT] [GpuLayer] sequential/sequential_4/softmax_4/Softmax
[07/19/2022-12:59:23] [V] [TRT] Using cublas a tactic source
[07/19/2022-12:59:23] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +167, GPU +154, now: CPU 437, GPU 2686 (MiB)
[07/19/2022-12:59:23] [V] [TRT] Using cuDNN as a tactic source
[07/19/2022-12:59:24] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +250, GPU +251, now: CPU 687, GPU 2937 (MiB)
[07/19/2022-12:59:24] [07/19/2022-12:59:24] [V] [TRT] Constructing optimization profile number 0 [1/1].
[07/19/2022-12:59:24] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:24] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:24] [V] [TRT] Tactic: 1002 Time: 5.98595
[07/19/2022-12:59:24] [V] [TRT] Tactic: 0 Time: 0.282568
[07/19/2022-12:59:24] [V] [TRT] Fastest Tactic: 0 Time: 0.282568
[07/19/2022-12:59:24] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Float(50176,50176:32,224,1) ***************
[07/19/2022-12:59:24] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:24] [V] [TRT] Tactic: 1002 Time: 4.31226
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 14.2921
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 1002 Time: 4.31226
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.132052
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.146044
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 1002 Time: 0.132052
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.292952
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.119316
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.119316
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning format combination: Float(150528,50176,224,1) -> Float(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 (Shuffle)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.160876
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.160876
[07/19/2022-12:59:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning format combination: Float(150528,1,672,3) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 (Shuffle)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.585192
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.585192
[07/19/2022-12:59:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning format combination: Float(50176,50176:32,224,1) -> Float(50176,50176:32,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 (Shuffle)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 14.2584
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 14.2584
[07/19/2022-12:59:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning format combination: Half(150528,50176,224,1) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 (Shuffle)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.146352
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.146352
[07/19/2022-12:59:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning format combination: Half(100352,50176:2,224,1) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 (Shuffle)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.246232
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.246232
[07/19/2022-12:59:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,50176,224,1) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,672,3) -> Float(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 2.1208
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.146384
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.146384
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,672,3) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 1.11351
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.148448
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.148448
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,672,3) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.141368
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.215948
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 1002 Time: 0.141368
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(50176,50176:32,224,1) -> Float(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 2.15968
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.53436
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.53436
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(50176,50176:32,224,1) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 1.30194
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.206296
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.206296
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(50176,50176:32,224,1) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 1.05154
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.518752
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.518752
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Float(50176,50176:32,224,1) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.378552
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.634456
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 1002 Time: 0.378552
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Half(150528,50176,224,1) -> Float(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.135524
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.149216
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 1002 Time: 0.135524
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Half(150528,50176,224,1) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 1.12299
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.158664
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.158664
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Half(150528,50176,224,1) -> Half(100352,50176:2,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 0.145996
[07/19/2022-12:59:25] [V] [TRT] Tactic: 0 Time: 0.116684
[07/19/2022-12:59:25] [V] [TRT] Fastest Tactic: 0 Time: 0.116684
[07/19/2022-12:59:25] [V] [TRT] *************** Autotuning Reformat:Half(100352,50176:2,224,1) -> Float(150528,50176,224,1) ***************
[07/19/2022-12:59:25] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:25] [V] [TRT] Tactic: 1002 Time: 1.03941
[07/19/2022-12:59:26] [V] [TRT] Tactic: 0 Time: 0.08562
[07/19/2022-12:59:26] [V] [TRT] Fastest Tactic: 0 Time: 0.08562
[07/19/2022-12:59:26] [V] [TRT] *************** Autotuning Reformat:Half(100352,50176:2,224,1) -> Float(150528,1,672,3) ***************
[07/19/2022-12:59:26] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:26] [V] [TRT] Tactic: 1002 Time: 1.09565
[07/19/2022-12:59:26] [V] [TRT] Tactic: 0 Time: 0.184296
[07/19/2022-12:59:26] [V] [TRT] Fastest Tactic: 0 Time: 0.184296
[07/19/2022-12:59:26] [V] [TRT] *************** Autotuning Reformat:Half(100352,50176:2,224,1) -> Half(150528,50176,224,1) ***************
[07/19/2022-12:59:26] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:26] [V] [TRT] Tactic: 1002 Time: 2.9486
[07/19/2022-12:59:26] [V] [TRT] Tactic: 0 Time: 0.07968
[07/19/2022-12:59:26] [V] [TRT] Fastest Tactic: 0 Time: 0.07968
[07/19/2022-12:59:26] [V] [TRT] *************** Autotuning format combination: Float(150528,50176,224,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-12:59:26] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:27] [V] [TRT] Tactic: 0 Time: 1.2119
[07/19/2022-12:59:27] [V] [TRT] Tactic: 1 Time: 0.96552
[07/19/2022-12:59:27] [V] [TRT] Tactic: 2 Time: 1.59894
[07/19/2022-12:59:27] [V] [TRT] Tactic: 5 Time: 21.5535
[07/19/2022-12:59:27] [V] [TRT] Fastest Tactic: 1 Time: 0.96552
[07/19/2022-12:59:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-12:59:27] [V] [TRT] Tactic: 1062367460111450758 Time: 0.283104
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-12:59:27] [V] [TRT] Tactic: 1754984623894446479 Time: 0.2899
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-12:59:27] [V] [TRT] Tactic: 3611739942397549984 Time: 0.813452
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-12:59:27] [V] [TRT] Tactic: 4337000649858996379 Time: 0.398644
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-12:59:27] [V] [TRT] Tactic: 4501471010995462441 Time: 0.761496
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-12:59:27] [V] [TRT] Tactic: 5137655947464784826 Time: 0.38804
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-12:59:27] [V] [TRT] Tactic: 5288347012147084929 Time: 0.806384
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-12:59:27] [V] [TRT] Tactic: 6645123197870846056 Time: 0.3944
[07/19/2022-12:59:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-12:59:28] [V] [TRT] Tactic: 7144526460361122478 Time: 0.28724
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-12:59:28] [V] [TRT] Tactic: -9137461792520977713 Time: 0.766252
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-12:59:28] [V] [TRT] Tactic: -8262349710178828730 Time: 0.811764
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-12:59:28] [V] [TRT] Tactic: -8133971918129952780 Time: 0.417276
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-12:59:28] [V] [TRT] Tactic: -6092040395344634144 Time: 0.288196
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-12:59:28] [V] [TRT] Tactic: -4787320710726427159 Time: 0.286944
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-12:59:28] [V] [TRT] Tactic: -3456450830548107839 Time: 0.269884
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-12:59:28] [V] [TRT] Tactic: -1218658103698133241 Time: 0.416396
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-12:59:28] [V] [TRT] Tactic: -836875257600482091 Time: 0.411344
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-12:59:28] [V] [TRT] Tactic: -410470605513481746 Time: 0.750688
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: -3456450830548107839 Time: 0.269884
[07/19/2022-12:59:28] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -3456450830548107839
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning format combination: Float(150528,1,672,3) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:28] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:28] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning format combination: Half(150528,50176,224,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 0 Time: 1.01804
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1 Time: 1.08454
[07/19/2022-12:59:28] [V] [TRT] Tactic: 2 Time: 1.56738
[07/19/2022-12:59:28] [V] [TRT] Tactic: 5 Time: 21.6656
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 0 Time: 1.01804
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:28] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:28] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning format combination: Half(100352,50176:2,224,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:28] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-12:59:28] [V] [TRT] Tactic: 3564772625446233998 Time: 0.19914
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_large_nn_v1 Tactic: 3650389455493082349
[07/19/2022-12:59:28] [V] [TRT] Tactic: 3650389455493082349 Time: 0.20478
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-12:59:28] [V] [TRT] Tactic: 5319956359050645452 Time: 0.191752
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-12:59:28] [V] [TRT] Tactic: 7205456024582378848 Time: 0.288228
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_large_nn_v1 Tactic: -6490690591794140522
[07/19/2022-12:59:28] [V] [TRT] Tactic: -6490690591794140522 Time: 0.291676
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_large_nn_v1 Tactic: -4686027666808657977
[07/19/2022-12:59:28] [V] [TRT] Tactic: -4686027666808657977 Time: 0.558728
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-12:59:28] [V] [TRT] Tactic: -4212163711445252890 Time: 0.543496
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-12:59:28] [V] [TRT] Tactic: -3898373634979201110 Time: 0.554576
[07/19/2022-12:59:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-12:59:28] [V] [TRT] Tactic: -2409163523992614473 Time: 0.283568
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 5319956359050645452 Time: 0.191752
[07/19/2022-12:59:28] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5319956359050645452
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1002 Time: 0.61944
[07/19/2022-12:59:28] [V] [TRT] Tactic: 0 Time: 0.674324
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 1002 Time: 0.61944
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1002 Time: 0.349768
[07/19/2022-12:59:28] [V] [TRT] Tactic: 0 Time: 0.378508
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 1002 Time: 0.349768
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1002 Time: 0.591356
[07/19/2022-12:59:28] [V] [TRT] Tactic: 0 Time: 0.233936
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 0 Time: 0.233936
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1002 Time: 0.640232
[07/19/2022-12:59:28] [V] [TRT] Tactic: 0 Time: 1.47068
[07/19/2022-12:59:28] [V] [TRT] Fastest Tactic: 1002 Time: 0.640232
[07/19/2022-12:59:28] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:28] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:28] [V] [TRT] Tactic: 1002 Time: 0.28402
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 1.37211
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 1002 Time: 0.28402
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.56486
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 1.55748
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 1002 Time: 0.56486
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.358056
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.368336
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 1002 Time: 0.358056
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.246596
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.600124
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 1002 Time: 0.246596
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.269088
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.228492
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 0 Time: 0.228492
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.523136
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.214876
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 0 Time: 0.214876
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.27954
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.48446
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 1002 Time: 0.27954
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1002 Time: 0.845388
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 0.201788
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: 0 Time: 0.201788
[07/19/2022-12:59:29] [V] [TRT] *************** Autotuning format combination: Float(401408,12544,112,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-12:59:29] [V] [TRT] Tactic: -1 Time: 0.399384
[07/19/2022-12:59:29] [V] [TRT] Fastest Tactic: -1 Time: 0.399384
[07/19/2022-12:59:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:29] [V] [TRT] Tactic: 0 Time: 1.13206
[07/19/2022-12:59:29] [V] [TRT] Tactic: 1 Time: 1.13774
[07/19/2022-12:59:29] [V] [TRT] Tactic: 2 Time: 1.27142
[07/19/2022-12:59:30] [V] [TRT] Tactic: 4 Time: 47.3667
[07/19/2022-12:59:31] [V] [TRT] Tactic: 5 Time: 82.6792
[07/19/2022-12:59:32] [V] [TRT] Tactic: 6 Time: 24.7341
[07/19/2022-12:59:32] [V] [TRT] Fastest Tactic: 0 Time: 1.13206
[07/19/2022-12:59:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-12:59:32] [V] [TRT] Tactic: 1062367460111450758 Time: 5.94655
[07/19/2022-12:59:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-12:59:32] [V] [TRT] Tactic: 1754984623894446479 Time: 5.49485
[07/19/2022-12:59:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-12:59:32] [V] [TRT] Tactic: 3611739942397549984 Time: 19.7496
[07/19/2022-12:59:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-12:59:32] [V] [TRT] Tactic: 3827454225649558724 Time: 16.6744
[07/19/2022-12:59:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-12:59:33] [V] [TRT] Tactic: 4337000649858996379 Time: 9.33031
[07/19/2022-12:59:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-12:59:33] [V] [TRT] Tactic: 4501471010995462441 Time: 18.1912
[07/19/2022-12:59:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-12:59:33] [V] [TRT] Tactic: 5137655947464784826 Time: 9.04601
[07/19/2022-12:59:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-12:59:34] [V] [TRT] Tactic: 5288347012147084929 Time: 19.621
[07/19/2022-12:59:34] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-12:59:34] [V] [TRT] Tactic: 5921334924264294896 Time: 11.0747
[07/19/2022-12:59:34] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-12:59:34] [V] [TRT] Tactic: 6645123197870846056 Time: 9.2806
[07/19/2022-12:59:34] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-12:59:34] [V] [TRT] Tactic: 7144526460361122478 Time: 5.36894
[07/19/2022-12:59:34] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-12:59:34] [V] [TRT] Tactic: 7852627285308570038 Time: 17.7157
[07/19/2022-12:59:34] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-12:59:35] [V] [TRT] Tactic: -9137461792520977713 Time: 18.4469
[07/19/2022-12:59:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-12:59:35] [V] [TRT] Tactic: -8776506421218919509 Time: 16.4181
[07/19/2022-12:59:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-12:59:35] [V] [TRT] Tactic: -8262349710178828730 Time: 19.7475
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-12:59:36] [V] [TRT] Tactic: -8133971918129952780 Time: 9.02033
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-12:59:36] [V] [TRT] Tactic: -6092040395344634144 Time: 6.17687
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-12:59:36] [V] [TRT] Tactic: -4787320710726427159 Time: 5.47764
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-12:59:36] [V] [TRT] Tactic: -3456450830548107839 Time: 5.80103
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-12:59:36] [V] [TRT] Tactic: -2318106587342035239 Time: 16.7671
[07/19/2022-12:59:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-12:59:37] [V] [TRT] Tactic: -1343271414618805657 Time: 10.9052
[07/19/2022-12:59:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-12:59:37] [V] [TRT] Tactic: -1218658103698133241 Time: 8.98543
[07/19/2022-12:59:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-12:59:37] [V] [TRT] Tactic: -836875257600482091 Time: 8.9127
[07/19/2022-12:59:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-12:59:37] [V] [TRT] Tactic: -410470605513481746 Time: 18.0454
[07/19/2022-12:59:37] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 5.36894
[07/19/2022-12:59:37] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-12:59:37] [V] [TRT] *************** Autotuning format combination: Float(401408,1,3584,32) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:37] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:37] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:37] [V] [TRT] *************** Autotuning format combination: Half(401408,12544,112,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:37] [V] [TRT] Tactic: 0 Time: 0.780896
[07/19/2022-12:59:37] [V] [TRT] Tactic: 1 Time: 0.785184
[07/19/2022-12:59:38] [V] [TRT] Tactic: 2 Time: 17.1528
[07/19/2022-12:59:39] [V] [TRT] Tactic: 4 Time: 47.2086
[07/19/2022-12:59:40] [V] [TRT] Tactic: 5 Time: 82.891
[07/19/2022-12:59:40] [V] [TRT] Tactic: 6 Time: 28.2321
[07/19/2022-12:59:40] [V] [TRT] Fastest Tactic: 0 Time: 0.780896
[07/19/2022-12:59:40] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:40] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:40] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning format combination: Half(200704,12544:2,112,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:40] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,12544,112,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Float(401408,1,3584,32) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(401408,12544,112,1) -> Half(200704,12544:2,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Float(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Float(401408,1,3584,32) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544:2,112,1) -> Half(401408,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] *************** Autotuning format combination: Float(401408,12544,112,1) -> Float(200704,12544,112,1) ***************
[07/19/2022-12:59:40] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-12:59:40] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:40] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (FusedConvActConvolution)
[07/19/2022-12:59:40] [V] [TRT] Tactic: 589823 Time: 0.756552
[07/19/2022-12:59:41] [V] [TRT] Tactic: 655359 Time: 1.04876
[07/19/2022-12:59:41] [V] [TRT] Tactic: 786431 Time: 0.749216
[07/19/2022-12:59:41] [V] [TRT] Tactic: 851967 Time: 1.74129
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1179647 Time: 0.99644
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1310719 Time: 1.1296
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1376255 Time: 0.672836
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1441791 Time: 1.2684
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1507327 Time: 1.61174
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1638399 Time: 0.797616
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1835007 Time: 0.76804
[07/19/2022-12:59:41] [V] [TRT] Tactic: 1900543 Time: 1.3018
[07/19/2022-12:59:41] [V] [TRT] Tactic: 2097151 Time: 0.856536
[07/19/2022-12:59:41] [V] [TRT] Tactic: 2162687 Time: 0.736828
[07/19/2022-12:59:42] [V] [TRT] Tactic: 2293759 Time: 0.643748
[07/19/2022-12:59:42] [V] [TRT] Tactic: 2359295 Time: 0.866636
[07/19/2022-12:59:42] [V] [TRT] Tactic: 2686975 Time: 0.660856
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3080191 Time: 1.49722
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3342335 Time: 1.45568
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3407871 Time: 0.726576
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3538943 Time: 0.71552
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3670015 Time: 0.872712
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3932159 Time: 1.1515
[07/19/2022-12:59:42] [V] [TRT] Tactic: 3997695 Time: 0.743648
[07/19/2022-12:59:42] [V] [TRT] Tactic: 4063231 Time: 1.74997
[07/19/2022-12:59:42] [V] [TRT] Tactic: 4194303 Time: 0.725408
[07/19/2022-12:59:42] [V] [TRT] Tactic: 4259839 Time: 0.842604
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4325375 Time: 0.711368
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4521983 Time: 0.777576
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4587519 Time: 0.723976
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4653055 Time: 1.20084
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4915199 Time: 0.708748
[07/19/2022-12:59:43] [V] [TRT] Tactic: 4980735 Time: 0.716912
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5177343 Time: 0.9479
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5242879 Time: 0.766764
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5373951 Time: 1.02427
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5439487 Time: 1.12219
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5570559 Time: 1.27984
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5636095 Time: 1.7534
[07/19/2022-12:59:43] [V] [TRT] Tactic: 5701631 Time: 0.688964
[07/19/2022-12:59:44] [V] [TRT] Tactic: 5767167 Time: 1.94983
[07/19/2022-12:59:44] [V] [TRT] Tactic: 5832703 Time: 0.70482
[07/19/2022-12:59:44] [V] [TRT] Tactic: 5898239 Time: 0.833064
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6029311 Time: 0.669788
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6225919 Time: 0.728172
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6291455 Time: 0.996344
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6422527 Time: 1.19254
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6750207 Time: 0.706404
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6815743 Time: 1.08496
[07/19/2022-12:59:44] [V] [TRT] Tactic: 6946815 Time: 1.07151
[07/19/2022-12:59:44] [V] [TRT] Tactic: 7012351 Time: 0.85712
[07/19/2022-12:59:44] [V] [TRT] Tactic: 7077887 Time: 0.7118
[07/19/2022-12:59:44] [V] [TRT] Tactic: 7143423 Time: 0.845228
[07/19/2022-12:59:44] [V] [TRT] Tactic: 7208959 Time: 0.764764
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7340031 Time: 0.823124
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7405567 Time: 0.923444
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7536639 Time: 0.749736
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7602175 Time: 0.707236
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7733247 Time: 0.83516
[07/19/2022-12:59:45] [V] [TRT] Tactic: 7798783 Time: 0.74876
[07/19/2022-12:59:45] [V] [TRT] Tactic: 8191999 Time: 0.809924
[07/19/2022-12:59:45] [V] [TRT] Tactic: 8257535 Time: 0.681996
[07/19/2022-12:59:45] [V] [TRT] Tactic: 8323071 Time: 0.775632
[07/19/2022-12:59:45] [V] [TRT] Tactic: 8650751 Time: 0.758216
[07/19/2022-12:59:45] [V] [TRT] Tactic: 8716287 Time: 0.97878
[07/19/2022-12:59:45] [V] [TRT] Tactic: 9109503 Time: 0.921508
[07/19/2022-12:59:45] [V] [TRT] Tactic: 9568255 Time: 0.711248
[07/19/2022-12:59:45] [V] [TRT] Tactic: 9895935 Time: 0.724872
[07/19/2022-12:59:45] [V] [TRT] Tactic: 10223615 Time: 0.666536
[07/19/2022-12:59:45] [V] [TRT] Tactic: 10354687 Time: 0.7157
[07/19/2022-12:59:45] [V] [TRT] Tactic: 10551295 Time: 0.702828
[07/19/2022-12:59:46] [V] [TRT] Tactic: 10747903 Time: 0.854012
[07/19/2022-12:59:46] [V] [TRT] Tactic: 10944511 Time: 0.7367
[07/19/2022-12:59:46] [V] [TRT] Fastest Tactic: 2293759 Time: 0.643748
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CudnnConvolution)
[07/19/2022-12:59:46] [V] [TRT] Tactic: 0 Time: 0.530948
[07/19/2022-12:59:46] [V] [TRT] Tactic: 1 Time: 0.493812
[07/19/2022-12:59:46] [V] [TRT] Tactic: 2 Time: 1.20264
[07/19/2022-12:59:46] [V] [TRT] Tactic: 4 skipped. Scratch requested: 76679168, available: 16777216
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5 Time: 1.45481
[07/19/2022-12:59:46] [I] [TRT] Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.
[07/19/2022-12:59:46] [V] [TRT] Fastest Tactic: 1 Time: 0.493812
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CublasConvolution)
[07/19/2022-12:59:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CaskConvolution)
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-12:59:46] [V] [TRT] Tactic: 1062367460111450758 Time: 0.285592
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-12:59:46] [V] [TRT] Tactic: 1698681053543049347 Time: 0.263148
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-12:59:46] [V] [TRT] Tactic: 4501471010995462441 Time: 0.764524
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5137655947464784826 Time: 0.391776
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5288347012147084929 Time: 0.789732
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5326823351883942011 Time: 0.75074
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5500448035057547314 Time: 0.443164
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-12:59:46] [V] [TRT] Tactic: 6645123197870846056 Time: 0.397676
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-12:59:46] [V] [TRT] Tactic: 7144526460361122478 Time: 0.298728
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-12:59:46] [V] [TRT] Tactic: -8262349710178828730 Time: 0.79828
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-12:59:46] [V] [TRT] Tactic: -6576203419454146580 Time: 0.274128
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-12:59:46] [V] [TRT] Tactic: -4787320710726427159 Time: 0.301152
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-12:59:46] [V] [TRT] Tactic: -3456450830548107839 Time: 0.276772
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-12:59:46] [V] [TRT] Tactic: -1218658103698133241 Time: 0.454808
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-12:59:46] [V] [TRT] Tactic: -836875257600482091 Time: 0.449564
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-12:59:46] [V] [TRT] Tactic: -410470605513481746 Time: 0.764324
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-12:59:46] [V] [TRT] Tactic: -377491875521947884 Time: 0.778432
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-12:59:46] [V] [TRT] Tactic: -37215280111360163 Time: 0.39032
[07/19/2022-12:59:46] [V] [TRT] Fastest Tactic: 1698681053543049347 Time: 0.263148
[07/19/2022-12:59:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 1698681053543049347
[07/19/2022-12:59:46] [V] [TRT] *************** Autotuning format combination: Float(401408,1,3584,32) -> Float(200704,1,1792,16) ***************
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CudnnConvolution)
[07/19/2022-12:59:46] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CublasConvolution)
[07/19/2022-12:59:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CaskConvolution)
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-12:59:46] [V] [TRT] Tactic: 3886731678879822788 Time: 0.494444
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-12:59:46] [V] [TRT] Tactic: 6629944304117643200 Time: 0.75196
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-12:59:46] [V] [TRT] Tactic: -9153228964338181824 Time: 0.759424
[07/19/2022-12:59:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-12:59:46] [V] [TRT] Tactic: -7394439838318485025 Time: 0.496616
[07/19/2022-12:59:46] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.494444
[07/19/2022-12:59:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-12:59:46] [V] [TRT] *************** Autotuning format combination: Half(401408,12544,112,1) -> Half(200704,12544,112,1) ***************
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CudnnConvolution)
[07/19/2022-12:59:46] [V] [TRT] Tactic: 0 Time: 0.536844
[07/19/2022-12:59:46] [V] [TRT] Tactic: 1 Time: 0.50056
[07/19/2022-12:59:46] [V] [TRT] Tactic: 2 Time: 1.24942
[07/19/2022-12:59:46] [V] [TRT] Tactic: 4 skipped. Scratch requested: 76679168, available: 16777216
[07/19/2022-12:59:46] [V] [TRT] Tactic: 5 Time: 1.38969
[07/19/2022-12:59:46] [V] [TRT] Fastest Tactic: 1 Time: 0.50056
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CublasConvolution)
[07/19/2022-12:59:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CaskConvolution)
[07/19/2022-12:59:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-12:59:46] [V] [TRT] *************** Autotuning format combination: Half(200704,12544:2,112,1) -> Half(200704,12544,112,1) ***************
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CaskConvolution)
[07/19/2022-12:59:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:46] [V] [TRT] *************** Autotuning format combination: Half(200704,12544:2,112,1) -> Half(100352,12544:2,112,1) ***************
[07/19/2022-12:59:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (FusedConvActConvolution)
[07/19/2022-12:59:46] [V] [TRT] Tactic: 589823 Time: 0.358448
[07/19/2022-12:59:46] [V] [TRT] Tactic: 655359 Time: 0.794468
[07/19/2022-12:59:46] [V] [TRT] Tactic: 786431 Time: 0.524016
[07/19/2022-12:59:46] [V] [TRT] Tactic: 851967 Time: 1.42181
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1179647 Time: 0.74854
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1310719 Time: 0.577736
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1376255 Time: 0.351872
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1441791 Time: 0.948276
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1507327 Time: 1.22974
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1638399 Time: 0.53124
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1835007 Time: 0.489352
[07/19/2022-12:59:47] [V] [TRT] Tactic: 1900543 Time: 0.942052
[07/19/2022-12:59:47] [V] [TRT] Tactic: 2162687 Time: 0.437764
[07/19/2022-12:59:47] [V] [TRT] Tactic: 2293759 Time: 0.373316
[07/19/2022-12:59:47] [V] [TRT] Tactic: 2359295 Time: 0.562808
[07/19/2022-12:59:47] [V] [TRT] Tactic: 2686975 Time: 0.588432
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3080191 Time: 1.05473
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3342335 Time: 1.13537
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3407871 Time: 0.482076
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3538943 Time: 0.563552
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3670015 Time: 0.637228
[07/19/2022-12:59:47] [V] [TRT] Tactic: 3932159 Time: 0.786136
[07/19/2022-12:59:48] [V] [TRT] Tactic: 3997695 Time: 0.590584
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4063231 Time: 1.4444
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4194303 Time: 0.473348
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4325375 Time: 0.422072
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4521983 Time: 0.354808
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4587519 Time: 0.563092
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4653055 Time: 0.957844
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4915199 Time: 0.520744
[07/19/2022-12:59:48] [V] [TRT] Tactic: 4980735 Time: 0.417256
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5177343 Time: 0.734248
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5242879 Time: 0.4664
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5373951 Time: 0.738568
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5439487 Time: 0.608444
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5570559 Time: 1.12176
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5636095 Time: 1.44448
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5701631 Time: 0.36022
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5767167 Time: 0.865584
[07/19/2022-12:59:48] [V] [TRT] Tactic: 5832703 Time: 0.4692
[07/19/2022-12:59:49] [V] [TRT] Tactic: 5898239 Time: 0.882256
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6029311 Time: 0.40074
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6225919 Time: 0.540344
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6291455 Time: 0.74994
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6422527 Time: 0.890432
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6750207 Time: 0.4833
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6815743 Time: 0.565772
[07/19/2022-12:59:49] [V] [TRT] Tactic: 6946815 Time: 0.580488
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7077887 Time: 0.529768
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7143423 Time: 0.44158
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7208959 Time: 0.474324
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7340031 Time: 0.914144
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7405567 Time: 0.709268
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7536639 Time: 0.46828
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7602175 Time: 0.446476
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7733247 Time: 0.612448
[07/19/2022-12:59:49] [V] [TRT] Tactic: 7798783 Time: 0.5217
[07/19/2022-12:59:49] [V] [TRT] Tactic: 8191999 Time: 0.45286
[07/19/2022-12:59:49] [V] [TRT] Tactic: 8257535 Time: 0.496864
[07/19/2022-12:59:49] [V] [TRT] Tactic: 8323071 Time: 0.449472
[07/19/2022-12:59:49] [V] [TRT] Tactic: 8650751 Time: 0.445488
[07/19/2022-12:59:49] [V] [TRT] Tactic: 8716287 Time: 0.543848
[07/19/2022-12:59:50] [V] [TRT] Tactic: 9568255 Time: 0.519176
[07/19/2022-12:59:50] [V] [TRT] Tactic: 9895935 Time: 0.47262
[07/19/2022-12:59:50] [V] [TRT] Tactic: 10223615 Time: 0.585864
[07/19/2022-12:59:50] [V] [TRT] Tactic: 10354687 Time: 0.671452
[07/19/2022-12:59:50] [V] [TRT] Tactic: 10551295 Time: 0.352144
[07/19/2022-12:59:50] [V] [TRT] Tactic: 10747903 Time: 0.614328
[07/19/2022-12:59:50] [V] [TRT] Tactic: 10944511 Time: 0.41864
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 1376255 Time: 0.351872
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CudnnConvolution)
[07/19/2022-12:59:50] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CublasConvolution)
[07/19/2022-12:59:50] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D (CaskConvolution)
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-12:59:50] [V] [TRT] Tactic: 3066127711859985668 Time: 0.171004
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-12:59:50] [V] [TRT] Tactic: 3564772625446233998 Time: 0.17752
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-12:59:50] [V] [TRT] Tactic: 5319956359050645452 Time: 0.174172
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-12:59:50] [V] [TRT] Tactic: 7205456024582378848 Time: 0.248052
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-12:59:50] [V] [TRT] Tactic: 8163473458334948789 Time: 0.243428
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-12:59:50] [V] [TRT] Tactic: -4212163711445252890 Time: 0.465772
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-12:59:50] [V] [TRT] Tactic: -3898373634979201110 Time: 0.47156
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-12:59:50] [V] [TRT] Tactic: -2409163523992614473 Time: 0.242612
[07/19/2022-12:59:50] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-12:59:50] [V] [TRT] Tactic: -1716393687483585322 Time: 0.463396
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.171004
[07/19/2022-12:59:50] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,12544,112,1) -> Float(200704,1,1792,16) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.594472
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.232208
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.232208
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,12544,112,1) -> Half(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.177236
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.195256
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.177236
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,12544,112,1) -> Half(100352,12544:2,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.293044
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.119292
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.119292
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,1,1792,16) -> Float(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.59592
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.375576
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.375576
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,1,1792,16) -> Half(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.287548
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.3599
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.287548
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Float(200704,1,1792,16) -> Half(100352,12544:2,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.297768
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.421276
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.297768
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544,112,1) -> Float(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.181692
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.1973
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.181692
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544,112,1) -> Float(200704,1,1792,16) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.275356
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.213924
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.213924
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(200704,12544,112,1) -> Half(100352,12544:2,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.14298
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.116528
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.116528
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(100352,12544:2,112,1) -> Float(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.289108
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.10964
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.10964
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(100352,12544:2,112,1) -> Float(200704,1,1792,16) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.279396
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.2445
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.2445
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning Reformat:Half(100352,12544:2,112,1) -> Half(200704,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1002 Time: 0.794312
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 0.102436
[07/19/2022-12:59:50] [V] [TRT] Fastest Tactic: 0 Time: 0.102436
[07/19/2022-12:59:50] [V] [TRT] *************** Autotuning format combination: Float(200704,12544,112,1) -> Float(1204224,12544,112,1) ***************
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-12:59:50] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-12:59:50] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:50] [V] [TRT] Tactic: 0 Time: 3.25272
[07/19/2022-12:59:50] [V] [TRT] Tactic: 1 Time: 2.75291
[07/19/2022-12:59:50] [V] [TRT] Tactic: 2 Time: 3.69308
[07/19/2022-12:59:50] [V] [TRT] Tactic: 4 skipped. Scratch requested: 208738304, available: 16777216
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5 Time: 4.26249
[07/19/2022-12:59:51] [V] [TRT] Fastest Tactic: 1 Time: 2.75291
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-12:59:51] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-12:59:51] [V] [TRT] Tactic: 1062367460111450758 Time: 0.673408
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-12:59:51] [V] [TRT] Tactic: 1698681053543049347 Time: 0.6326
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-12:59:51] [V] [TRT] Tactic: 4501471010995462441 Time: 0.695164
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5137655947464784826 Time: 0.66464
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5288347012147084929 Time: 0.706164
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5326823351883942011 Time: 0.682028
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5500448035057547314 Time: 0.732452
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-12:59:51] [V] [TRT] Tactic: 6645123197870846056 Time: 0.6694
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-12:59:51] [V] [TRT] Tactic: 7144526460361122478 Time: 0.70582
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-12:59:51] [V] [TRT] Tactic: -8262349710178828730 Time: 0.717356
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-12:59:51] [V] [TRT] Tactic: -6576203419454146580 Time: 0.651432
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-12:59:51] [V] [TRT] Tactic: -4787320710726427159 Time: 0.70472
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-12:59:51] [V] [TRT] Tactic: -3456450830548107839 Time: 0.665884
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-12:59:51] [V] [TRT] Tactic: -1218658103698133241 Time: 0.743004
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-12:59:51] [V] [TRT] Tactic: -836875257600482091 Time: 0.743516
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-12:59:51] [V] [TRT] Tactic: -410470605513481746 Time: 0.69026
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-12:59:51] [V] [TRT] Tactic: -377491875521947884 Time: 0.699048
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-12:59:51] [V] [TRT] Tactic: -37215280111360163 Time: 0.665332
[07/19/2022-12:59:51] [V] [TRT] Fastest Tactic: 1698681053543049347 Time: 0.6326
[07/19/2022-12:59:51] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 1698681053543049347
[07/19/2022-12:59:51] [V] [TRT] *************** Autotuning format combination: Float(200704,1,1792,16) -> Float(1204224,1,10752,96) ***************
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:51] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-12:59:51] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-12:59:51] [V] [TRT] Tactic: 3886731678879822788 Time: 0.831408
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-12:59:51] [V] [TRT] Tactic: 6629944304117643200 Time: 2.14423
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-12:59:51] [V] [TRT] Tactic: -9153228964338181824 Time: 2.17807
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-12:59:51] [V] [TRT] Tactic: -7394439838318485025 Time: 0.91746
[07/19/2022-12:59:51] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.831408
[07/19/2022-12:59:51] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-12:59:51] [V] [TRT] *************** Autotuning format combination: Half(200704,12544,112,1) -> Half(1204224,12544,112,1) ***************
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:51] [V] [TRT] Tactic: 0 Time: 2.7946
[07/19/2022-12:59:51] [V] [TRT] Tactic: 1 Time: 2.64586
[07/19/2022-12:59:51] [V] [TRT] Tactic: 2 Time: 3.18477
[07/19/2022-12:59:51] [V] [TRT] Tactic: 4 skipped. Scratch requested: 208738304, available: 16777216
[07/19/2022-12:59:51] [V] [TRT] Tactic: 5 Time: 4.0547
[07/19/2022-12:59:51] [V] [TRT] Fastest Tactic: 1 Time: 2.64586
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-12:59:51] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:51] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-12:59:51] [V] [TRT] *************** Autotuning format combination: Half(100352,12544:2,112,1) -> Half(1204224,12544,112,1) ***************
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:51] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] *************** Autotuning format combination: Half(100352,12544:2,112,1) -> Half(602112,12544:2,112,1) ***************
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-12:59:51] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:51] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-12:59:51] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-12:59:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-12:59:51] [V] [TRT] Tactic: 3066127711859985668 Time: 0.42408
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-12:59:51] [V] [TRT] Tactic: 3564772625446233998 Time: 0.431924
[07/19/2022-12:59:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-12:59:52] [V] [TRT] Tactic: 5319956359050645452 Time: 0.43146
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-12:59:52] [V] [TRT] Tactic: 7205456024582378848 Time: 0.419264
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-12:59:52] [V] [TRT] Tactic: 8163473458334948789 Time: 0.42058
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-12:59:52] [V] [TRT] Tactic: -4212163711445252890 Time: 0.432012
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-12:59:52] [V] [TRT] Tactic: -3898373634979201110 Time: 0.434056
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-12:59:52] [V] [TRT] Tactic: -2409163523992614473 Time: 0.41614
[07/19/2022-12:59:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-12:59:52] [V] [TRT] Tactic: -1716393687483585322 Time: 0.423416
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: -2409163523992614473 Time: 0.41614
[07/19/2022-12:59:52] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -2409163523992614473
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,12544,112,1) -> Float(1204224,1,10752,96) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.23173
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 2.04097
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 1.23173
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,12544,112,1) -> Half(1204224,12544,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.03931
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 1.15465
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 1.03931
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,12544,112,1) -> Half(602112,12544:2,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.94501
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 0.69504
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 0 Time: 0.69504
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,1,10752,96) -> Float(1204224,12544,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.59096
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 5.063
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 1.59096
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,1,10752,96) -> Half(1204224,12544,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 0.961984
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 4.96962
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 0.961984
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Float(1204224,1,10752,96) -> Half(602112,12544:2,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 2.0153
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 5.48446
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 2.0153
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Half(1204224,12544,112,1) -> Float(1204224,12544,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.14105
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 1.16152
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 1.14105
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Half(1204224,12544,112,1) -> Float(1204224,1,10752,96) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 0.761548
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 1.73344
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 1002 Time: 0.761548
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Half(1204224,12544,112,1) -> Half(602112,12544:2,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 0.77716
[07/19/2022-12:59:52] [V] [TRT] Tactic: 0 Time: 0.677012
[07/19/2022-12:59:52] [V] [TRT] Fastest Tactic: 0 Time: 0.677012
[07/19/2022-12:59:52] [V] [TRT] *************** Autotuning Reformat:Half(602112,12544:2,112,1) -> Float(1204224,12544,112,1) ***************
[07/19/2022-12:59:52] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:52] [V] [TRT] Tactic: 1002 Time: 1.5705
[07/19/2022-12:59:53] [V] [TRT] Tactic: 0 Time: 0.63888
[07/19/2022-12:59:53] [V] [TRT] Fastest Tactic: 0 Time: 0.63888
[07/19/2022-12:59:53] [V] [TRT] *************** Autotuning Reformat:Half(602112,12544:2,112,1) -> Float(1204224,1,10752,96) ***************
[07/19/2022-12:59:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:53] [V] [TRT] Tactic: 1002 Time: 0.839224
[07/19/2022-12:59:53] [V] [TRT] Tactic: 0 Time: 1.44735
[07/19/2022-12:59:53] [V] [TRT] Fastest Tactic: 1002 Time: 0.839224
[07/19/2022-12:59:53] [V] [TRT] *************** Autotuning Reformat:Half(602112,12544:2,112,1) -> Half(1204224,12544,112,1) ***************
[07/19/2022-12:59:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-12:59:53] [V] [TRT] Tactic: 1002 Time: 2.19664
[07/19/2022-12:59:53] [V] [TRT] Tactic: 0 Time: 0.7488
[07/19/2022-12:59:53] [V] [TRT] Fastest Tactic: 0 Time: 0.7488
[07/19/2022-12:59:53] [V] [TRT] *************** Autotuning format combination: Float(1204224,12544,112,1) -> Float(301056,3136,56,1) ***************
[07/19/2022-12:59:53] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-12:59:53] [V] [TRT] Tactic: -1 Time: 0.758596
[07/19/2022-12:59:53] [V] [TRT] Fastest Tactic: -1 Time: 0.758596
[07/19/2022-12:59:53] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-12:59:53] [V] [TRT] Tactic: 0 Time: 1.97949
[07/19/2022-12:59:53] [V] [TRT] Tactic: 1 Time: 1.9728
[07/19/2022-12:59:53] [V] [TRT] Tactic: 2 Time: 1.99129
[07/19/2022-12:59:57] [V] [TRT] Tactic: 5 Time: 234.544
[07/19/2022-12:59:57] [V] [TRT] Fastest Tactic: 1 Time: 1.9728
[07/19/2022-12:59:57] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-12:59:57] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-12:59:57] [V] [TRT] Tactic: 1062367460111450758 Time: 5.31468
[07/19/2022-12:59:57] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-12:59:57] [V] [TRT] Tactic: 1754984623894446479 Time: 4.48703
[07/19/2022-12:59:57] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-12:59:57] [V] [TRT] Tactic: 3611739942397549984 Time: 15.3869
[07/19/2022-12:59:57] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-12:59:57] [V] [TRT] Tactic: 4337000649858996379 Time: 7.54109
[07/19/2022-12:59:57] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-12:59:58] [V] [TRT] Tactic: 4501471010995462441 Time: 14.4796
[07/19/2022-12:59:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-12:59:58] [V] [TRT] Tactic: 5137655947464784826 Time: 7.37248
[07/19/2022-12:59:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-12:59:58] [V] [TRT] Tactic: 5288347012147084929 Time: 15.3839
[07/19/2022-12:59:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-12:59:58] [V] [TRT] Tactic: 6645123197870846056 Time: 7.51176
[07/19/2022-12:59:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-12:59:58] [V] [TRT] Tactic: 7144526460361122478 Time: 4.4079
[07/19/2022-12:59:59] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-12:59:59] [V] [TRT] Tactic: -9137461792520977713 Time: 14.5154
[07/19/2022-12:59:59] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-12:59:59] [V] [TRT] Tactic: -8262349710178828730 Time: 15.4001
[07/19/2022-12:59:59] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-12:59:59] [V] [TRT] Tactic: -8133971918129952780 Time: 7.39414
[07/19/2022-12:59:59] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-12:59:59] [V] [TRT] Tactic: -6092040395344634144 Time: 5.3507
[07/19/2022-12:59:59] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-12:59:59] [V] [TRT] Tactic: -4787320710726427159 Time: 4.49232
[07/19/2022-13:00:00] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:00] [V] [TRT] Tactic: -3456450830548107839 Time: 5.13268
[07/19/2022-13:00:00] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:00] [V] [TRT] Tactic: -1218658103698133241 Time: 7.40178
[07/19/2022-13:00:00] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:00] [V] [TRT] Tactic: -836875257600482091 Time: 7.3061
[07/19/2022-13:00:00] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:00] [V] [TRT] Tactic: -410470605513481746 Time: 14.3473
[07/19/2022-13:00:00] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 4.4079
[07/19/2022-13:00:00] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:00:00] [V] [TRT] *************** Autotuning format combination: Float(1204224,1,10752,96) -> Float(301056,1,5376,96) ***************
[07/19/2022-13:00:00] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:00] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:00] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:00] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:00] [V] [TRT] *************** Autotuning format combination: Half(1204224,12544,112,1) -> Half(301056,3136,56,1) ***************
[07/19/2022-13:00:00] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:00] [V] [TRT] Tactic: 0 Time: 1.57878
[07/19/2022-13:00:00] [V] [TRT] Tactic: 1 Time: 1.57791
[07/19/2022-13:00:00] [V] [TRT] Tactic: 2 Time: 1.78491
[07/19/2022-13:00:04] [V] [TRT] Tactic: 5 Time: 233.001
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1 Time: 1.57791
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:04] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:04] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning format combination: Half(602112,12544:2,112,1) -> Half(150528,3136:2,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:04] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,3136,56,1) -> Float(301056,1,5376,96) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.31792
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.45052
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1002 Time: 0.31792
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,3136,56,1) -> Half(301056,3136,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.292432
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.290312
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 0 Time: 0.290312
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,3136,56,1) -> Half(150528,3136:2,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.456944
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.176216
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 0 Time: 0.176216
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,1,5376,96) -> Float(301056,3136,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.437892
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.589608
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1002 Time: 0.437892
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,1,5376,96) -> Half(301056,3136,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.267204
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.55756
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1002 Time: 0.267204
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Float(301056,1,5376,96) -> Half(150528,3136:2,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.44086
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.58342
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1002 Time: 0.44086
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Half(301056,3136,56,1) -> Float(301056,3136,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.296252
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.28978
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 0 Time: 0.28978
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Half(301056,3136,56,1) -> Float(301056,1,5376,96) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.18672
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.379924
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 1002 Time: 0.18672
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Half(301056,3136,56,1) -> Half(150528,3136:2,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.207816
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.173008
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 0 Time: 0.173008
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Half(150528,3136:2,56,1) -> Float(301056,3136,56,1) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:04] [V] [TRT] Tactic: 1002 Time: 0.427132
[07/19/2022-13:00:04] [V] [TRT] Tactic: 0 Time: 0.162316
[07/19/2022-13:00:04] [V] [TRT] Fastest Tactic: 0 Time: 0.162316
[07/19/2022-13:00:04] [V] [TRT] *************** Autotuning Reformat:Half(150528,3136:2,56,1) -> Float(301056,1,5376,96) ***************
[07/19/2022-13:00:04] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1002 Time: 0.20866
[07/19/2022-13:00:05] [V] [TRT] Tactic: 0 Time: 0.36478
[07/19/2022-13:00:05] [V] [TRT] Fastest Tactic: 1002 Time: 0.20866
[07/19/2022-13:00:05] [V] [TRT] *************** Autotuning Reformat:Half(150528,3136:2,56,1) -> Half(301056,3136,56,1) ***************
[07/19/2022-13:00:05] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1002 Time: 0.596572
[07/19/2022-13:00:05] [V] [TRT] Tactic: 0 Time: 0.152468
[07/19/2022-13:00:05] [V] [TRT] Fastest Tactic: 0 Time: 0.152468
[07/19/2022-13:00:05] [V] [TRT] *************** Autotuning format combination: Float(301056,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:05] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:00:05] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:05] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:05] [V] [TRT] Tactic: 589823 Time: 0.39134
[07/19/2022-13:00:05] [V] [TRT] Tactic: 655359 Time: 0.546092
[07/19/2022-13:00:05] [V] [TRT] Tactic: 786431 Time: 0.418344
[07/19/2022-13:00:05] [V] [TRT] Tactic: 851967 Time: 0.92546
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1179647 Time: 0.469808
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1310719 Time: 0.606376
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1376255 Time: 0.474888
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1441791 Time: 0.587228
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1507327 Time: 0.847692
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1638399 Time: 0.452372
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1835007 Time: 0.42568
[07/19/2022-13:00:05] [V] [TRT] Tactic: 1900543 Time: 0.905984
[07/19/2022-13:00:05] [V] [TRT] Tactic: 2097151 Time: 0.43504
[07/19/2022-13:00:05] [V] [TRT] Tactic: 2162687 Time: 0.514516
[07/19/2022-13:00:05] [V] [TRT] Tactic: 2293759 Time: 0.45224
[07/19/2022-13:00:05] [V] [TRT] Tactic: 2359295 Time: 0.475508
[07/19/2022-13:00:05] [V] [TRT] Tactic: 2686975 Time: 0.4483
[07/19/2022-13:00:05] [V] [TRT] Tactic: 3080191 Time: 0.734048
[07/19/2022-13:00:05] [V] [TRT] Tactic: 3342335 Time: 0.902512
[07/19/2022-13:00:06] [V] [TRT] Tactic: 3407871 Time: 0.427776
[07/19/2022-13:00:06] [V] [TRT] Tactic: 3538943 Time: 0.407488
[07/19/2022-13:00:06] [V] [TRT] Tactic: 3670015 Time: 0.5929
[07/19/2022-13:00:06] [V] [TRT] Tactic: 3932159 Time: 0.754152
[07/19/2022-13:00:06] [V] [TRT] Tactic: 3997695 Time: 0.423344
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4063231 Time: 0.875536
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4194303 Time: 0.374564
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4259839 Time: 0.388692
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4325375 Time: 0.389956
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4521983 Time: 0.460168
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4587519 Time: 0.387848
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4653055 Time: 0.5754
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4915199 Time: 0.37788
[07/19/2022-13:00:06] [V] [TRT] Tactic: 4980735 Time: 0.402824
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5177343 Time: 0.500172
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5242879 Time: 0.441276
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5373951 Time: 0.649064
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5439487 Time: 0.680904
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5570559 Time: 0.612636
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5636095 Time: 0.875684
[07/19/2022-13:00:06] [V] [TRT] Tactic: 5701631 Time: 0.518624
[07/19/2022-13:00:07] [V] [TRT] Tactic: 5767167 Time: 1.41504
[07/19/2022-13:00:07] [V] [TRT] Tactic: 5832703 Time: 0.41208
[07/19/2022-13:00:07] [V] [TRT] Tactic: 5898239 Time: 0.41316
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6029311 Time: 0.45556
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6225919 Time: 0.41426
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6291455 Time: 0.46974
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6422527 Time: 0.712656
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6750207 Time: 0.426748
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6815743 Time: 0.677484
[07/19/2022-13:00:07] [V] [TRT] Tactic: 6946815 Time: 0.65734
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7012351 Time: 0.433648
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7077887 Time: 0.389576
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7143423 Time: 0.48694
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7208959 Time: 0.461436
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7340031 Time: 0.413052
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7405567 Time: 0.505008
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7536639 Time: 0.526872
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7602175 Time: 0.415768
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7733247 Time: 0.435884
[07/19/2022-13:00:07] [V] [TRT] Tactic: 7798783 Time: 0.417548
[07/19/2022-13:00:07] [V] [TRT] Tactic: 8191999 Time: 0.460644
[07/19/2022-13:00:07] [V] [TRT] Tactic: 8257535 Time: 0.377
[07/19/2022-13:00:07] [V] [TRT] Tactic: 8323071 Time: 0.437836
[07/19/2022-13:00:07] [V] [TRT] Tactic: 8650751 Time: 0.459916
[07/19/2022-13:00:08] [V] [TRT] Tactic: 8716287 Time: 0.679352
[07/19/2022-13:00:08] [V] [TRT] Tactic: 9109503 Time: 0.430168
[07/19/2022-13:00:08] [V] [TRT] Tactic: 9568255 Time: 0.378808
[07/19/2022-13:00:08] [V] [TRT] Tactic: 9895935 Time: 0.37384
[07/19/2022-13:00:08] [V] [TRT] Tactic: 10223615 Time: 0.446984
[07/19/2022-13:00:08] [V] [TRT] Tactic: 10354687 Time: 0.378352
[07/19/2022-13:00:08] [V] [TRT] Tactic: 10551295 Time: 0.402768
[07/19/2022-13:00:08] [V] [TRT] Tactic: 10747903 Time: 0.4566
[07/19/2022-13:00:08] [V] [TRT] Tactic: 10944511 Time: 0.402764
[07/19/2022-13:00:08] [V] [TRT] Fastest Tactic: 9895935 Time: 0.37384
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:08] [V] [TRT] Tactic: 0 Time: 0.276764
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1 Time: 0.264032
[07/19/2022-13:00:08] [V] [TRT] Tactic: 2 Time: 0.762588
[07/19/2022-13:00:08] [V] [TRT] Tactic: 4 skipped. Scratch requested: 84354048, available: 16777216
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5 Time: 0.890004
[07/19/2022-13:00:08] [V] [TRT] Fastest Tactic: 1 Time: 0.264032
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:08] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1062367460111450758 Time: 0.150992
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1698681053543049347 Time: 0.149416
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:08] [V] [TRT] Tactic: 4501471010995462441 Time: 0.37806
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5137655947464784826 Time: 0.199748
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5288347012147084929 Time: 0.383876
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5326823351883942011 Time: 0.368428
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5500448035057547314 Time: 0.234808
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:08] [V] [TRT] Tactic: 6645123197870846056 Time: 0.203476
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:08] [V] [TRT] Tactic: 7144526460361122478 Time: 0.15874
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:08] [V] [TRT] Tactic: -8262349710178828730 Time: 0.387736
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:08] [V] [TRT] Tactic: -6576203419454146580 Time: 0.140328
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:08] [V] [TRT] Tactic: -4787320710726427159 Time: 0.161344
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:08] [V] [TRT] Tactic: -3456450830548107839 Time: 0.145136
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:08] [V] [TRT] Tactic: -1218658103698133241 Time: 0.245196
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:08] [V] [TRT] Tactic: -836875257600482091 Time: 0.242732
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:08] [V] [TRT] Tactic: -410470605513481746 Time: 0.37186
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:08] [V] [TRT] Tactic: -377491875521947884 Time: 0.378476
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:08] [V] [TRT] Tactic: -37215280111360163 Time: 0.199036
[07/19/2022-13:00:08] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.140328
[07/19/2022-13:00:08] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:00:08] [V] [TRT] *************** Autotuning format combination: Float(301056,1,5376,96) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:08] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:08] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:08] [V] [TRT] Tactic: 3886731678879822788 Time: 0.223116
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:08] [V] [TRT] Tactic: 6629944304117643200 Time: 0.265376
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:08] [V] [TRT] Tactic: -9153228964338181824 Time: 0.268148
[07/19/2022-13:00:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:08] [V] [TRT] Tactic: -7394439838318485025 Time: 0.223512
[07/19/2022-13:00:08] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.223116
[07/19/2022-13:00:08] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:08] [V] [TRT] *************** Autotuning format combination: Half(301056,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:08] [V] [TRT] Tactic: 0 Time: 0.271176
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1 Time: 0.263496
[07/19/2022-13:00:08] [V] [TRT] Tactic: 2 Time: 0.741564
[07/19/2022-13:00:08] [V] [TRT] Tactic: 4 skipped. Scratch requested: 84354048, available: 16777216
[07/19/2022-13:00:08] [V] [TRT] Tactic: 5 Time: 0.884324
[07/19/2022-13:00:08] [V] [TRT] Fastest Tactic: 1 Time: 0.263496
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:08] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:08] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:08] [V] [TRT] *************** Autotuning format combination: Half(150528,3136:2,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:08] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:08] [V] [TRT] *************** Autotuning format combination: Half(150528,3136:2,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:08] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:08] [V] [TRT] Tactic: 589823 Time: 0.216236
[07/19/2022-13:00:08] [V] [TRT] Tactic: 655359 Time: 0.41774
[07/19/2022-13:00:08] [V] [TRT] Tactic: 786431 Time: 0.250868
[07/19/2022-13:00:08] [V] [TRT] Tactic: 851967 Time: 0.6275
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1179647 Time: 0.288424
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1310719 Time: 0.32072
[07/19/2022-13:00:08] [V] [TRT] Tactic: 1376255 Time: 0.238656
[07/19/2022-13:00:09] [V] [TRT] Tactic: 1441791 Time: 0.3511
[07/19/2022-13:00:09] [V] [TRT] Tactic: 1507327 Time: 0.531984
[07/19/2022-13:00:09] [V] [TRT] Tactic: 1638399 Time: 0.246468
[07/19/2022-13:00:09] [V] [TRT] Tactic: 1835007 Time: 0.241688
[07/19/2022-13:00:09] [V] [TRT] Tactic: 1900543 Time: 0.504728
[07/19/2022-13:00:09] [V] [TRT] Tactic: 2162687 Time: 0.28138
[07/19/2022-13:00:09] [V] [TRT] Tactic: 2293759 Time: 0.24582
[07/19/2022-13:00:09] [V] [TRT] Tactic: 2359295 Time: 0.26864
[07/19/2022-13:00:09] [V] [TRT] Tactic: 2686975 Time: 0.409168
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3080191 Time: 0.479412
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3342335 Time: 0.5535
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3407871 Time: 0.249488
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3538943 Time: 0.261144
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3670015 Time: 0.440196
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3932159 Time: 0.37928
[07/19/2022-13:00:09] [V] [TRT] Tactic: 3997695 Time: 0.264824
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4063231 Time: 0.588028
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4194303 Time: 0.2084
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4325375 Time: 0.209512
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4521983 Time: 0.224856
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4587519 Time: 0.239244
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4653055 Time: 0.381196
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4915199 Time: 0.214212
[07/19/2022-13:00:09] [V] [TRT] Tactic: 4980735 Time: 0.21928
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5177343 Time: 0.293892
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5242879 Time: 0.240868
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5373951 Time: 0.331136
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5439487 Time: 0.340844
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5570559 Time: 0.493316
[07/19/2022-13:00:09] [V] [TRT] Tactic: 5636095 Time: 0.588148
[07/19/2022-13:00:10] [V] [TRT] Tactic: 5701631 Time: 0.236568
[07/19/2022-13:00:10] [V] [TRT] Tactic: 5767167 Time: 0.620296
[07/19/2022-13:00:10] [V] [TRT] Tactic: 5832703 Time: 0.237472
[07/19/2022-13:00:10] [V] [TRT] Tactic: 5898239 Time: 0.329132
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6029311 Time: 0.254788
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6225919 Time: 0.249152
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6291455 Time: 0.28884
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6422527 Time: 0.435308
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6750207 Time: 0.22944
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6815743 Time: 0.319516
[07/19/2022-13:00:10] [V] [TRT] Tactic: 6946815 Time: 0.322156
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7077887 Time: 0.2421
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7143423 Time: 0.248476
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7208959 Time: 0.246108
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7340031 Time: 0.332768
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7405567 Time: 0.298052
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7536639 Time: 0.293212
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7602175 Time: 0.2173
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7733247 Time: 0.25928
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7798783 Time: 0.25126
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8191999 Time: 0.246344
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8257535 Time: 0.20314
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8323071 Time: 0.230736
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8650751 Time: 0.238916
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8716287 Time: 0.33052
[07/19/2022-13:00:10] [V] [TRT] Tactic: 9568255 Time: 0.21394
[07/19/2022-13:00:10] [V] [TRT] Tactic: 9895935 Time: 0.208668
[07/19/2022-13:00:10] [V] [TRT] Tactic: 10223615 Time: 0.409744
[07/19/2022-13:00:10] [V] [TRT] Tactic: 10354687 Time: 0.25514
[07/19/2022-13:00:10] [V] [TRT] Tactic: 10551295 Time: 0.202188
[07/19/2022-13:00:10] [V] [TRT] Tactic: 10747903 Time: 0.26204
[07/19/2022-13:00:10] [V] [TRT] Tactic: 10944511 Time: 0.219252
[07/19/2022-13:00:10] [V] [TRT] Fastest Tactic: 10551295 Time: 0.202188
[07/19/2022-13:00:10] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:10] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:10] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:10] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:10] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:10] [V] [TRT] Tactic: 3066127711859985668 Time: 0.087628
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:10] [V] [TRT] Tactic: 3564772625446233998 Time: 0.093004
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:10] [V] [TRT] Tactic: 5319956359050645452 Time: 0.087488
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:10] [V] [TRT] Tactic: 7205456024582378848 Time: 0.114888
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:10] [V] [TRT] Tactic: 8163473458334948789 Time: 0.111456
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:10] [V] [TRT] Tactic: -4212163711445252890 Time: 0.205672
[07/19/2022-13:00:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:11] [V] [TRT] Tactic: -3898373634979201110 Time: 0.209932
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:11] [V] [TRT] Tactic: -2409163523992614473 Time: 0.112192
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:11] [V] [TRT] Tactic: -1716393687483585322 Time: 0.204712
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 5319956359050645452 Time: 0.087488
[07/19/2022-13:00:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5319956359050645452
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.155456
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.109628
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.109628
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.07652
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.076456
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.076456
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.103772
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.047252
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.047252
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.163292
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.094728
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.094728
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.079136
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.093492
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.079136
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.089136
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.10518
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.089136
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.077728
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.076804
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.076804
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.072976
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.096124
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.072976
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.069796
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.045984
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.045984
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.108716
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.04322
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.04322
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.074608
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.094548
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.074608
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.210736
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.040816
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.040816
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.154652
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.109488
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.109488
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.076648
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.077292
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.076648
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.103924
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.047008
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.047008
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.16358
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.094724
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.094724
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.079124
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.093456
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.079124
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.089368
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.105272
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.089368
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.077608
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.07686
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.07686
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.074188
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.097032
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.074188
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.07046
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.0459
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.0459
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.10954
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.043564
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.043564
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.074912
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.094472
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.074912
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1002 Time: 0.210944
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 0.040828
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 0 Time: 0.040828
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning format combination: Float(75264,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:11] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:11] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 1.25596
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1 Time: 0.991992
[07/19/2022-13:00:11] [V] [TRT] Tactic: 2 Time: 1.44027
[07/19/2022-13:00:11] [V] [TRT] Tactic: 4 skipped. Scratch requested: 118420992, available: 16777216
[07/19/2022-13:00:11] [V] [TRT] Tactic: 5 Time: 1.60065
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: 1 Time: 0.991992
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1062367460111450758 Time: 0.317372
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1698681053543049347 Time: 0.29576
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:11] [V] [TRT] Tactic: 4501471010995462441 Time: 0.381616
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:11] [V] [TRT] Tactic: 5137655947464784826 Time: 0.290164
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:11] [V] [TRT] Tactic: 5288347012147084929 Time: 0.388644
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:11] [V] [TRT] Tactic: 5326823351883942011 Time: 0.372852
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:11] [V] [TRT] Tactic: 5500448035057547314 Time: 0.315984
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:11] [V] [TRT] Tactic: 6645123197870846056 Time: 0.290224
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:11] [V] [TRT] Tactic: 7144526460361122478 Time: 0.328656
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:11] [V] [TRT] Tactic: -8262349710178828730 Time: 0.390432
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:11] [V] [TRT] Tactic: -6576203419454146580 Time: 0.305276
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:11] [V] [TRT] Tactic: -4787320710726427159 Time: 0.328632
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:11] [V] [TRT] Tactic: -3456450830548107839 Time: 0.310652
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:11] [V] [TRT] Tactic: -1218658103698133241 Time: 0.324524
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:11] [V] [TRT] Tactic: -836875257600482091 Time: 0.322852
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:11] [V] [TRT] Tactic: -410470605513481746 Time: 0.37444
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:11] [V] [TRT] Tactic: -377491875521947884 Time: 0.38518
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:11] [V] [TRT] Tactic: -37215280111360163 Time: 0.289608
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.289608
[07/19/2022-13:00:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,1344,24) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:11] [V] [TRT] Tactic: 3886731678879822788 Time: 0.39386
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:11] [V] [TRT] Tactic: 6629944304117643200 Time: 0.916944
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:11] [V] [TRT] Tactic: -9153228964338181824 Time: 0.930844
[07/19/2022-13:00:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:11] [V] [TRT] Tactic: -7394439838318485025 Time: 0.391324
[07/19/2022-13:00:11] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.391324
[07/19/2022-13:00:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:00:11] [V] [TRT] *************** Autotuning format combination: Half(75264,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:11] [V] [TRT] Tactic: 0 Time: 1.08607
[07/19/2022-13:00:11] [V] [TRT] Tactic: 1 Time: 0.991144
[07/19/2022-13:00:12] [V] [TRT] Tactic: 2 Time: 1.3075
[07/19/2022-13:00:12] [V] [TRT] Tactic: 4 skipped. Scratch requested: 118420992, available: 16777216
[07/19/2022-13:00:12] [V] [TRT] Tactic: 5 Time: 1.65554
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1 Time: 0.991144
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:12] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:12] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning format combination: Half(37632,3136:2,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:12] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning format combination: Half(37632,3136:2,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:12] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:12] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:12] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:12] [V] [TRT] Tactic: 3066127711859985668 Time: 0.20818
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:12] [V] [TRT] Tactic: 3564772625446233998 Time: 0.214844
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:12] [V] [TRT] Tactic: 5319956359050645452 Time: 0.211968
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:12] [V] [TRT] Tactic: 7205456024582378848 Time: 0.18902
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:12] [V] [TRT] Tactic: 8163473458334948789 Time: 0.187544
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:12] [V] [TRT] Tactic: -4212163711445252890 Time: 0.251452
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:12] [V] [TRT] Tactic: -3898373634979201110 Time: 0.253228
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:12] [V] [TRT] Tactic: -2409163523992614473 Time: 0.187896
[07/19/2022-13:00:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:12] [V] [TRT] Tactic: -1716393687483585322 Time: 0.247556
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.187544
[07/19/2022-13:00:12] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 8163473458334948789
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.453892
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.673884
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.453892
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.435056
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.428012
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.428012
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.644896
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.261944
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.261944
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.666008
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 1.00566
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.666008
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.419692
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.952872
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.419692
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.615924
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.997768
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.615924
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.438584
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.417064
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.417064
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.313824
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.591756
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.313824
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.304916
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.256856
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.256856
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.634828
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.241284
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.241284
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.323684
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.545212
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 1002 Time: 0.323684
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1002 Time: 0.995404
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 0.227688
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: 0 Time: 0.227688
[07/19/2022-13:00:12] [V] [TRT] *************** Autotuning format combination: Float(451584,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:12] [V] [TRT] Tactic: -1 Time: 0.435356
[07/19/2022-13:00:12] [V] [TRT] Fastest Tactic: -1 Time: 0.435356
[07/19/2022-13:00:12] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:12] [V] [TRT] Tactic: 0 Time: 1.18559
[07/19/2022-13:00:12] [V] [TRT] Tactic: 1 Time: 1.18504
[07/19/2022-13:00:12] [V] [TRT] Tactic: 2 Time: 1.43951
[07/19/2022-13:00:13] [V] [TRT] Tactic: 4 Time: 54.9094
[07/19/2022-13:00:15] [V] [TRT] Tactic: 5 Time: 98.6978
[07/19/2022-13:00:15] [V] [TRT] Tactic: 6 Time: 30.7836
[07/19/2022-13:00:15] [V] [TRT] Fastest Tactic: 1 Time: 1.18504
[07/19/2022-13:00:15] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:16] [V] [TRT] Tactic: 1062367460111450758 Time: 7.8273
[07/19/2022-13:00:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:00:16] [V] [TRT] Tactic: 1754984623894446479 Time: 6.58869
[07/19/2022-13:00:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:00:16] [V] [TRT] Tactic: 3611739942397549984 Time: 22.8879
[07/19/2022-13:00:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-13:00:17] [V] [TRT] Tactic: 3827454225649558724 Time: 21.7564
[07/19/2022-13:00:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:00:17] [V] [TRT] Tactic: 4337000649858996379 Time: 11.2972
[07/19/2022-13:00:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:17] [V] [TRT] Tactic: 4501471010995462441 Time: 21.5587
[07/19/2022-13:00:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:17] [V] [TRT] Tactic: 5137655947464784826 Time: 10.9291
[07/19/2022-13:00:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:18] [V] [TRT] Tactic: 5288347012147084929 Time: 22.7507
[07/19/2022-13:00:18] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-13:00:18] [V] [TRT] Tactic: 5921334924264294896 Time: 14.4768
[07/19/2022-13:00:18] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:18] [V] [TRT] Tactic: 6645123197870846056 Time: 11.1961
[07/19/2022-13:00:18] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:19] [V] [TRT] Tactic: 7144526460361122478 Time: 6.39444
[07/19/2022-13:00:19] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-13:00:19] [V] [TRT] Tactic: 7852627285308570038 Time: 23.1376
[07/19/2022-13:00:19] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:00:19] [V] [TRT] Tactic: -9137461792520977713 Time: 21.8225
[07/19/2022-13:00:19] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-13:00:20] [V] [TRT] Tactic: -8776506421218919509 Time: 21.4733
[07/19/2022-13:00:20] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:20] [V] [TRT] Tactic: -8262349710178828730 Time: 22.9152
[07/19/2022-13:00:20] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:00:20] [V] [TRT] Tactic: -8133971918129952780 Time: 10.8919
[07/19/2022-13:00:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:00:21] [V] [TRT] Tactic: -6092040395344634144 Time: 8.10551
[07/19/2022-13:00:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:21] [V] [TRT] Tactic: -4787320710726427159 Time: 6.6019
[07/19/2022-13:00:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:21] [V] [TRT] Tactic: -3456450830548107839 Time: 7.50666
[07/19/2022-13:00:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-13:00:21] [V] [TRT] Tactic: -2318106587342035239 Time: 21.947
[07/19/2022-13:00:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-13:00:22] [V] [TRT] Tactic: -1343271414618805657 Time: 14.2358
[07/19/2022-13:00:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:22] [V] [TRT] Tactic: -1218658103698133241 Time: 10.9033
[07/19/2022-13:00:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:22] [V] [TRT] Tactic: -836875257600482091 Time: 11.0412
[07/19/2022-13:00:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:23] [V] [TRT] Tactic: -410470605513481746 Time: 21.327
[07/19/2022-13:00:23] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 6.39444
[07/19/2022-13:00:23] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:00:23] [V] [TRT] *************** Autotuning format combination: Float(451584,1,8064,144) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:23] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:23] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:23] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:23] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:23] [V] [TRT] *************** Autotuning format combination: Half(451584,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:23] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:23] [V] [TRT] Tactic: 0 Time: 0.9011
[07/19/2022-13:00:23] [V] [TRT] Tactic: 1 Time: 0.899468
[07/19/2022-13:00:23] [V] [TRT] Tactic: 2 Time: 19.222
[07/19/2022-13:00:24] [V] [TRT] Tactic: 4 Time: 55.2157
[07/19/2022-13:00:26] [V] [TRT] Tactic: 5 Time: 99.0323
[07/19/2022-13:00:26] [V] [TRT] Tactic: 6 Time: 46.941
[07/19/2022-13:00:26] [V] [TRT] Fastest Tactic: 1 Time: 0.899468
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:26] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning format combination: Half(225792,3136:2,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] *************** Autotuning format combination: Float(451584,3136,56,1), Float(75264,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CudaDepthwiseConvolution)
[07/19/2022-13:00:26] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (FusedConvActConvolution)
[07/19/2022-13:00:26] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CudnnConvolution)
[07/19/2022-13:00:26] [V] [TRT] Tactic: 0 Time: 0.40628
[07/19/2022-13:00:26] [V] [TRT] Tactic: 1 Time: 0.331
[07/19/2022-13:00:26] [V] [TRT] Tactic: 2 Time: 1.12045
[07/19/2022-13:00:26] [V] [TRT] Tactic: 4 skipped. Scratch requested: 126531072, available: 16777216
[07/19/2022-13:00:26] [V] [TRT] Tactic: 5 Time: 1.2802
[07/19/2022-13:00:26] [V] [TRT] Fastest Tactic: 1 Time: 0.331
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CublasConvolution)
[07/19/2022-13:00:26] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CaskConvolution)
[07/19/2022-13:00:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:26] [V] [TRT] Tactic: 1062367460111450758 Time: 0.215316
[07/19/2022-13:00:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:26] [V] [TRT] Tactic: 1698681053543049347 Time: 0.21612
[07/19/2022-13:00:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:27] [V] [TRT] Tactic: 4501471010995462441 Time: 0.53102
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5137655947464784826 Time: 0.281156
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5288347012147084929 Time: 0.53862
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5326823351883942011 Time: 0.51666
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5500448035057547314 Time: 0.333176
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:27] [V] [TRT] Tactic: 6645123197870846056 Time: 0.286344
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:27] [V] [TRT] Tactic: 7144526460361122478 Time: 0.230168
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:27] [V] [TRT] Tactic: -8262349710178828730 Time: 0.542684
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:27] [V] [TRT] Tactic: -6576203419454146580 Time: 0.199156
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:27] [V] [TRT] Tactic: -4787320710726427159 Time: 0.23196
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:27] [V] [TRT] Tactic: -3456450830548107839 Time: 0.203824
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:27] [V] [TRT] Tactic: -1218658103698133241 Time: 0.349676
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:27] [V] [TRT] Tactic: -836875257600482091 Time: 0.343828
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:27] [V] [TRT] Tactic: -410470605513481746 Time: 0.523036
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:27] [V] [TRT] Tactic: -377491875521947884 Time: 0.530708
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:27] [V] [TRT] Tactic: -37215280111360163 Time: 0.278932
[07/19/2022-13:00:27] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.199156
[07/19/2022-13:00:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Float(451584,1,8064,144), Float(75264,1,1344,24) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CudnnConvolution)
[07/19/2022-13:00:27] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CublasConvolution)
[07/19/2022-13:00:27] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CaskConvolution)
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:27] [V] [TRT] Tactic: 3886731678879822788 Time: 0.34806
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:27] [V] [TRT] Tactic: 6629944304117643200 Time: 0.44236
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:27] [V] [TRT] Tactic: -9153228964338181824 Time: 0.446692
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:27] [V] [TRT] Tactic: -7394439838318485025 Time: 0.346516
[07/19/2022-13:00:27] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.346516
[07/19/2022-13:00:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Half(451584,3136,56,1), Half(75264,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CudnnConvolution)
[07/19/2022-13:00:27] [V] [TRT] Tactic: 0 Time: 0.387192
[07/19/2022-13:00:27] [V] [TRT] Tactic: 1 Time: 0.374324
[07/19/2022-13:00:27] [V] [TRT] Tactic: 2 Time: 1.07516
[07/19/2022-13:00:27] [V] [TRT] Tactic: 4 skipped. Scratch requested: 126531072, available: 16777216
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5 Time: 1.24607
[07/19/2022-13:00:27] [V] [TRT] Fastest Tactic: 1 Time: 0.374324
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CublasConvolution)
[07/19/2022-13:00:27] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CaskConvolution)
[07/19/2022-13:00:27] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Half(225792,3136:2,56,1), Half(37632,3136:2,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (FusedConvActConvolution)
[07/19/2022-13:00:27] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CudnnConvolution)
[07/19/2022-13:00:27] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CublasConvolution)
[07/19/2022-13:00:27] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add (CaskConvolution)
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:27] [V] [TRT] Tactic: 3066127711859985668 Time: 0.114196
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:27] [V] [TRT] Tactic: 3564772625446233998 Time: 0.123544
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:27] [V] [TRT] Tactic: 5319956359050645452 Time: 0.119716
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:27] [V] [TRT] Tactic: 7205456024582378848 Time: 0.155112
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:27] [V] [TRT] Tactic: 8163473458334948789 Time: 0.152172
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:27] [V] [TRT] Tactic: -4212163711445252890 Time: 0.280744
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:27] [V] [TRT] Tactic: -3898373634979201110 Time: 0.285824
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:27] [V] [TRT] Tactic: -2409163523992614473 Time: 0.153332
[07/19/2022-13:00:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:27] [V] [TRT] Tactic: -1716393687483585322 Time: 0.278776
[07/19/2022-13:00:27] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.114196
[07/19/2022-13:00:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,1344,24) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(75264,3136,56,1) -> Half(37632,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Float(75264,1,1344,24) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(37632,3136:2,56,1) -> Half(75264,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Float(75264,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Float(75264,1,1344,24) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Half(75264,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Half(37632,3136:2,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:27] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Half(37632,3136:2,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Float(451584,1,8064,144) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(451584,3136,56,1) -> Half(225792,3136:2,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Float(451584,1,8064,144) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning Reformat:Half(225792,3136:2,56,1) -> Half(451584,3136,56,1) ***************
[07/19/2022-13:00:27] [V] [TRT] *************** Autotuning format combination: Float(451584,3136,56,1) -> Float(112896,784,28,1) ***************
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:27] [V] [TRT] Tactic: -1 Time: 0.322372
[07/19/2022-13:00:27] [V] [TRT] Fastest Tactic: -1 Time: 0.322372
[07/19/2022-13:00:27] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:27] [V] [TRT] Tactic: 0 Time: 0.784128
[07/19/2022-13:00:27] [V] [TRT] Tactic: 1 Time: 0.779576
[07/19/2022-13:00:27] [V] [TRT] Tactic: 2 Time: 0.789988
[07/19/2022-13:00:29] [V] [TRT] Tactic: 5 Time: 92.9155
[07/19/2022-13:00:29] [V] [TRT] Fastest Tactic: 1 Time: 0.779576
[07/19/2022-13:00:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:29] [V] [TRT] Tactic: 1062367460111450758 Time: 3.17918
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:00:29] [V] [TRT] Tactic: 1754984623894446479 Time: 3.23236
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:00:29] [V] [TRT] Tactic: 3611739942397549984 Time: 7.00236
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:00:29] [V] [TRT] Tactic: 4337000649858996379 Time: 3.56217
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:29] [V] [TRT] Tactic: 4501471010995462441 Time: 6.61917
[07/19/2022-13:00:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:29] [V] [TRT] Tactic: 5137655947464784826 Time: 3.44214
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:30] [V] [TRT] Tactic: 5288347012147084929 Time: 6.92936
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:30] [V] [TRT] Tactic: 6645123197870846056 Time: 3.52682
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:30] [V] [TRT] Tactic: 7144526460361122478 Time: 3.02156
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:00:30] [V] [TRT] Tactic: -9137461792520977713 Time: 6.80804
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:30] [V] [TRT] Tactic: -8262349710178828730 Time: 7.0045
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:00:30] [V] [TRT] Tactic: -8133971918129952780 Time: 3.38723
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:00:30] [V] [TRT] Tactic: -6092040395344634144 Time: 3.30879
[07/19/2022-13:00:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:31] [V] [TRT] Tactic: -4787320710726427159 Time: 3.07808
[07/19/2022-13:00:31] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:31] [V] [TRT] Tactic: -3456450830548107839 Time: 3.09237
[07/19/2022-13:00:31] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:31] [V] [TRT] Tactic: -1218658103698133241 Time: 3.41246
[07/19/2022-13:00:31] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:31] [V] [TRT] Tactic: -836875257600482091 Time: 3.3449
[07/19/2022-13:00:31] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:31] [V] [TRT] Tactic: -410470605513481746 Time: 6.54573
[07/19/2022-13:00:31] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 3.02156
[07/19/2022-13:00:31] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:00:31] [V] [TRT] *************** Autotuning format combination: Float(451584,1,8064,144) -> Float(112896,1,4032,144) ***************
[07/19/2022-13:00:31] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:31] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:31] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:31] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:31] [V] [TRT] *************** Autotuning format combination: Half(451584,3136,56,1) -> Half(112896,784,28,1) ***************
[07/19/2022-13:00:31] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:31] [V] [TRT] Tactic: 0 Time: 0.615796
[07/19/2022-13:00:31] [V] [TRT] Tactic: 1 Time: 0.58508
[07/19/2022-13:00:31] [V] [TRT] Tactic: 2 Time: 0.69118
[07/19/2022-13:00:33] [V] [TRT] Tactic: 5 Time: 93.4877
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1 Time: 0.58508
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:33] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning format combination: Half(225792,3136:2,56,1) -> Half(56448,784:2,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:33] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,784,28,1) -> Float(112896,1,4032,144) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.125652
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.144968
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.125652
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,784,28,1) -> Half(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.128008
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.113392
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.113392
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,784,28,1) -> Half(56448,784:2,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.160896
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.068708
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.068708
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,4032,144) -> Float(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.176072
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.148724
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.148724
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,4032,144) -> Half(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.091588
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.147044
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.091588
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,4032,144) -> Half(56448,784:2,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.145396
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.161076
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.145396
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(112896,784,28,1) -> Float(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.129424
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.103392
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.103392
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(112896,784,28,1) -> Float(112896,1,4032,144) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.084752
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.13432
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.084752
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(112896,784,28,1) -> Half(56448,784:2,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.088012
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.067284
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.067284
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(56448,784:2,28,1) -> Float(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.15862
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.064212
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.064212
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(56448,784:2,28,1) -> Float(112896,1,4032,144) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.087096
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.13992
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.087096
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning Reformat:Half(56448,784:2,28,1) -> Half(112896,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1002 Time: 0.248628
[07/19/2022-13:00:33] [V] [TRT] Tactic: 0 Time: 0.059344
[07/19/2022-13:00:33] [V] [TRT] Fastest Tactic: 0 Time: 0.059344
[07/19/2022-13:00:33] [V] [TRT] *************** Autotuning format combination: Float(112896,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:00:33] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:33] [V] [TRT] Tactic: 589823 Time: 0.1675
[07/19/2022-13:00:33] [V] [TRT] Tactic: 655359 Time: 0.234252
[07/19/2022-13:00:33] [V] [TRT] Tactic: 786431 Time: 0.15002
[07/19/2022-13:00:33] [V] [TRT] Tactic: 851967 Time: 0.31358
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1179647 Time: 0.186104
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1310719 Time: 0.235072
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1376255 Time: 0.193072
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1441791 Time: 0.216404
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1507327 Time: 0.311668
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1638399 Time: 0.164804
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1835007 Time: 0.1534
[07/19/2022-13:00:33] [V] [TRT] Tactic: 1900543 Time: 0.3745
[07/19/2022-13:00:33] [V] [TRT] Tactic: 2162687 Time: 0.191904
[07/19/2022-13:00:33] [V] [TRT] Tactic: 2293759 Time: 0.19476
[07/19/2022-13:00:33] [V] [TRT] Tactic: 2359295 Time: 0.187212
[07/19/2022-13:00:33] [V] [TRT] Tactic: 2686975 Time: 0.188552
[07/19/2022-13:00:33] [V] [TRT] Tactic: 3080191 Time: 0.277768
[07/19/2022-13:00:33] [V] [TRT] Tactic: 3342335 Time: 0.320384
[07/19/2022-13:00:33] [V] [TRT] Tactic: 3407871 Time: 0.18332
[07/19/2022-13:00:33] [V] [TRT] Tactic: 3538943 Time: 0.171976
[07/19/2022-13:00:33] [V] [TRT] Tactic: 3670015 Time: 0.25426
[07/19/2022-13:00:34] [V] [TRT] Tactic: 3932159 Time: 0.323788
[07/19/2022-13:00:34] [V] [TRT] Tactic: 3997695 Time: 0.14438
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4063231 Time: 0.309692
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4194303 Time: 0.148836
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4325375 Time: 0.145464
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4521983 Time: 0.181608
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4587519 Time: 0.149472
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4653055 Time: 0.222084
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4915199 Time: 0.129704
[07/19/2022-13:00:34] [V] [TRT] Tactic: 4980735 Time: 0.147972
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5177343 Time: 0.17614
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5242879 Time: 0.174848
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5373951 Time: 0.229164
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5439487 Time: 0.195496
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5570559 Time: 0.225812
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5636095 Time: 0.310512
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5701631 Time: 0.240536
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5767167 Time: 0.272568
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5832703 Time: 0.176936
[07/19/2022-13:00:34] [V] [TRT] Tactic: 5898239 Time: 0.147152
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6029311 Time: 0.1836
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6225919 Time: 0.159532
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6291455 Time: 0.185636
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6422527 Time: 0.27642
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6750207 Time: 0.145552
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6815743 Time: 0.188348
[07/19/2022-13:00:34] [V] [TRT] Tactic: 6946815 Time: 0.203668
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7077887 Time: 0.164884
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7143423 Time: 0.18064
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7208959 Time: 0.176528
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7340031 Time: 0.155244
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7405567 Time: 0.188468
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7536639 Time: 0.175372
[07/19/2022-13:00:34] [V] [TRT] Tactic: 7602175 Time: 0.180492
[07/19/2022-13:00:35] [V] [TRT] Tactic: 7733247 Time: 0.171752
[07/19/2022-13:00:35] [V] [TRT] Tactic: 7798783 Time: 0.150228
[07/19/2022-13:00:35] [V] [TRT] Tactic: 8191999 Time: 0.175496
[07/19/2022-13:00:35] [V] [TRT] Tactic: 8257535 Time: 0.133416
[07/19/2022-13:00:35] [V] [TRT] Tactic: 8323071 Time: 0.14976
[07/19/2022-13:00:35] [V] [TRT] Tactic: 8650751 Time: 0.17436
[07/19/2022-13:00:35] [V] [TRT] Tactic: 8716287 Time: 0.203404
[07/19/2022-13:00:35] [V] [TRT] Tactic: 9568255 Time: 0.130148
[07/19/2022-13:00:35] [V] [TRT] Tactic: 9895935 Time: 0.14916
[07/19/2022-13:00:35] [V] [TRT] Tactic: 10223615 Time: 0.18856
[07/19/2022-13:00:35] [V] [TRT] Tactic: 10354687 Time: 0.14826
[07/19/2022-13:00:35] [V] [TRT] Tactic: 10551295 Time: 0.14828
[07/19/2022-13:00:35] [V] [TRT] Tactic: 10747903 Time: 0.172664
[07/19/2022-13:00:35] [V] [TRT] Tactic: 10944511 Time: 0.146144
[07/19/2022-13:00:35] [V] [TRT] Fastest Tactic: 4915199 Time: 0.129704
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:35] [V] [TRT] Tactic: 0 Time: 0.120824
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1 Time: 0.120924
[07/19/2022-13:00:35] [V] [TRT] Tactic: 2 Time: 0.320432
[07/19/2022-13:00:35] [V] [TRT] Tactic: 4 skipped. Scratch requested: 42633216, available: 16777216
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5 Time: 0.457328
[07/19/2022-13:00:35] [V] [TRT] Fastest Tactic: 0 Time: 0.120824
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1062367460111450758 Time: 0.074132
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1698681053543049347 Time: 0.077216
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:35] [V] [TRT] Tactic: 4501471010995462441 Time: 0.148668
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5137655947464784826 Time: 0.081832
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5288347012147084929 Time: 0.149624
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5326823351883942011 Time: 0.144576
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5500448035057547314 Time: 0.095716
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:35] [V] [TRT] Tactic: 6645123197870846056 Time: 0.08354
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:35] [V] [TRT] Tactic: 7144526460361122478 Time: 0.079944
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:35] [V] [TRT] Tactic: -8262349710178828730 Time: 0.151336
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:35] [V] [TRT] Tactic: -6576203419454146580 Time: 0.068568
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:35] [V] [TRT] Tactic: -4787320710726427159 Time: 0.08106
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:35] [V] [TRT] Tactic: -3456450830548107839 Time: 0.07014
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:35] [V] [TRT] Tactic: -1218658103698133241 Time: 0.099972
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:35] [V] [TRT] Tactic: -836875257600482091 Time: 0.097616
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:35] [V] [TRT] Tactic: -410470605513481746 Time: 0.14658
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:35] [V] [TRT] Tactic: -377491875521947884 Time: 0.149204
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:35] [V] [TRT] Tactic: -37215280111360163 Time: 0.080024
[07/19/2022-13:00:35] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.068568
[07/19/2022-13:00:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:00:35] [V] [TRT] *************** Autotuning format combination: Float(112896,1,4032,144) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:35] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:35] [V] [TRT] Tactic: 3886731678879822788 Time: 0.087836
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:35] [V] [TRT] Tactic: 6629944304117643200 Time: 0.097232
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:35] [V] [TRT] Tactic: -9153228964338181824 Time: 0.100164
[07/19/2022-13:00:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:35] [V] [TRT] Tactic: -7394439838318485025 Time: 0.088868
[07/19/2022-13:00:35] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.087836
[07/19/2022-13:00:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:35] [V] [TRT] *************** Autotuning format combination: Half(112896,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:35] [V] [TRT] Tactic: 0 Time: 0.11098
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1 Time: 0.106556
[07/19/2022-13:00:35] [V] [TRT] Tactic: 2 Time: 0.314984
[07/19/2022-13:00:35] [V] [TRT] Tactic: 4 skipped. Scratch requested: 42633216, available: 16777216
[07/19/2022-13:00:35] [V] [TRT] Tactic: 5 Time: 0.440672
[07/19/2022-13:00:35] [V] [TRT] Fastest Tactic: 1 Time: 0.106556
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:35] [V] [TRT] *************** Autotuning format combination: Half(56448,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:35] [V] [TRT] *************** Autotuning format combination: Half(56448,784:2,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:35] [V] [TRT] Tactic: 589823 Time: 0.074724
[07/19/2022-13:00:35] [V] [TRT] Tactic: 655359 Time: 0.1799
[07/19/2022-13:00:35] [V] [TRT] Tactic: 786431 Time: 0.09632
[07/19/2022-13:00:35] [V] [TRT] Tactic: 851967 Time: 0.19052
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1310719 Time: 0.135804
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1376255 Time: 0.08508
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1507327 Time: 0.17746
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1638399 Time: 0.08102
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1835007 Time: 0.087576
[07/19/2022-13:00:35] [V] [TRT] Tactic: 1900543 Time: 0.18896
[07/19/2022-13:00:35] [V] [TRT] Tactic: 2162687 Time: 0.11324
[07/19/2022-13:00:35] [V] [TRT] Tactic: 2293759 Time: 0.114488
[07/19/2022-13:00:36] [V] [TRT] Tactic: 2359295 Time: 0.093132
[07/19/2022-13:00:36] [V] [TRT] Tactic: 2686975 Time: 0.144436
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3080191 Time: 0.16522
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3342335 Time: 0.179456
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3407871 Time: 0.10412
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3538943 Time: 0.097324
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3670015 Time: 0.18306
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3932159 Time: 0.136644
[07/19/2022-13:00:36] [V] [TRT] Tactic: 4063231 Time: 0.19238
[07/19/2022-13:00:36] [V] [TRT] Tactic: 4194303 Time: 0.07354
[07/19/2022-13:00:36] [V] [TRT] Tactic: 4325375 Time: 0.073668
[07/19/2022-13:00:36] [V] [TRT] Tactic: 4521983 Time: 0.078524
[07/19/2022-13:00:36] [V] [TRT] Tactic: 4980735 Time: 0.083124
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5242879 Time: 0.083676
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5439487 Time: 0.08858
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5570559 Time: 0.166
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5636095 Time: 0.192128
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5701631 Time: 0.098372
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5767167 Time: 0.12182
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5832703 Time: 0.098976
[07/19/2022-13:00:36] [V] [TRT] Tactic: 6029311 Time: 0.102372
[07/19/2022-13:00:36] [V] [TRT] Tactic: 6225919 Time: 0.083764
[07/19/2022-13:00:36] [V] [TRT] Tactic: 6422527 Time: 0.149828
[07/19/2022-13:00:36] [V] [TRT] Tactic: 6815743 Time: 0.087104
[07/19/2022-13:00:36] [V] [TRT] Tactic: 6946815 Time: 0.094392
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7077887 Time: 0.090896
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7143423 Time: 0.085704
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7208959 Time: 0.093036
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7405567 Time: 0.101332
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7536639 Time: 0.113996
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7602175 Time: 0.084288
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7733247 Time: 0.091892
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7798783 Time: 0.096376
[07/19/2022-13:00:36] [V] [TRT] Tactic: 8191999 Time: 0.084692
[07/19/2022-13:00:36] [V] [TRT] Tactic: 8323071 Time: 0.069856
[07/19/2022-13:00:36] [V] [TRT] Tactic: 8650751 Time: 0.080216
[07/19/2022-13:00:36] [V] [TRT] Tactic: 8716287 Time: 0.093176
[07/19/2022-13:00:36] [V] [TRT] Tactic: 9895935 Time: 0.072644
[07/19/2022-13:00:36] [V] [TRT] Tactic: 10223615 Time: 0.144648
[07/19/2022-13:00:36] [V] [TRT] Tactic: 10551295 Time: 0.061076
[07/19/2022-13:00:36] [V] [TRT] Tactic: 10747903 Time: 0.091384
[07/19/2022-13:00:36] [V] [TRT] Tactic: 10944511 Time: 0.082896
[07/19/2022-13:00:36] [V] [TRT] Fastest Tactic: 10551295 Time: 0.061076
[07/19/2022-13:00:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:36] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:36] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3066127711859985668 Time: 0.0384
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:36] [V] [TRT] Tactic: 3564772625446233998 Time: 0.041724
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:36] [V] [TRT] Tactic: 5319956359050645452 Time: 0.039392
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:36] [V] [TRT] Tactic: 7205456024582378848 Time: 0.047444
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:36] [V] [TRT] Tactic: 8163473458334948789 Time: 0.04488
[07/19/2022-13:00:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:37] [V] [TRT] Tactic: -4212163711445252890 Time: 0.078584
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:37] [V] [TRT] Tactic: -3898373634979201110 Time: 0.079832
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:37] [V] [TRT] Tactic: -2409163523992614473 Time: 0.04668
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:37] [V] [TRT] Tactic: -1716393687483585322 Time: 0.077644
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.0384
[07/19/2022-13:00:37] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.042952
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.028924
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.028924
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.031176
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.024052
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.024052
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.032884
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.017488
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.017488
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.044812
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.027004
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.027004
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.020836
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.027636
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.020836
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.029424
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.031736
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.029424
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.031504
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.019864
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.019864
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.019348
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.029364
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.019348
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.022848
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.01712
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.01712
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.027484
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.014664
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.014664
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.019576
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.033192
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.019576
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.051608
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.014356
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.014356
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.04298
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.028784
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.028784
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.031196
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.024104
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.024104
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.033056
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.01748
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.01748
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.04514
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.026896
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.026896
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.020932
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.027668
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.020932
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.029472
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.03178
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.029472
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.031184
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.02016
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.02016
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.019368
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.029236
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.019368
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.022968
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.0171
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.0171
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.027724
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.01446
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.01446
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.01944
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.033216
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1002 Time: 0.01944
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1002 Time: 0.052016
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.014368
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.014368
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning format combination: Float(25088,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:37] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:37] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.452428
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1 Time: 0.34084
[07/19/2022-13:00:37] [V] [TRT] Tactic: 2 Time: 0.524772
[07/19/2022-13:00:37] [V] [TRT] Tactic: 4 skipped. Scratch requested: 54059008, available: 16777216
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5 Time: 0.666804
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 1 Time: 0.34084
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:37] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1062367460111450758 Time: 0.109736
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1698681053543049347 Time: 0.101152
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:37] [V] [TRT] Tactic: 4501471010995462441 Time: 0.118332
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5137655947464784826 Time: 0.089976
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5288347012147084929 Time: 0.119296
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5326823351883942011 Time: 0.114428
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5500448035057547314 Time: 0.096752
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:37] [V] [TRT] Tactic: 6645123197870846056 Time: 0.090684
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:37] [V] [TRT] Tactic: 7144526460361122478 Time: 0.111444
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:37] [V] [TRT] Tactic: -8262349710178828730 Time: 0.120728
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:37] [V] [TRT] Tactic: -6576203419454146580 Time: 0.103772
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:37] [V] [TRT] Tactic: -4787320710726427159 Time: 0.112512
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:37] [V] [TRT] Tactic: -3456450830548107839 Time: 0.106048
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:37] [V] [TRT] Tactic: -1218658103698133241 Time: 0.09958
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:37] [V] [TRT] Tactic: -836875257600482091 Time: 0.098448
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:37] [V] [TRT] Tactic: -410470605513481746 Time: 0.11614
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:37] [V] [TRT] Tactic: -377491875521947884 Time: 0.117356
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:37] [V] [TRT] Tactic: -37215280111360163 Time: 0.090472
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 5137655947464784826 Time: 0.089976
[07/19/2022-13:00:37] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5137655947464784826
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning format combination: Float(25088,1,896,32) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:37] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:37] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:37] [V] [TRT] Tactic: 3886731678879822788 Time: 0.107132
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:37] [V] [TRT] Tactic: 6629944304117643200 Time: 0.277796
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:37] [V] [TRT] Tactic: -9153228964338181824 Time: 0.280368
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:37] [V] [TRT] Tactic: -7394439838318485025 Time: 0.10842
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.107132
[07/19/2022-13:00:37] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning format combination: Half(25088,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:37] [V] [TRT] Tactic: 0 Time: 0.34634
[07/19/2022-13:00:37] [V] [TRT] Tactic: 1 Time: 0.346892
[07/19/2022-13:00:37] [V] [TRT] Tactic: 2 Time: 0.420292
[07/19/2022-13:00:37] [V] [TRT] Tactic: 4 skipped. Scratch requested: 54059008, available: 16777216
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5 Time: 0.62282
[07/19/2022-13:00:37] [V] [TRT] Fastest Tactic: 0 Time: 0.34634
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:37] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:37] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:37] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:37] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:37] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:37] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:37] [V] [TRT] Tactic: 3066127711859985668 Time: 0.06234
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:37] [V] [TRT] Tactic: 3564772625446233998 Time: 0.065068
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:37] [V] [TRT] Tactic: 5319956359050645452 Time: 0.062964
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:37] [V] [TRT] Tactic: 7205456024582378848 Time: 0.05212
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:37] [V] [TRT] Tactic: 8163473458334948789 Time: 0.051216
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:37] [V] [TRT] Tactic: -4212163711445252890 Time: 0.06706
[07/19/2022-13:00:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:38] [V] [TRT] Tactic: -3898373634979201110 Time: 0.067904
[07/19/2022-13:00:38] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:38] [V] [TRT] Tactic: -2409163523992614473 Time: 0.051032
[07/19/2022-13:00:38] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:38] [V] [TRT] Tactic: -1716393687483585322 Time: 0.067012
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: -2409163523992614473 Time: 0.051032
[07/19/2022-13:00:38] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -2409163523992614473
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.130608
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.206572
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 1002 Time: 0.130608
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.16892
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.145592
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.145592
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.220144
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.089956
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.089956
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.207652
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.202736
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.202736
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.105224
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.1972
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 1002 Time: 0.105224
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.2057
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.21558
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 1002 Time: 0.2057
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.170356
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.149504
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.149504
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.098836
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.18196
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 1002 Time: 0.098836
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.11824
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.088312
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.088312
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.213652
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.084056
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.084056
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.10768
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.184252
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 1002 Time: 0.10768
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1002 Time: 0.291352
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.077792
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: 0 Time: 0.077792
[07/19/2022-13:00:38] [V] [TRT] *************** Autotuning format combination: Float(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:38] [V] [TRT] Tactic: -1 Time: 0.159892
[07/19/2022-13:00:38] [V] [TRT] Fastest Tactic: -1 Time: 0.159892
[07/19/2022-13:00:38] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:38] [V] [TRT] Tactic: 0 Time: 0.409084
[07/19/2022-13:00:38] [V] [TRT] Tactic: 1 Time: 0.410308
[07/19/2022-13:00:38] [V] [TRT] Tactic: 2 Time: 0.493556
[07/19/2022-13:00:38] [V] [TRT] Tactic: 4 Time: 30.0568
[07/19/2022-13:00:39] [V] [TRT] Tactic: 5 Time: 42.8265
[07/19/2022-13:00:39] [V] [TRT] Tactic: 6 Time: 16.2932
[07/19/2022-13:00:39] [V] [TRT] Fastest Tactic: 0 Time: 0.409084
[07/19/2022-13:00:39] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:39] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:40] [V] [TRT] Tactic: 1062367460111450758 Time: 4.2835
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:00:40] [V] [TRT] Tactic: 1754984623894446479 Time: 4.49412
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:00:40] [V] [TRT] Tactic: 3611739942397549984 Time: 9.28488
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-13:00:40] [V] [TRT] Tactic: 3827454225649558724 Time: 8.54474
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:00:40] [V] [TRT] Tactic: 4337000649858996379 Time: 4.71205
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:40] [V] [TRT] Tactic: 4501471010995462441 Time: 8.78064
[07/19/2022-13:00:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:41] [V] [TRT] Tactic: 5137655947464784826 Time: 4.49683
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:41] [V] [TRT] Tactic: 5288347012147084929 Time: 9.10492
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-13:00:41] [V] [TRT] Tactic: 5921334924264294896 Time: 5.81152
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:41] [V] [TRT] Tactic: 6645123197870846056 Time: 4.66026
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:41] [V] [TRT] Tactic: 7144526460361122478 Time: 4.1167
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-13:00:41] [V] [TRT] Tactic: 7852627285308570038 Time: 9.05411
[07/19/2022-13:00:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:00:42] [V] [TRT] Tactic: -9137461792520977713 Time: 8.87079
[07/19/2022-13:00:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-13:00:42] [V] [TRT] Tactic: -8776506421218919509 Time: 8.92531
[07/19/2022-13:00:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:42] [V] [TRT] Tactic: -8262349710178828730 Time: 9.30395
[07/19/2022-13:00:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:00:42] [V] [TRT] Tactic: -8133971918129952780 Time: 4.46134
[07/19/2022-13:00:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:00:42] [V] [TRT] Tactic: -6092040395344634144 Time: 4.43881
[07/19/2022-13:00:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:42] [V] [TRT] Tactic: -4787320710726427159 Time: 4.13033
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:43] [V] [TRT] Tactic: -3456450830548107839 Time: 4.17122
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-13:00:43] [V] [TRT] Tactic: -2318106587342035239 Time: 8.572
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-13:00:43] [V] [TRT] Tactic: -1343271414618805657 Time: 5.70129
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:43] [V] [TRT] Tactic: -1218658103698133241 Time: 4.48775
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:43] [V] [TRT] Tactic: -836875257600482091 Time: 4.35894
[07/19/2022-13:00:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:43] [V] [TRT] Tactic: -410470605513481746 Time: 8.64346
[07/19/2022-13:00:43] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 4.1167
[07/19/2022-13:00:43] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:00:43] [V] [TRT] *************** Autotuning format combination: Float(150528,1,5376,192) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:43] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:43] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:43] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:43] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:43] [V] [TRT] *************** Autotuning format combination: Half(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:43] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:43] [V] [TRT] Tactic: 0 Time: 0.313808
[07/19/2022-13:00:43] [V] [TRT] Tactic: 1 Time: 0.311808
[07/19/2022-13:00:44] [V] [TRT] Tactic: 2 Time: 7.05972
[07/19/2022-13:00:44] [V] [TRT] Tactic: 4 Time: 29.9331
[07/19/2022-13:00:45] [V] [TRT] Tactic: 5 Time: 43.6263
[07/19/2022-13:00:45] [V] [TRT] Tactic: 6 Time: 34.682
[07/19/2022-13:00:45] [V] [TRT] Fastest Tactic: 1 Time: 0.311808
[07/19/2022-13:00:45] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:45] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:45] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning format combination: Half(75264,784:2,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:45] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] *************** Autotuning format combination: Float(150528,784,28,1), Float(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:45] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CudaDepthwiseConvolution)
[07/19/2022-13:00:45] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:45] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (FusedConvActConvolution)
[07/19/2022-13:00:45] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:45] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CudnnConvolution)
[07/19/2022-13:00:45] [V] [TRT] Tactic: 0 Time: 0.161824
[07/19/2022-13:00:45] [V] [TRT] Tactic: 1 Time: 0.15912
[07/19/2022-13:00:45] [V] [TRT] Tactic: 2 Time: 0.426624
[07/19/2022-13:00:45] [V] [TRT] Tactic: 4 skipped. Scratch requested: 56844288, available: 16777216
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5 Time: 0.594404
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: 1 Time: 0.15912
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CublasConvolution)
[07/19/2022-13:00:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:46] [V] [TRT] Tactic: 1062367460111450758 Time: 0.096468
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:46] [V] [TRT] Tactic: 1698681053543049347 Time: 0.101184
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:46] [V] [TRT] Tactic: 4501471010995462441 Time: 0.193892
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5137655947464784826 Time: 0.105108
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5288347012147084929 Time: 0.193748
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5326823351883942011 Time: 0.187904
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5500448035057547314 Time: 0.125628
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:46] [V] [TRT] Tactic: 6645123197870846056 Time: 0.106668
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:46] [V] [TRT] Tactic: 7144526460361122478 Time: 0.105424
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:46] [V] [TRT] Tactic: -8262349710178828730 Time: 0.194208
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:46] [V] [TRT] Tactic: -6576203419454146580 Time: 0.08858
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:46] [V] [TRT] Tactic: -4787320710726427159 Time: 0.106408
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:46] [V] [TRT] Tactic: -3456450830548107839 Time: 0.089968
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:46] [V] [TRT] Tactic: -1218658103698133241 Time: 0.12854
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:46] [V] [TRT] Tactic: -836875257600482091 Time: 0.12902
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:46] [V] [TRT] Tactic: -410470605513481746 Time: 0.190664
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:46] [V] [TRT] Tactic: -377491875521947884 Time: 0.1936
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:46] [V] [TRT] Tactic: -37215280111360163 Time: 0.102552
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.08858
[07/19/2022-13:00:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,1,5376,192), Float(25088,1,896,32) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CudnnConvolution)
[07/19/2022-13:00:46] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CublasConvolution)
[07/19/2022-13:00:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:46] [V] [TRT] Tactic: 3886731678879822788 Time: 0.12012
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:46] [V] [TRT] Tactic: 6629944304117643200 Time: 0.13394
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:46] [V] [TRT] Tactic: -9153228964338181824 Time: 0.135744
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:46] [V] [TRT] Tactic: -7394439838318485025 Time: 0.12054
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.12012
[07/19/2022-13:00:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(150528,784,28,1), Half(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CudnnConvolution)
[07/19/2022-13:00:46] [V] [TRT] Tactic: 0 Time: 0.15036
[07/19/2022-13:00:46] [V] [TRT] Tactic: 1 Time: 0.147716
[07/19/2022-13:00:46] [V] [TRT] Tactic: 2 Time: 0.417216
[07/19/2022-13:00:46] [V] [TRT] Tactic: 4 skipped. Scratch requested: 56844288, available: 16777216
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5 Time: 0.586192
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: 1 Time: 0.147716
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CublasConvolution)
[07/19/2022-13:00:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(75264,784:2,28,1), Half(12544,784:2,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (FusedConvActConvolution)
[07/19/2022-13:00:46] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CudnnConvolution)
[07/19/2022-13:00:46] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CublasConvolution)
[07/19/2022-13:00:46] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:46] [V] [TRT] Tactic: 3066127711859985668 Time: 0.050216
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:46] [V] [TRT] Tactic: 3564772625446233998 Time: 0.054432
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:46] [V] [TRT] Tactic: 5319956359050645452 Time: 0.05204
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:46] [V] [TRT] Tactic: 7205456024582378848 Time: 0.0603
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:46] [V] [TRT] Tactic: 8163473458334948789 Time: 0.057544
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:46] [V] [TRT] Tactic: -4212163711445252890 Time: 0.100328
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:46] [V] [TRT] Tactic: -3898373634979201110 Time: 0.102192
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:46] [V] [TRT] Tactic: -2409163523992614473 Time: 0.058244
[07/19/2022-13:00:46] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:46] [V] [TRT] Tactic: -1716393687483585322 Time: 0.099344
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.050216
[07/19/2022-13:00:46] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(25088,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(25088,1,896,32) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(25088,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,1,5376,192) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:46] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(75264,784:2,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,784,28,1), Float(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,1,5376,192), Float(25088,1,896,32) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(150528,784,28,1), Half(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(75264,784:2,28,1), Half(12544,784:2,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(25088,1,896,32) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(25088,784,28,1) -> Half(12544,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Float(25088,1,896,32) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(12544,784:2,28,1) -> Half(25088,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(25088,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(25088,1,896,32) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(25088,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:46] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Half(12544,784:2,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Float(150528,1,5376,192) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(150528,784,28,1) -> Half(75264,784:2,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Float(150528,1,5376,192) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning Reformat:Half(75264,784:2,28,1) -> Half(150528,784,28,1) ***************
[07/19/2022-13:00:46] [V] [TRT] *************** Autotuning format combination: Float(150528,784,28,1) -> Float(37632,196,14,1) ***************
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:46] [V] [TRT] Tactic: -1 Time: 0.115412
[07/19/2022-13:00:46] [V] [TRT] Fastest Tactic: -1 Time: 0.115412
[07/19/2022-13:00:46] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:46] [V] [TRT] Tactic: 0 Time: 0.28818
[07/19/2022-13:00:46] [V] [TRT] Tactic: 1 Time: 0.289192
[07/19/2022-13:00:46] [V] [TRT] Tactic: 2 Time: 0.287808
[07/19/2022-13:00:47] [V] [TRT] Tactic: 5 Time: 34.6106
[07/19/2022-13:00:47] [V] [TRT] Fastest Tactic: 2 Time: 0.287808
[07/19/2022-13:00:47] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:47] [V] [TRT] Tactic: 1062367460111450758 Time: 4.1631
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:00:47] [V] [TRT] Tactic: 1754984623894446479 Time: 4.49492
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:00:47] [V] [TRT] Tactic: 3611739942397549984 Time: 4.4828
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:00:47] [V] [TRT] Tactic: 4337000649858996379 Time: 4.42738
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:47] [V] [TRT] Tactic: 4501471010995462441 Time: 4.18308
[07/19/2022-13:00:47] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:47] [V] [TRT] Tactic: 5137655947464784826 Time: 4.15694
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:48] [V] [TRT] Tactic: 5288347012147084929 Time: 4.13191
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:48] [V] [TRT] Tactic: 6645123197870846056 Time: 4.18518
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:48] [V] [TRT] Tactic: 7144526460361122478 Time: 3.91084
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:00:48] [V] [TRT] Tactic: -9137461792520977713 Time: 4.45593
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:48] [V] [TRT] Tactic: -8262349710178828730 Time: 4.2023
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:00:48] [V] [TRT] Tactic: -8133971918129952780 Time: 4.42556
[07/19/2022-13:00:48] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:00:48] [V] [TRT] Tactic: -6092040395344634144 Time: 4.40876
[07/19/2022-13:00:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:49] [V] [TRT] Tactic: -4787320710726427159 Time: 4.20818
[07/19/2022-13:00:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:49] [V] [TRT] Tactic: -3456450830548107839 Time: 4.1402
[07/19/2022-13:00:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:49] [V] [TRT] Tactic: -1218658103698133241 Time: 3.93413
[07/19/2022-13:00:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:49] [V] [TRT] Tactic: -836875257600482091 Time: 4.09446
[07/19/2022-13:00:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:49] [V] [TRT] Tactic: -410470605513481746 Time: 4.06857
[07/19/2022-13:00:49] [V] [TRT] Fastest Tactic: 7144526460361122478 Time: 3.91084
[07/19/2022-13:00:49] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:00:49] [V] [TRT] *************** Autotuning format combination: Float(150528,1,5376,192) -> Float(37632,1,2688,192) ***************
[07/19/2022-13:00:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:49] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:49] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:49] [V] [TRT] *************** Autotuning format combination: Half(150528,784,28,1) -> Half(37632,196,14,1) ***************
[07/19/2022-13:00:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:49] [V] [TRT] Tactic: 0 Time: 0.238308
[07/19/2022-13:00:49] [V] [TRT] Tactic: 1 Time: 0.239588
[07/19/2022-13:00:49] [V] [TRT] Tactic: 2 Time: 0.257528
[07/19/2022-13:00:50] [V] [TRT] Tactic: 5 Time: 35.525
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.238308
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:50] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:50] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning format combination: Half(75264,784:2,28,1) -> Half(18816,196:2,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:50] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,196,14,1) -> Float(37632,1,2688,192) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.041692
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.058276
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.041692
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,196,14,1) -> Half(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.718288
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.034676
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.034676
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,196,14,1) -> Half(18816,196:2,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.047504
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.024372
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.024372
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,1,2688,192) -> Float(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.0594
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.045876
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.045876
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,1,2688,192) -> Half(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.03366
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.0396
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.03366
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Float(37632,1,2688,192) -> Half(18816,196:2,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.04052
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.046408
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.04052
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(37632,196,14,1) -> Float(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.723144
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.02832
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.02832
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(37632,196,14,1) -> Float(37632,1,2688,192) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.03008
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.042348
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.03008
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(37632,196,14,1) -> Half(18816,196:2,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.035756
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.024212
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.024212
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(18816,196:2,14,1) -> Float(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.045036
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.021144
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.021144
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(18816,196:2,14,1) -> Float(37632,1,2688,192) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.02984
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.048444
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 1002 Time: 0.02984
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning Reformat:Half(18816,196:2,14,1) -> Half(37632,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1002 Time: 0.0624
[07/19/2022-13:00:50] [V] [TRT] Tactic: 0 Time: 0.021064
[07/19/2022-13:00:50] [V] [TRT] Fastest Tactic: 0 Time: 0.021064
[07/19/2022-13:00:50] [V] [TRT] *************** Autotuning format combination: Float(37632,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:00:50] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:50] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:50] [V] [TRT] Tactic: 589823 Time: 0.077856
[07/19/2022-13:00:50] [V] [TRT] Tactic: 655359 Time: 0.08536
[07/19/2022-13:00:50] [V] [TRT] Tactic: 786431 Time: 0.070368
[07/19/2022-13:00:50] [V] [TRT] Tactic: 851967 Time: 0.09048
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1179647 Time: 0.061924
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1310719 Time: 0.160688
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1376255 Time: 0.089592
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1441791 Time: 0.08128
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1507327 Time: 0.100084
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1638399 Time: 0.087676
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1835007 Time: 0.07368
[07/19/2022-13:00:50] [V] [TRT] Tactic: 1900543 Time: 0.112168
[07/19/2022-13:00:50] [V] [TRT] Tactic: 2097151 Time: 0.075648
[07/19/2022-13:00:50] [V] [TRT] Tactic: 2162687 Time: 0.09404
[07/19/2022-13:00:50] [V] [TRT] Tactic: 2293759 Time: 0.08978
[07/19/2022-13:00:50] [V] [TRT] Tactic: 2359295 Time: 0.084444
[07/19/2022-13:00:50] [V] [TRT] Tactic: 2686975 Time: 0.089108
[07/19/2022-13:00:50] [V] [TRT] Tactic: 3080191 Time: 0.070732
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3342335 Time: 0.099272
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3407871 Time: 0.0736
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3538943 Time: 0.0623
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3670015 Time: 0.114216
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3932159 Time: 0.116684
[07/19/2022-13:00:51] [V] [TRT] Tactic: 3997695 Time: 0.06912
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4063231 Time: 0.083168
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4194303 Time: 0.068712
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4259839 Time: 0.080492
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4325375 Time: 0.093776
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4521983 Time: 0.09204
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4587519 Time: 0.078588
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4653055 Time: 0.06774
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4915199 Time: 0.070364
[07/19/2022-13:00:51] [V] [TRT] Tactic: 4980735 Time: 0.085316
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5177343 Time: 0.066872
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5242879 Time: 0.064556
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5373951 Time: 0.067168
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5439487 Time: 0.06634
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5570559 Time: 0.070144
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5636095 Time: 0.0831
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5701631 Time: 0.088448
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5767167 Time: 0.081892
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5832703 Time: 0.069672
[07/19/2022-13:00:51] [V] [TRT] Tactic: 5898239 Time: 0.055584
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6029311 Time: 0.08236
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6225919 Time: 0.0539
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6291455 Time: 0.06186
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6422527 Time: 0.08256
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6750207 Time: 0.066856
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6815743 Time: 0.065188
[07/19/2022-13:00:51] [V] [TRT] Tactic: 6946815 Time: 0.098288
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7012351 Time: 0.075528
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7077887 Time: 0.059584
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7143423 Time: 0.088244
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7208959 Time: 0.071344
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7340031 Time: 0.057788
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7405567 Time: 0.0621
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7536639 Time: 0.067852
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7602175 Time: 0.09612
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7733247 Time: 0.056688
[07/19/2022-13:00:51] [V] [TRT] Tactic: 7798783 Time: 0.07008
[07/19/2022-13:00:51] [V] [TRT] Tactic: 8191999 Time: 0.098916
[07/19/2022-13:00:51] [V] [TRT] Tactic: 8257535 Time: 0.071592
[07/19/2022-13:00:51] [V] [TRT] Tactic: 8323071 Time: 0.064956
[07/19/2022-13:00:51] [V] [TRT] Tactic: 8650751 Time: 0.097408
[07/19/2022-13:00:51] [V] [TRT] Tactic: 8716287 Time: 0.058296
[07/19/2022-13:00:51] [V] [TRT] Tactic: 9109503 Time: 0.075864
[07/19/2022-13:00:51] [V] [TRT] Tactic: 9568255 Time: 0.06988
[07/19/2022-13:00:51] [V] [TRT] Tactic: 9895935 Time: 0.068596
[07/19/2022-13:00:51] [V] [TRT] Tactic: 10223615 Time: 0.089244
[07/19/2022-13:00:51] [V] [TRT] Tactic: 10354687 Time: 0.079688
[07/19/2022-13:00:51] [V] [TRT] Tactic: 10551295 Time: 0.070932
[07/19/2022-13:00:51] [V] [TRT] Tactic: 10747903 Time: 0.055196
[07/19/2022-13:00:51] [V] [TRT] Tactic: 10944511 Time: 0.085104
[07/19/2022-13:00:51] [V] [TRT] Fastest Tactic: 6225919 Time: 0.0539
[07/19/2022-13:00:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:51] [V] [TRT] Tactic: 0 Time: 0.073424
[07/19/2022-13:00:51] [V] [TRT] Tactic: 1 Time: 0.06672
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2 Time: 0.234104
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4 skipped. Scratch requested: 29245440, available: 16777216
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5 Time: 0.554268
[07/19/2022-13:00:52] [V] [TRT] Fastest Tactic: 1 Time: 0.06672
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:52] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1062367460111450758 Time: 0.039304
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1698681053543049347 Time: 0.035584
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4501471010995462441 Time: 0.05508
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5137655947464784826 Time: 0.032888
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5288347012147084929 Time: 0.05508
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5326823351883942011 Time: 0.053724
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5500448035057547314 Time: 0.03832
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:52] [V] [TRT] Tactic: 6645123197870846056 Time: 0.03442
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:52] [V] [TRT] Tactic: 7144526460361122478 Time: 0.0371
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:52] [V] [TRT] Tactic: -8262349710178828730 Time: 0.055256
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:52] [V] [TRT] Tactic: -6576203419454146580 Time: 0.03452
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:52] [V] [TRT] Tactic: -4787320710726427159 Time: 0.039256
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:52] [V] [TRT] Tactic: -3456450830548107839 Time: 0.036256
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:52] [V] [TRT] Tactic: -1218658103698133241 Time: 0.039564
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:52] [V] [TRT] Tactic: -836875257600482091 Time: 0.039332
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:52] [V] [TRT] Tactic: -410470605513481746 Time: 0.053896
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:52] [V] [TRT] Tactic: -377491875521947884 Time: 0.054596
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:52] [V] [TRT] Tactic: -37215280111360163 Time: 0.0329
[07/19/2022-13:00:52] [V] [TRT] Fastest Tactic: 5137655947464784826 Time: 0.032888
[07/19/2022-13:00:52] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5137655947464784826
[07/19/2022-13:00:52] [V] [TRT] *************** Autotuning format combination: Float(37632,1,2688,192) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:52] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:52] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3886731678879822788 Time: 0.030108
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:52] [V] [TRT] Tactic: 6629944304117643200 Time: 0.047904
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:52] [V] [TRT] Tactic: -9153228964338181824 Time: 0.048696
[07/19/2022-13:00:52] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:52] [V] [TRT] Tactic: -7394439838318485025 Time: 0.030356
[07/19/2022-13:00:52] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.030108
[07/19/2022-13:00:52] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:52] [V] [TRT] *************** Autotuning format combination: Half(37632,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:52] [V] [TRT] Tactic: 0 Time: 0.073656
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1 Time: 0.073848
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2 Time: 0.163712
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4 skipped. Scratch requested: 29245440, available: 16777216
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5 Time: 0.486604
[07/19/2022-13:00:52] [V] [TRT] Fastest Tactic: 0 Time: 0.073656
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:52] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:52] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:00:52] [V] [TRT] *************** Autotuning format combination: Half(18816,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:52] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:52] [V] [TRT] *************** Autotuning format combination: Half(18816,196:2,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:52] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:00:52] [V] [TRT] Tactic: 589823 Time: 0.045092
[07/19/2022-13:00:52] [V] [TRT] Tactic: 655359 Time: 0.062496
[07/19/2022-13:00:52] [V] [TRT] Tactic: 786431 Time: 0.061376
[07/19/2022-13:00:52] [V] [TRT] Tactic: 851967 Time: 0.060344
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1179647 Time: 0.035092
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1310719 Time: 0.104268
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1376255 Time: 0.04976
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1441791 Time: 0.044152
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1507327 Time: 0.061932
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1638399 Time: 0.051288
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1835007 Time: 0.058188
[07/19/2022-13:00:52] [V] [TRT] Tactic: 1900543 Time: 0.065716
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2097151 Time: 0.050548
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2162687 Time: 0.05026
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2293759 Time: 0.048584
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2359295 Time: 0.048464
[07/19/2022-13:00:52] [V] [TRT] Tactic: 2686975 Time: 0.078036
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3080191 Time: 0.052676
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3342335 Time: 0.061244
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3407871 Time: 0.04174
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3538943 Time: 0.035644
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3670015 Time: 0.08386
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3932159 Time: 0.054804
[07/19/2022-13:00:52] [V] [TRT] Tactic: 3997695 Time: 0.0519
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4063231 Time: 0.05436
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4194303 Time: 0.041776
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4259839 Time: 0.05168
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4325375 Time: 0.050676
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4521983 Time: 0.053304
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4587519 Time: 0.051928
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4653055 Time: 0.04172
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4915199 Time: 0.04152
[07/19/2022-13:00:52] [V] [TRT] Tactic: 4980735 Time: 0.04842
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5177343 Time: 0.038308
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5242879 Time: 0.038152
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5373951 Time: 0.03742
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5439487 Time: 0.038968
[07/19/2022-13:00:52] [V] [TRT] Tactic: 5570559 Time: 0.055432
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5636095 Time: 0.054148
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5701631 Time: 0.0453
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5767167 Time: 0.045176
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5832703 Time: 0.039204
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5898239 Time: 0.034524
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6029311 Time: 0.044676
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6225919 Time: 0.030832
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6291455 Time: 0.03474
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6422527 Time: 0.049668
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6750207 Time: 0.03956
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6815743 Time: 0.038016
[07/19/2022-13:00:53] [V] [TRT] Tactic: 6946815 Time: 0.052368
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7012351 Time: 0.050564
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7077887 Time: 0.033848
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7143423 Time: 0.048152
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7208959 Time: 0.039996
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7340031 Time: 0.035396
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7405567 Time: 0.035684
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7536639 Time: 0.04236
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7602175 Time: 0.051556
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7733247 Time: 0.032624
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7798783 Time: 0.061432
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8191999 Time: 0.052436
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8257535 Time: 0.040176
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8323071 Time: 0.038616
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8650751 Time: 0.052584
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8716287 Time: 0.032816
[07/19/2022-13:00:53] [V] [TRT] Tactic: 9109503 Time: 0.048864
[07/19/2022-13:00:53] [V] [TRT] Tactic: 9568255 Time: 0.04098
[07/19/2022-13:00:53] [V] [TRT] Tactic: 9895935 Time: 0.041408
[07/19/2022-13:00:53] [V] [TRT] Tactic: 10223615 Time: 0.078044
[07/19/2022-13:00:53] [V] [TRT] Tactic: 10354687 Time: 0.048684
[07/19/2022-13:00:53] [V] [TRT] Tactic: 10551295 Time: 0.039392
[07/19/2022-13:00:53] [V] [TRT] Tactic: 10747903 Time: 0.031904
[07/19/2022-13:00:53] [V] [TRT] Tactic: 10944511 Time: 0.048616
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 6225919 Time: 0.030832
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CudnnConvolution)
[07/19/2022-13:00:53] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CublasConvolution)
[07/19/2022-13:00:53] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D (CaskConvolution)
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:53] [V] [TRT] Tactic: 3066127711859985668 Time: 0.021224
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:53] [V] [TRT] Tactic: 3564772625446233998 Time: 0.0231
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:53] [V] [TRT] Tactic: 5319956359050645452 Time: 0.022068
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:53] [V] [TRT] Tactic: 7205456024582378848 Time: 0.021164
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:53] [V] [TRT] Tactic: 8163473458334948789 Time: 0.019656
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:53] [V] [TRT] Tactic: -4212163711445252890 Time: 0.030816
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:53] [V] [TRT] Tactic: -3898373634979201110 Time: 0.030928
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:53] [V] [TRT] Tactic: -2409163523992614473 Time: 0.0204
[07/19/2022-13:00:53] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:53] [V] [TRT] Tactic: -1716393687483585322 Time: 0.030224
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.019656
[07/19/2022-13:00:53] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 8163473458334948789
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.017844
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.01632
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.01632
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.237592
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.013168
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.013168
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.019648
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.009476
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.009476
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.0215
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.014564
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.014564
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.01476
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.01506
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 1002 Time: 0.01476
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.017704
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.017684
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.017684
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.244144
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.011104
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.011104
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.012872
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.01632
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 1002 Time: 0.012872
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.017936
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.009372
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.009372
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.018988
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.009336
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.009336
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.01276
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.01778
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 1002 Time: 0.01276
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.025816
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.00912
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.00912
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.01784
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.016356
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.016356
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.2372
[07/19/2022-13:00:53] [V] [TRT] Tactic: 0 Time: 0.013264
[07/19/2022-13:00:53] [V] [TRT] Fastest Tactic: 0 Time: 0.013264
[07/19/2022-13:00:53] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:53] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:53] [V] [TRT] Tactic: 1002 Time: 0.020028
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.009412
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.009412
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.02192
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.014464
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.014464
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.01476
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.014856
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 1002 Time: 0.01476
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.017864
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.017768
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.017768
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.2451
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.011156
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.011156
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.01282
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.01632
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 1002 Time: 0.01282
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.018
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.009316
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.009316
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.019328
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.009304
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.009304
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.012744
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.017876
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 1002 Time: 0.012744
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1002 Time: 0.025836
[07/19/2022-13:00:54] [V] [TRT] Tactic: 0 Time: 0.009276
[07/19/2022-13:00:54] [V] [TRT] Fastest Tactic: 0 Time: 0.009276
[07/19/2022-13:00:54] [V] [TRT] *************** Autotuning format combination: Float(12544,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:54] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:54] [V] [TRT] Tactic: 589823 Time: 0.309912
[07/19/2022-13:00:54] [V] [TRT] Tactic: 655359 Time: 0.283876
[07/19/2022-13:00:54] [V] [TRT] Tactic: 786431 Time: 0.328296
[07/19/2022-13:00:54] [V] [TRT] Tactic: 851967 Time: 0.293312
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1179647 Time: 0.31278
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1310719 Time: 0.487344
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1376255 Time: 0.307304
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1441791 Time: 0.350136
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1507327 Time: 0.319104
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1638399 Time: 0.37108
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1835007 Time: 0.339584
[07/19/2022-13:00:54] [V] [TRT] Tactic: 1900543 Time: 0.326932
[07/19/2022-13:00:54] [V] [TRT] Tactic: 2097151 Time: 0.318572
[07/19/2022-13:00:54] [V] [TRT] Tactic: 2162687 Time: 0.303908
[07/19/2022-13:00:54] [V] [TRT] Tactic: 2293759 Time: 0.303596
[07/19/2022-13:00:54] [V] [TRT] Tactic: 2359295 Time: 0.323008
[07/19/2022-13:00:54] [V] [TRT] Tactic: 2686975 Time: 0.30942
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3080191 Time: 0.296956
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3342335 Time: 0.323544
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3407871 Time: 0.301172
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3538943 Time: 0.292072
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3670015 Time: 0.293676
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3932159 Time: 0.317704
[07/19/2022-13:00:54] [V] [TRT] Tactic: 3997695 Time: 0.303728
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4063231 Time: 0.2872
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4194303 Time: 0.331284
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4259839 Time: 0.33394
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4325375 Time: 0.346996
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4521983 Time: 0.353596
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4587519 Time: 0.322612
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4653055 Time: 0.32026
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4915199 Time: 0.305636
[07/19/2022-13:00:55] [V] [TRT] Tactic: 4980735 Time: 0.361316
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5177343 Time: 0.311216
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5242879 Time: 0.29012
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5373951 Time: 0.28346
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5439487 Time: 0.31026
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5570559 Time: 0.294464
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5636095 Time: 0.286448
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5701631 Time: 0.316076
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5767167 Time: 0.330496
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5832703 Time: 0.294076
[07/19/2022-13:00:55] [V] [TRT] Tactic: 5898239 Time: 0.282536
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6029311 Time: 0.296484
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6225919 Time: 0.291724
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6291455 Time: 0.313476
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6422527 Time: 0.304564
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6750207 Time: 0.31684
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6815743 Time: 0.295652
[07/19/2022-13:00:55] [V] [TRT] Tactic: 6946815 Time: 0.331352
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7012351 Time: 0.3315
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7077887 Time: 0.29908
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7143423 Time: 0.374024
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7208959 Time: 0.312808
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7340031 Time: 0.296936
[07/19/2022-13:00:55] [V] [TRT] Tactic: 7405567 Time: 0.305512
[07/19/2022-13:00:56] [V] [TRT] Tactic: 7536639 Time: 0.30538
[07/19/2022-13:00:56] [V] [TRT] Tactic: 7602175 Time: 0.358156
[07/19/2022-13:00:56] [V] [TRT] Tactic: 7733247 Time: 0.29626
[07/19/2022-13:00:56] [V] [TRT] Tactic: 7798783 Time: 0.34908
[07/19/2022-13:00:56] [V] [TRT] Tactic: 8191999 Time: 0.379604
[07/19/2022-13:00:56] [V] [TRT] Tactic: 8257535 Time: 0.316224
[07/19/2022-13:00:56] [V] [TRT] Tactic: 8323071 Time: 0.322656
[07/19/2022-13:00:56] [V] [TRT] Tactic: 8650751 Time: 0.37118
[07/19/2022-13:00:56] [V] [TRT] Tactic: 8716287 Time: 0.289752
[07/19/2022-13:00:56] [V] [TRT] Tactic: 9109503 Time: 0.335
[07/19/2022-13:00:56] [V] [TRT] Tactic: 9568255 Time: 0.318108
[07/19/2022-13:00:56] [V] [TRT] Tactic: 9895935 Time: 0.356936
[07/19/2022-13:00:56] [V] [TRT] Tactic: 10223615 Time: 0.333372
[07/19/2022-13:00:56] [V] [TRT] Tactic: 10354687 Time: 0.368424
[07/19/2022-13:00:56] [V] [TRT] Tactic: 10551295 Time: 0.337816
[07/19/2022-13:00:56] [V] [TRT] Tactic: 10747903 Time: 0.31934
[07/19/2022-13:00:56] [V] [TRT] Tactic: 10944511 Time: 0.394036
[07/19/2022-13:00:56] [V] [TRT] Fastest Tactic: 5898239 Time: 0.282536
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:56] [V] [TRT] Tactic: 0 Time: 0.28424
[07/19/2022-13:00:56] [V] [TRT] Tactic: 1 Time: 0.283252
[07/19/2022-13:00:56] [V] [TRT] Tactic: 2 Time: 0.3563
[07/19/2022-13:00:56] [V] [TRT] Tactic: 4 skipped. Scratch requested: 57016320, available: 16777216
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5 Time: 1.12168
[07/19/2022-13:00:56] [V] [TRT] Fastest Tactic: 1 Time: 0.283252
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:56] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:00:56] [V] [TRT] Tactic: 1062367460111450758 Time: 0.10816
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:00:56] [V] [TRT] Tactic: 1698681053543049347 Time: 0.094768
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:00:56] [V] [TRT] Tactic: 4501471010995462441 Time: 0.085852
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5137655947464784826 Time: 0.08696
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5288347012147084929 Time: 0.08786
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5326823351883942011 Time: 0.085716
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5500448035057547314 Time: 0.088904
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:00:56] [V] [TRT] Tactic: 6645123197870846056 Time: 0.092332
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:00:56] [V] [TRT] Tactic: 7144526460361122478 Time: 0.104884
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:00:56] [V] [TRT] Tactic: -8262349710178828730 Time: 0.088304
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:00:56] [V] [TRT] Tactic: -6576203419454146580 Time: 0.101208
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:00:56] [V] [TRT] Tactic: -4787320710726427159 Time: 0.108972
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:00:56] [V] [TRT] Tactic: -3456450830548107839 Time: 0.103948
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:00:56] [V] [TRT] Tactic: -1218658103698133241 Time: 0.094736
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:00:56] [V] [TRT] Tactic: -836875257600482091 Time: 0.091704
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:00:56] [V] [TRT] Tactic: -410470605513481746 Time: 0.086096
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:00:56] [V] [TRT] Tactic: -377491875521947884 Time: 0.087724
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:00:56] [V] [TRT] Tactic: -37215280111360163 Time: 0.091688
[07/19/2022-13:00:56] [V] [TRT] Fastest Tactic: 5326823351883942011 Time: 0.085716
[07/19/2022-13:00:56] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5326823351883942011
[07/19/2022-13:00:56] [V] [TRT] *************** Autotuning format combination: Float(12544,1,896,64) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:56] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:56] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:00:56] [V] [TRT] Tactic: 3886731678879822788 Time: 0.094444
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:00:56] [V] [TRT] Tactic: 6629944304117643200 Time: 0.21474
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:00:56] [V] [TRT] Tactic: -9153228964338181824 Time: 0.219724
[07/19/2022-13:00:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:00:56] [V] [TRT] Tactic: -7394439838318485025 Time: 0.098688
[07/19/2022-13:00:56] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.094444
[07/19/2022-13:00:56] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:00:56] [V] [TRT] *************** Autotuning format combination: Half(12544,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:56] [V] [TRT] Tactic: 0 Time: 0.24356
[07/19/2022-13:00:56] [V] [TRT] Tactic: 1 Time: 0.235624
[07/19/2022-13:00:56] [V] [TRT] Tactic: 2 Time: 0.259332
[07/19/2022-13:00:56] [V] [TRT] Tactic: 4 skipped. Scratch requested: 57016320, available: 16777216
[07/19/2022-13:00:56] [V] [TRT] Tactic: 5 Time: 1.11356
[07/19/2022-13:00:56] [V] [TRT] Fastest Tactic: 1 Time: 0.235624
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:56] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:56] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:00:56] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:56] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:56] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:00:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:00:56] [V] [TRT] Tactic: 589823 Time: 0.118996
[07/19/2022-13:00:57] [V] [TRT] Tactic: 655359 Time: 0.116568
[07/19/2022-13:00:57] [V] [TRT] Tactic: 786431 Time: 0.17252
[07/19/2022-13:00:57] [V] [TRT] Tactic: 851967 Time: 0.14346
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1179647 Time: 0.127824
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1310719 Time: 0.268096
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1376255 Time: 0.11628
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1441791 Time: 0.174244
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1507327 Time: 0.137116
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1638399 Time: 0.18282
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1835007 Time: 0.172988
[07/19/2022-13:00:57] [V] [TRT] Tactic: 1900543 Time: 0.128924
[07/19/2022-13:00:57] [V] [TRT] Tactic: 2097151 Time: 0.195356
[07/19/2022-13:00:57] [V] [TRT] Tactic: 2162687 Time: 0.10754
[07/19/2022-13:00:57] [V] [TRT] Tactic: 2293759 Time: 0.107848
[07/19/2022-13:00:57] [V] [TRT] Tactic: 2359295 Time: 0.133652
[07/19/2022-13:00:57] [V] [TRT] Tactic: 2686975 Time: 0.147368
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3080191 Time: 0.106456
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3342335 Time: 0.124216
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3407871 Time: 0.113824
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3538943 Time: 0.112544
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3670015 Time: 0.117452
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3932159 Time: 0.12096
[07/19/2022-13:00:57] [V] [TRT] Tactic: 3997695 Time: 0.165464
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4063231 Time: 0.124004
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4194303 Time: 0.158848
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4259839 Time: 0.203216
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4325375 Time: 0.158144
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4521983 Time: 0.140004
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4587519 Time: 0.17964
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4653055 Time: 0.15872
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4915199 Time: 0.158212
[07/19/2022-13:00:57] [V] [TRT] Tactic: 4980735 Time: 0.164556
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5177343 Time: 0.141876
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5242879 Time: 0.113384
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5373951 Time: 0.133992
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5439487 Time: 0.145208
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5570559 Time: 0.11216
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5636095 Time: 0.124428
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5701631 Time: 0.104116
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5767167 Time: 0.13814
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5832703 Time: 0.11416
[07/19/2022-13:00:57] [V] [TRT] Tactic: 5898239 Time: 0.141392
[07/19/2022-13:00:57] [V] [TRT] Tactic: 6029311 Time: 0.10192
[07/19/2022-13:00:57] [V] [TRT] Tactic: 6225919 Time: 0.10576
[07/19/2022-13:00:57] [V] [TRT] Tactic: 6291455 Time: 0.127772
[07/19/2022-13:00:58] [V] [TRT] Tactic: 6422527 Time: 0.102072
[07/19/2022-13:00:58] [V] [TRT] Tactic: 6750207 Time: 0.137252
[07/19/2022-13:00:58] [V] [TRT] Tactic: 6815743 Time: 0.11566
[07/19/2022-13:00:58] [V] [TRT] Tactic: 6946815 Time: 0.151368
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7012351 Time: 0.200684
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7077887 Time: 0.109644
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7143423 Time: 0.14662
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7208959 Time: 0.12324
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7340031 Time: 0.135936
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7405567 Time: 0.121548
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7536639 Time: 0.11012
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7602175 Time: 0.149276
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7733247 Time: 0.114368
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7798783 Time: 0.164004
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8191999 Time: 0.166352
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8257535 Time: 0.154428
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8323071 Time: 0.143516
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8650751 Time: 0.160964
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8716287 Time: 0.113924
[07/19/2022-13:00:58] [V] [TRT] Tactic: 9109503 Time: 0.192204
[07/19/2022-13:00:58] [V] [TRT] Tactic: 9568255 Time: 0.161988
[07/19/2022-13:00:58] [V] [TRT] Tactic: 9895935 Time: 0.161944
[07/19/2022-13:00:58] [V] [TRT] Tactic: 10223615 Time: 0.147096
[07/19/2022-13:00:58] [V] [TRT] Tactic: 10354687 Time: 0.198636
[07/19/2022-13:00:58] [V] [TRT] Tactic: 10551295 Time: 0.117032
[07/19/2022-13:00:58] [V] [TRT] Tactic: 10747903 Time: 0.118536
[07/19/2022-13:00:58] [V] [TRT] Tactic: 10944511 Time: 0.169644
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 6029311 Time: 0.10192
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:58] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:00:58] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:00:58] [V] [TRT] Tactic: 3066127711859985668 Time: 0.059916
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:00:58] [V] [TRT] Tactic: 3564772625446233998 Time: 0.065704
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:00:58] [V] [TRT] Tactic: 5319956359050645452 Time: 0.061452
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:00:58] [V] [TRT] Tactic: 7205456024582378848 Time: 0.050976
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:00:58] [V] [TRT] Tactic: 8163473458334948789 Time: 0.04872
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:00:58] [V] [TRT] Tactic: -4212163711445252890 Time: 0.048172
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:00:58] [V] [TRT] Tactic: -3898373634979201110 Time: 0.049412
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:00:58] [V] [TRT] Tactic: -2409163523992614473 Time: 0.052616
[07/19/2022-13:00:58] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:00:58] [V] [TRT] Tactic: -1716393687483585322 Time: 0.048456
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: -4212163711445252890 Time: 0.048172
[07/19/2022-13:00:58] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -4212163711445252890
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.092524
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.125016
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 1002 Time: 0.092524
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 1.71855
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.088592
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.088592
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.138756
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.056924
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.056924
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.129412
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.098344
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.098344
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.076728
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.094692
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 1002 Time: 0.076728
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.11756
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.10872
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.10872
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 1.68679
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.084216
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.084216
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.067316
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.109168
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 1002 Time: 0.067316
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.080908
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.052624
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.052624
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.102628
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.047376
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.047376
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.068184
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.110984
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 1002 Time: 0.068184
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:00:58] [V] [TRT] Tactic: 1002 Time: 0.16004
[07/19/2022-13:00:58] [V] [TRT] Tactic: 0 Time: 0.046664
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: 0 Time: 0.046664
[07/19/2022-13:00:58] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:00:58] [V] [TRT] Tactic: -1 Time: 0.16678
[07/19/2022-13:00:58] [V] [TRT] Fastest Tactic: -1 Time: 0.16678
[07/19/2022-13:00:58] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:00:59] [V] [TRT] Tactic: 0 Time: 0.279736
[07/19/2022-13:00:59] [V] [TRT] Tactic: 1 Time: 0.280592
[07/19/2022-13:00:59] [V] [TRT] Tactic: 2 Time: 0.285344
[07/19/2022-13:01:00] [V] [TRT] Tactic: 4 Time: 60.5317
[07/19/2022-13:01:01] [V] [TRT] Tactic: 5 Time: 70.1701
[07/19/2022-13:01:01] [V] [TRT] Tactic: 6 Time: 32.9716
[07/19/2022-13:01:01] [V] [TRT] Fastest Tactic: 0 Time: 0.279736
[07/19/2022-13:01:01] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:01] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:02] [V] [TRT] Tactic: 1062367460111450758 Time: 8.82456
[07/19/2022-13:01:02] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:01:02] [V] [TRT] Tactic: 1754984623894446479 Time: 9.46005
[07/19/2022-13:01:02] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:01:02] [V] [TRT] Tactic: 3611739942397549984 Time: 9.34771
[07/19/2022-13:01:02] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-13:01:02] [V] [TRT] Tactic: 3827454225649558724 Time: 7.86666
[07/19/2022-13:01:02] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:01:03] [V] [TRT] Tactic: 4337000649858996379 Time: 9.35293
[07/19/2022-13:01:03] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:03] [V] [TRT] Tactic: 4501471010995462441 Time: 8.74525
[07/19/2022-13:01:03] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:03] [V] [TRT] Tactic: 5137655947464784826 Time: 8.71009
[07/19/2022-13:01:03] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:03] [V] [TRT] Tactic: 5288347012147084929 Time: 8.732
[07/19/2022-13:01:03] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-13:01:04] [V] [TRT] Tactic: 5921334924264294896 Time: 7.90572
[07/19/2022-13:01:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:04] [V] [TRT] Tactic: 6645123197870846056 Time: 8.78246
[07/19/2022-13:01:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:04] [V] [TRT] Tactic: 7144526460361122478 Time: 8.65824
[07/19/2022-13:01:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-13:01:04] [V] [TRT] Tactic: 7852627285308570038 Time: 7.90134
[07/19/2022-13:01:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:01:05] [V] [TRT] Tactic: -9137461792520977713 Time: 9.33726
[07/19/2022-13:01:05] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-13:01:05] [V] [TRT] Tactic: -8776506421218919509 Time: 8.02182
[07/19/2022-13:01:05] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:05] [V] [TRT] Tactic: -8262349710178828730 Time: 8.72366
[07/19/2022-13:01:05] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:01:05] [V] [TRT] Tactic: -8133971918129952780 Time: 9.28487
[07/19/2022-13:01:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:01:06] [V] [TRT] Tactic: -6092040395344634144 Time: 9.31021
[07/19/2022-13:01:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:06] [V] [TRT] Tactic: -4787320710726427159 Time: 8.77759
[07/19/2022-13:01:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:06] [V] [TRT] Tactic: -3456450830548107839 Time: 8.67367
[07/19/2022-13:01:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-13:01:06] [V] [TRT] Tactic: -2318106587342035239 Time: 7.8166
[07/19/2022-13:01:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-13:01:07] [V] [TRT] Tactic: -1343271414618805657 Time: 7.79932
[07/19/2022-13:01:07] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:07] [V] [TRT] Tactic: -1218658103698133241 Time: 8.74888
[07/19/2022-13:01:07] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:07] [V] [TRT] Tactic: -836875257600482091 Time: 8.67179
[07/19/2022-13:01:07] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:07] [V] [TRT] Tactic: -410470605513481746 Time: 8.6918
[07/19/2022-13:01:07] [V] [TRT] Fastest Tactic: -1343271414618805657 Time: 7.79932
[07/19/2022-13:01:07] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:01:07] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:07] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:07] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:07] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:07] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:07] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:07] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:08] [V] [TRT] Tactic: 0 Time: 0.190832
[07/19/2022-13:01:08] [V] [TRT] Tactic: 1 Time: 0.195332
[07/19/2022-13:01:08] [V] [TRT] Tactic: 2 Time: 15.6058
[07/19/2022-13:01:09] [V] [TRT] Tactic: 4 Time: 60.2221
[07/19/2022-13:01:10] [V] [TRT] Tactic: 5 Time: 69.3828
[07/19/2022-13:01:11] [V] [TRT] Tactic: 6 Time: 52.0435
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: 0 Time: 0.190832
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1), Float(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CudaDepthwiseConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (FusedConvActConvolution)
[07/19/2022-13:01:11] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] Tactic: 0 Time: 0.137088
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1 Time: 0.12622
[07/19/2022-13:01:11] [V] [TRT] Tactic: 2 Time: 0.356996
[07/19/2022-13:01:11] [V] [TRT] Tactic: 4 skipped. Scratch requested: 58490880, available: 16777216
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5 Time: 1.02374
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: 1 Time: 0.12622
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CublasConvolution)
[07/19/2022-13:01:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1062367460111450758 Time: 0.083912
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1698681053543049347 Time: 0.092624
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:11] [V] [TRT] Tactic: 4501471010995462441 Time: 0.102448
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5137655947464784826 Time: 0.074152
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5288347012147084929 Time: 0.102596
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5326823351883942011 Time: 0.099452
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5500448035057547314 Time: 0.122308
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:11] [V] [TRT] Tactic: 6645123197870846056 Time: 0.07672
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:11] [V] [TRT] Tactic: 7144526460361122478 Time: 0.095796
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:11] [V] [TRT] Tactic: -8262349710178828730 Time: 0.103236
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:11] [V] [TRT] Tactic: -6576203419454146580 Time: 0.07432
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:11] [V] [TRT] Tactic: -4787320710726427159 Time: 0.098872
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:11] [V] [TRT] Tactic: -3456450830548107839 Time: 0.076928
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:11] [V] [TRT] Tactic: -1218658103698133241 Time: 0.126084
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:11] [V] [TRT] Tactic: -836875257600482091 Time: 0.125464
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:11] [V] [TRT] Tactic: -410470605513481746 Time: 0.100216
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:11] [V] [TRT] Tactic: -377491875521947884 Time: 0.100992
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:11] [V] [TRT] Tactic: -37215280111360163 Time: 0.074332
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: 5137655947464784826 Time: 0.074152
[07/19/2022-13:01:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 5137655947464784826
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384), Float(12544,1,896,64) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CublasConvolution)
[07/19/2022-13:01:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:11] [V] [TRT] Tactic: 3886731678879822788 Time: 0.061468
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:11] [V] [TRT] Tactic: 6629944304117643200 Time: 0.105732
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:11] [V] [TRT] Tactic: -9153228964338181824 Time: 0.107248
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:11] [V] [TRT] Tactic: -7394439838318485025 Time: 0.061264
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.061264
[07/19/2022-13:01:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1), Half(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] Tactic: 0 Time: 0.129516
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1 Time: 0.127308
[07/19/2022-13:01:11] [V] [TRT] Tactic: 2 Time: 0.344332
[07/19/2022-13:01:11] [V] [TRT] Tactic: 4 skipped. Scratch requested: 58490880, available: 16777216
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5 Time: 0.885044
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: 1 Time: 0.127308
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CublasConvolution)
[07/19/2022-13:01:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1), Half(6272,196:2,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (FusedConvActConvolution)
[07/19/2022-13:01:11] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CublasConvolution)
[07/19/2022-13:01:11] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:11] [V] [TRT] Tactic: 3066127711859985668 Time: 0.034476
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:11] [V] [TRT] Tactic: 3564772625446233998 Time: 0.03926
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:11] [V] [TRT] Tactic: 5319956359050645452 Time: 0.035928
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:11] [V] [TRT] Tactic: 7205456024582378848 Time: 0.034216
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:11] [V] [TRT] Tactic: 8163473458334948789 Time: 0.032016
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:11] [V] [TRT] Tactic: -4212163711445252890 Time: 0.052536
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:11] [V] [TRT] Tactic: -3898373634979201110 Time: 0.053468
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:11] [V] [TRT] Tactic: -2409163523992614473 Time: 0.032848
[07/19/2022-13:01:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:11] [V] [TRT] Tactic: -1716393687483585322 Time: 0.05228
[07/19/2022-13:01:11] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.032016
[07/19/2022-13:01:11] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 8163473458334948789
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,1,896,64) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(12544,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1), Float(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384), Float(12544,1,896,64) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1), Half(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1), Half(6272,196:2,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,1,896,64) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(12544,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1), Float(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384), Float(12544,1,896,64) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1), Half(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1), Half(6272,196:2,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(12544,1,896,64) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(12544,196,14,1) -> Half(6272,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Float(12544,1,896,64) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(6272,196:2,14,1) -> Half(12544,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(12544,1,896,64) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(12544,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(6272,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:11] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Float(75264,1,5376,384) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(75264,196,14,1) -> Half(37632,196:2,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Float(75264,1,5376,384) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning Reformat:Half(37632,196:2,14,1) -> Half(75264,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] *************** Autotuning format combination: Float(75264,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:01:11] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:11] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:01:11] [V] [TRT] Tactic: 589823 Time: 0.296504
[07/19/2022-13:01:11] [V] [TRT] Tactic: 655359 Time: 0.19274
[07/19/2022-13:01:11] [V] [TRT] Tactic: 786431 Time: 0.213044
[07/19/2022-13:01:11] [V] [TRT] Tactic: 851967 Time: 0.219104
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1179647 Time: 0.201824
[07/19/2022-13:01:11] [V] [TRT] Tactic: 1310719 Time: 0.430764
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1376255 Time: 0.330112
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1441791 Time: 0.268336
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1507327 Time: 0.30158
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1638399 Time: 0.274132
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1835007 Time: 0.215568
[07/19/2022-13:01:12] [V] [TRT] Tactic: 1900543 Time: 0.312588
[07/19/2022-13:01:12] [V] [TRT] Tactic: 2097151 Time: 0.19504
[07/19/2022-13:01:12] [V] [TRT] Tactic: 2162687 Time: 0.34822
[07/19/2022-13:01:12] [V] [TRT] Tactic: 2293759 Time: 0.319516
[07/19/2022-13:01:12] [V] [TRT] Tactic: 2359295 Time: 0.322576
[07/19/2022-13:01:12] [V] [TRT] Tactic: 2686975 Time: 0.313904
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3080191 Time: 0.212716
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3342335 Time: 0.3085
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3407871 Time: 0.202524
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3538943 Time: 0.189612
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3670015 Time: 0.29612
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3932159 Time: 0.298476
[07/19/2022-13:01:12] [V] [TRT] Tactic: 3997695 Time: 0.182836
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4063231 Time: 0.208108
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4194303 Time: 0.214468
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4259839 Time: 0.202928
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4325375 Time: 0.228504
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4521983 Time: 0.314608
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4587519 Time: 0.19794
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4653055 Time: 0.233124
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4915199 Time: 0.185552
[07/19/2022-13:01:12] [V] [TRT] Tactic: 4980735 Time: 0.226608
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5177343 Time: 0.223432
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5242879 Time: 0.195656
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5373951 Time: 0.214248
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5439487 Time: 0.212128
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5570559 Time: 0.21508
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5636095 Time: 0.207664
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5701631 Time: 0.337364
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5767167 Time: 0.296752
[07/19/2022-13:01:12] [V] [TRT] Tactic: 5832703 Time: 0.200412
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5898239 Time: 0.172872
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6029311 Time: 0.317004
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6225919 Time: 0.177088
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6291455 Time: 0.202604
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6422527 Time: 0.242228
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6750207 Time: 0.169124
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6815743 Time: 0.2065
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6946815 Time: 0.240784
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7012351 Time: 0.194516
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7077887 Time: 0.1875
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7143423 Time: 0.270188
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7208959 Time: 0.259864
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7340031 Time: 0.180028
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7405567 Time: 0.212848
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7536639 Time: 0.204848
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7602175 Time: 0.241716
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7733247 Time: 0.191604
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7798783 Time: 0.21244
[07/19/2022-13:01:13] [V] [TRT] Tactic: 8191999 Time: 0.275776
[07/19/2022-13:01:13] [V] [TRT] Tactic: 8257535 Time: 0.194732
[07/19/2022-13:01:13] [V] [TRT] Tactic: 8323071 Time: 0.19692
[07/19/2022-13:01:13] [V] [TRT] Tactic: 8650751 Time: 0.253164
[07/19/2022-13:01:13] [V] [TRT] Tactic: 8716287 Time: 0.187208
[07/19/2022-13:01:13] [V] [TRT] Tactic: 9109503 Time: 0.192916
[07/19/2022-13:01:13] [V] [TRT] Tactic: 9568255 Time: 0.185328
[07/19/2022-13:01:13] [V] [TRT] Tactic: 9895935 Time: 0.213828
[07/19/2022-13:01:13] [V] [TRT] Tactic: 10223615 Time: 0.31342
[07/19/2022-13:01:13] [V] [TRT] Tactic: 10354687 Time: 0.206572
[07/19/2022-13:01:13] [V] [TRT] Tactic: 10551295 Time: 0.207144
[07/19/2022-13:01:13] [V] [TRT] Tactic: 10747903 Time: 0.190396
[07/19/2022-13:01:13] [V] [TRT] Tactic: 10944511 Time: 0.226708
[07/19/2022-13:01:13] [V] [TRT] Fastest Tactic: 6750207 Time: 0.169124
[07/19/2022-13:01:13] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:13] [V] [TRT] Tactic: 0 Time: 0.195224
[07/19/2022-13:01:13] [V] [TRT] Tactic: 1 Time: 0.161308
[07/19/2022-13:01:13] [V] [TRT] Tactic: 2 Time: 0.361316
[07/19/2022-13:01:13] [V] [TRT] Tactic: 4 skipped. Scratch requested: 86851584, available: 16777216
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5 Time: 1.22372
[07/19/2022-13:01:13] [V] [TRT] Fastest Tactic: 1 Time: 0.161308
[07/19/2022-13:01:13] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:13] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:13] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:13] [V] [TRT] Tactic: 1062367460111450758 Time: 0.09656
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:13] [V] [TRT] Tactic: 1698681053543049347 Time: 0.096984
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:13] [V] [TRT] Tactic: 4501471010995462441 Time: 0.10106
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5137655947464784826 Time: 0.105444
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5288347012147084929 Time: 0.101252
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5326823351883942011 Time: 0.098676
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:13] [V] [TRT] Tactic: 5500448035057547314 Time: 0.111796
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:13] [V] [TRT] Tactic: 6645123197870846056 Time: 0.107732
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:13] [V] [TRT] Tactic: 7144526460361122478 Time: 0.1685
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:13] [V] [TRT] Tactic: -8262349710178828730 Time: 0.10286
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:13] [V] [TRT] Tactic: -6576203419454146580 Time: 0.087532
[07/19/2022-13:01:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:13] [V] [TRT] Tactic: -4787320710726427159 Time: 0.172016
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:14] [V] [TRT] Tactic: -3456450830548107839 Time: 0.092972
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:14] [V] [TRT] Tactic: -1218658103698133241 Time: 0.118732
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:14] [V] [TRT] Tactic: -836875257600482091 Time: 0.115876
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:14] [V] [TRT] Tactic: -410470605513481746 Time: 0.100056
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:14] [V] [TRT] Tactic: -377491875521947884 Time: 0.099712
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:14] [V] [TRT] Tactic: -37215280111360163 Time: 0.103208
[07/19/2022-13:01:14] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.087532
[07/19/2022-13:01:14] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:01:14] [V] [TRT] *************** Autotuning format combination: Float(75264,1,5376,384) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:14] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:14] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3886731678879822788 Time: 0.10422
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:14] [V] [TRT] Tactic: 6629944304117643200 Time: 0.139004
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:14] [V] [TRT] Tactic: -9153228964338181824 Time: 0.141236
[07/19/2022-13:01:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:14] [V] [TRT] Tactic: -7394439838318485025 Time: 0.104856
[07/19/2022-13:01:14] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.10422
[07/19/2022-13:01:14] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:01:14] [V] [TRT] *************** Autotuning format combination: Half(75264,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:14] [V] [TRT] Tactic: 0 Time: 0.167492
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1 Time: 0.143628
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2 Time: 0.344996
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4 skipped. Scratch requested: 86851584, available: 16777216
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5 Time: 1.10642
[07/19/2022-13:01:14] [V] [TRT] Fastest Tactic: 1 Time: 0.143628
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:14] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:14] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:14] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:14] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:14] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:14] [V] [TRT] *************** Autotuning format combination: Half(37632,196:2,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:14] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:01:14] [V] [TRT] Tactic: 589823 Time: 0.090204
[07/19/2022-13:01:14] [V] [TRT] Tactic: 655359 Time: 0.10558
[07/19/2022-13:01:14] [V] [TRT] Tactic: 786431 Time: 0.103884
[07/19/2022-13:01:14] [V] [TRT] Tactic: 851967 Time: 0.09328
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1179647 Time: 0.088736
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1310719 Time: 0.246976
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1376255 Time: 0.10116
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1441791 Time: 0.118188
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1507327 Time: 0.102304
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1638399 Time: 0.112416
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1835007 Time: 0.10424
[07/19/2022-13:01:14] [V] [TRT] Tactic: 1900543 Time: 0.111592
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2097151 Time: 0.11022
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2162687 Time: 0.111604
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2293759 Time: 0.107552
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2359295 Time: 0.11512
[07/19/2022-13:01:14] [V] [TRT] Tactic: 2686975 Time: 0.187112
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3080191 Time: 0.088384
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3342335 Time: 0.100592
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3407871 Time: 0.09708
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3538943 Time: 0.088732
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3670015 Time: 0.156716
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3932159 Time: 0.10226
[07/19/2022-13:01:14] [V] [TRT] Tactic: 3997695 Time: 0.105176
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4063231 Time: 0.085424
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4194303 Time: 0.100104
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4259839 Time: 0.112516
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4325375 Time: 0.118308
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4521983 Time: 0.108932
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4587519 Time: 0.109672
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4653055 Time: 0.108788
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4915199 Time: 0.08934
[07/19/2022-13:01:14] [V] [TRT] Tactic: 4980735 Time: 0.135628
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5177343 Time: 0.10502
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5242879 Time: 0.086476
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5373951 Time: 0.100072
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5439487 Time: 0.100016
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5570559 Time: 0.09222
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5636095 Time: 0.085172
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5701631 Time: 0.105408
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5767167 Time: 0.1169
[07/19/2022-13:01:14] [V] [TRT] Tactic: 5832703 Time: 0.093596
[07/19/2022-13:01:15] [V] [TRT] Tactic: 5898239 Time: 0.091208
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6029311 Time: 0.098652
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6225919 Time: 0.081864
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6291455 Time: 0.088836
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6422527 Time: 0.085696
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6750207 Time: 0.086208
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6815743 Time: 0.091824
[07/19/2022-13:01:15] [V] [TRT] Tactic: 6946815 Time: 0.103132
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7012351 Time: 0.110228
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7077887 Time: 0.083328
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7143423 Time: 0.123032
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7208959 Time: 0.10518
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7340031 Time: 0.095312
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7405567 Time: 0.088208
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7536639 Time: 0.105304
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7602175 Time: 0.095392
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7733247 Time: 0.08672
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7798783 Time: 0.103728
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8191999 Time: 0.129368
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8257535 Time: 0.088936
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8323071 Time: 0.091768
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8650751 Time: 0.105228
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8716287 Time: 0.09292
[07/19/2022-13:01:15] [V] [TRT] Tactic: 9109503 Time: 0.109116
[07/19/2022-13:01:15] [V] [TRT] Tactic: 9568255 Time: 0.08984
[07/19/2022-13:01:15] [V] [TRT] Tactic: 9895935 Time: 0.099424
[07/19/2022-13:01:15] [V] [TRT] Tactic: 10223615 Time: 0.187136
[07/19/2022-13:01:15] [V] [TRT] Tactic: 10354687 Time: 0.10534
[07/19/2022-13:01:15] [V] [TRT] Tactic: 10551295 Time: 0.08364
[07/19/2022-13:01:15] [V] [TRT] Tactic: 10747903 Time: 0.08412
[07/19/2022-13:01:15] [V] [TRT] Tactic: 10944511 Time: 0.135424
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 6225919 Time: 0.081864
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:15] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:15] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:15] [V] [TRT] Tactic: 3066127711859985668 Time: 0.049364
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:15] [V] [TRT] Tactic: 3564772625446233998 Time: 0.053244
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:15] [V] [TRT] Tactic: 5319956359050645452 Time: 0.05256
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:15] [V] [TRT] Tactic: 7205456024582378848 Time: 0.058364
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:15] [V] [TRT] Tactic: 8163473458334948789 Time: 0.054852
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:15] [V] [TRT] Tactic: -4212163711445252890 Time: 0.051648
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:15] [V] [TRT] Tactic: -3898373634979201110 Time: 0.05254
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:15] [V] [TRT] Tactic: -2409163523992614473 Time: 0.056828
[07/19/2022-13:01:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:15] [V] [TRT] Tactic: -1716393687483585322 Time: 0.051012
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.049364
[07/19/2022-13:01:15] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.027648
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.02294
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.02294
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.354408
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.019628
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.019628
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.027172
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.013888
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.013888
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.032508
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.021104
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.021104
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.019496
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.021084
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 1002 Time: 0.019496
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.023356
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.024436
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 1002 Time: 0.023356
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.364068
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.015768
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.015768
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.017256
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.023032
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 1002 Time: 0.017256
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.021996
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.013252
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.013252
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.025632
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.011968
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.011968
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.017196
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.025944
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 1002 Time: 0.017196
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.034696
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.011672
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.011672
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.027492
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.022744
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.022744
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:15] [V] [TRT] Tactic: 1002 Time: 0.353888
[07/19/2022-13:01:15] [V] [TRT] Tactic: 0 Time: 0.01908
[07/19/2022-13:01:15] [V] [TRT] Fastest Tactic: 0 Time: 0.01908
[07/19/2022-13:01:15] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:15] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.02764
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.01352
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.01352
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.032556
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.020924
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.020924
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.019556
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.021064
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.019556
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.023832
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.024408
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.023832
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.363852
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.015952
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.015952
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.016808
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.02298
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.016808
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.022504
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.013244
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.013244
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.025844
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.011748
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.011748
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.0167
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.026
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.0167
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.03464
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.011832
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.011832
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning format combination: Float(18816,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:01:16] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:01:16] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.427476
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1 Time: 0.424344
[07/19/2022-13:01:16] [V] [TRT] Tactic: 2 Time: 0.511316
[07/19/2022-13:01:16] [V] [TRT] Tactic: 4 skipped. Scratch requested: 128065536, available: 16777216
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5 Time: 1.89152
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1 Time: 0.424344
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:16] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1062367460111450758 Time: 0.185084
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1698681053543049347 Time: 0.162184
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:16] [V] [TRT] Tactic: 4501471010995462441 Time: 0.157064
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5137655947464784826 Time: 0.143388
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5288347012147084929 Time: 0.158476
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5326823351883942011 Time: 0.154
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5500448035057547314 Time: 0.15866
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:16] [V] [TRT] Tactic: 6645123197870846056 Time: 0.146116
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:16] [V] [TRT] Tactic: 7144526460361122478 Time: 0.184264
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:16] [V] [TRT] Tactic: -8262349710178828730 Time: 0.160104
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:16] [V] [TRT] Tactic: -6576203419454146580 Time: 0.168644
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:16] [V] [TRT] Tactic: -4787320710726427159 Time: 0.186832
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:16] [V] [TRT] Tactic: -3456450830548107839 Time: 0.174628
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:16] [V] [TRT] Tactic: -1218658103698133241 Time: 0.166068
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:16] [V] [TRT] Tactic: -836875257600482091 Time: 0.162908
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:16] [V] [TRT] Tactic: -410470605513481746 Time: 0.155764
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:16] [V] [TRT] Tactic: -377491875521947884 Time: 0.156136
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:16] [V] [TRT] Tactic: -37215280111360163 Time: 0.140708
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.140708
[07/19/2022-13:01:16] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning format combination: Float(18816,1,1344,96) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:16] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:16] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:16] [V] [TRT] Tactic: 3886731678879822788 Time: 0.156636
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:16] [V] [TRT] Tactic: 6629944304117643200 Time: 0.320896
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:16] [V] [TRT] Tactic: -9153228964338181824 Time: 0.324368
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:16] [V] [TRT] Tactic: -7394439838318485025 Time: 0.156888
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.156636
[07/19/2022-13:01:16] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning format combination: Half(18816,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.366852
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1 Time: 0.343672
[07/19/2022-13:01:16] [V] [TRT] Tactic: 2 Time: 0.404188
[07/19/2022-13:01:16] [V] [TRT] Tactic: 4 skipped. Scratch requested: 128065536, available: 16777216
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5 Time: 1.80232
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1 Time: 0.343672
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:16] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:16] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:16] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:01:16] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:16] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:16] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:16] [V] [TRT] Tactic: 3066127711859985668 Time: 0.096984
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:16] [V] [TRT] Tactic: 3564772625446233998 Time: 0.106508
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:16] [V] [TRT] Tactic: 5319956359050645452 Time: 0.099796
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:16] [V] [TRT] Tactic: 7205456024582378848 Time: 0.081784
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:16] [V] [TRT] Tactic: 8163473458334948789 Time: 0.07922
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:16] [V] [TRT] Tactic: -4212163711445252890 Time: 0.0847
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:16] [V] [TRT] Tactic: -3898373634979201110 Time: 0.086656
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:16] [V] [TRT] Tactic: -2409163523992614473 Time: 0.080312
[07/19/2022-13:01:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:16] [V] [TRT] Tactic: -1716393687483585322 Time: 0.08406
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.07922
[07/19/2022-13:01:16] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 8163473458334948789
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.120436
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.170024
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.120436
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 2.10224
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.112068
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.112068
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.197472
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.068412
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.068412
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.161924
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.139112
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.139112
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.093164
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.127728
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.093164
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.171612
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.137508
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.137508
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 2.15942
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.103828
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.103828
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.085892
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.150036
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.085892
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.118596
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.067404
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.067404
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.133352
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.064636
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 0 Time: 0.064636
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:16] [V] [TRT] Tactic: 1002 Time: 0.089612
[07/19/2022-13:01:16] [V] [TRT] Tactic: 0 Time: 0.141664
[07/19/2022-13:01:16] [V] [TRT] Fastest Tactic: 1002 Time: 0.089612
[07/19/2022-13:01:16] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:16] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:17] [V] [TRT] Tactic: 1002 Time: 0.214644
[07/19/2022-13:01:17] [V] [TRT] Tactic: 0 Time: 0.05994
[07/19/2022-13:01:17] [V] [TRT] Fastest Tactic: 0 Time: 0.05994
[07/19/2022-13:01:17] [V] [TRT] *************** Autotuning format combination: Float(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:17] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:01:17] [V] [TRT] Tactic: -1 Time: 0.215664
[07/19/2022-13:01:17] [V] [TRT] Fastest Tactic: -1 Time: 0.215664
[07/19/2022-13:01:17] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:17] [V] [TRT] Tactic: 0 Time: 0.3748
[07/19/2022-13:01:17] [V] [TRT] Tactic: 1 Time: 0.37362
[07/19/2022-13:01:17] [V] [TRT] Tactic: 2 Time: 0.374232
[07/19/2022-13:01:18] [V] [TRT] Tactic: 4 Time: 90.0097
[07/19/2022-13:01:20] [V] [TRT] Tactic: 5 Time: 104.243
[07/19/2022-13:01:21] [V] [TRT] Tactic: 6 Time: 49.2384
[07/19/2022-13:01:21] [V] [TRT] Fastest Tactic: 1 Time: 0.37362
[07/19/2022-13:01:21] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:21] [V] [TRT] Tactic: 1062367460111450758 Time: 13.1678
[07/19/2022-13:01:21] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:01:21] [V] [TRT] Tactic: 1754984623894446479 Time: 14.3653
[07/19/2022-13:01:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:01:22] [V] [TRT] Tactic: 3611739942397549984 Time: 14.2165
[07/19/2022-13:01:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-13:01:22] [V] [TRT] Tactic: 3827454225649558724 Time: 11.8041
[07/19/2022-13:01:22] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:01:23] [V] [TRT] Tactic: 4337000649858996379 Time: 13.99
[07/19/2022-13:01:23] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:23] [V] [TRT] Tactic: 4501471010995462441 Time: 13.1453
[07/19/2022-13:01:23] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:23] [V] [TRT] Tactic: 5137655947464784826 Time: 13.0287
[07/19/2022-13:01:24] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:24] [V] [TRT] Tactic: 5288347012147084929 Time: 13.0855
[07/19/2022-13:01:24] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-13:01:24] [V] [TRT] Tactic: 5921334924264294896 Time: 11.6736
[07/19/2022-13:01:24] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:24] [V] [TRT] Tactic: 6645123197870846056 Time: 13.1716
[07/19/2022-13:01:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:25] [V] [TRT] Tactic: 7144526460361122478 Time: 13.1787
[07/19/2022-13:01:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-13:01:25] [V] [TRT] Tactic: 7852627285308570038 Time: 11.8181
[07/19/2022-13:01:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:01:26] [V] [TRT] Tactic: -9137461792520977713 Time: 14.0755
[07/19/2022-13:01:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-13:01:26] [V] [TRT] Tactic: -8776506421218919509 Time: 11.8088
[07/19/2022-13:01:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:26] [V] [TRT] Tactic: -8262349710178828730 Time: 13.2162
[07/19/2022-13:01:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:01:27] [V] [TRT] Tactic: -8133971918129952780 Time: 14.0517
[07/19/2022-13:01:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:01:27] [V] [TRT] Tactic: -6092040395344634144 Time: 14.0211
[07/19/2022-13:01:27] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:28] [V] [TRT] Tactic: -4787320710726427159 Time: 13.361
[07/19/2022-13:01:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:28] [V] [TRT] Tactic: -3456450830548107839 Time: 13.0473
[07/19/2022-13:01:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-13:01:28] [V] [TRT] Tactic: -2318106587342035239 Time: 11.788
[07/19/2022-13:01:28] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-13:01:29] [V] [TRT] Tactic: -1343271414618805657 Time: 11.6403
[07/19/2022-13:01:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:29] [V] [TRT] Tactic: -1218658103698133241 Time: 13.0349
[07/19/2022-13:01:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:29] [V] [TRT] Tactic: -836875257600482091 Time: 13.0422
[07/19/2022-13:01:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:30] [V] [TRT] Tactic: -410470605513481746 Time: 13.0536
[07/19/2022-13:01:30] [V] [TRT] Fastest Tactic: -1343271414618805657 Time: 11.6403
[07/19/2022-13:01:30] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:01:30] [V] [TRT] *************** Autotuning format combination: Float(112896,1,8064,576) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:30] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:30] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:30] [V] [TRT] *************** Autotuning format combination: Half(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:30] [V] [TRT] Tactic: 0 Time: 0.22536
[07/19/2022-13:01:30] [V] [TRT] Tactic: 1 Time: 0.22654
[07/19/2022-13:01:30] [V] [TRT] Tactic: 2 Time: 23.1936
[07/19/2022-13:01:32] [V] [TRT] Tactic: 4 Time: 89.6478
[07/19/2022-13:01:33] [V] [TRT] Tactic: 5 Time: 104.276
[07/19/2022-13:01:35] [V] [TRT] Tactic: 6 Time: 77.4505
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: 0 Time: 0.22536
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(56448,196:2,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,196,14,1), Float(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CudaDepthwiseConvolution)
[07/19/2022-13:01:35] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (FusedConvActConvolution)
[07/19/2022-13:01:35] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] Tactic: 0 Time: 0.284412
[07/19/2022-13:01:35] [V] [TRT] Tactic: 1 Time: 0.22742
[07/19/2022-13:01:35] [V] [TRT] Tactic: 2 Time: 0.455224
[07/19/2022-13:01:35] [V] [TRT] Tactic: 4 skipped. Scratch requested: 130277376, available: 16777216
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5 Time: 1.76705
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: 1 Time: 0.22742
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CublasConvolution)
[07/19/2022-13:01:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:35] [V] [TRT] Tactic: 1062367460111450758 Time: 0.139852
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:35] [V] [TRT] Tactic: 1698681053543049347 Time: 0.142124
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:35] [V] [TRT] Tactic: 4501471010995462441 Time: 0.146148
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5137655947464784826 Time: 0.151312
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5288347012147084929 Time: 0.145468
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5326823351883942011 Time: 0.142496
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5500448035057547314 Time: 0.162776
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:35] [V] [TRT] Tactic: 6645123197870846056 Time: 0.154564
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:35] [V] [TRT] Tactic: 7144526460361122478 Time: 0.2597
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:35] [V] [TRT] Tactic: -8262349710178828730 Time: 0.14772
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:35] [V] [TRT] Tactic: -6576203419454146580 Time: 0.124412
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:35] [V] [TRT] Tactic: -4787320710726427159 Time: 0.261012
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:35] [V] [TRT] Tactic: -3456450830548107839 Time: 0.13058
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:35] [V] [TRT] Tactic: -1218658103698133241 Time: 0.17182
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:35] [V] [TRT] Tactic: -836875257600482091 Time: 0.167892
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:35] [V] [TRT] Tactic: -410470605513481746 Time: 0.143256
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:35] [V] [TRT] Tactic: -377491875521947884 Time: 0.14448
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:35] [V] [TRT] Tactic: -37215280111360163 Time: 0.149168
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: -6576203419454146580 Time: 0.124412
[07/19/2022-13:01:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -6576203419454146580
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,1,8064,576), Float(18816,1,1344,96) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CublasConvolution)
[07/19/2022-13:01:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:35] [V] [TRT] Tactic: 3886731678879822788 Time: 0.155656
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:35] [V] [TRT] Tactic: 6629944304117643200 Time: 0.223504
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:35] [V] [TRT] Tactic: -9153228964338181824 Time: 0.22776
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:35] [V] [TRT] Tactic: -7394439838318485025 Time: 0.157492
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.155656
[07/19/2022-13:01:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(112896,196,14,1), Half(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] Tactic: 0 Time: 0.27608
[07/19/2022-13:01:35] [V] [TRT] Tactic: 1 Time: 0.238924
[07/19/2022-13:01:35] [V] [TRT] Tactic: 2 Time: 0.4376
[07/19/2022-13:01:35] [V] [TRT] Tactic: 4 skipped. Scratch requested: 130277376, available: 16777216
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5 Time: 1.58953
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: 1 Time: 0.238924
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CublasConvolution)
[07/19/2022-13:01:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(56448,196:2,14,1), Half(9408,196:2,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (FusedConvActConvolution)
[07/19/2022-13:01:35] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CublasConvolution)
[07/19/2022-13:01:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:35] [V] [TRT] Tactic: 3066127711859985668 Time: 0.072732
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:35] [V] [TRT] Tactic: 3564772625446233998 Time: 0.07982
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:35] [V] [TRT] Tactic: 5319956359050645452 Time: 0.077776
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:35] [V] [TRT] Tactic: 7205456024582378848 Time: 0.083848
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:35] [V] [TRT] Tactic: 8163473458334948789 Time: 0.07956
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:35] [V] [TRT] Tactic: -4212163711445252890 Time: 0.077328
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:35] [V] [TRT] Tactic: -3898373634979201110 Time: 0.07816
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:35] [V] [TRT] Tactic: -2409163523992614473 Time: 0.081996
[07/19/2022-13:01:35] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:35] [V] [TRT] Tactic: -1716393687483585322 Time: 0.075348
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: 3066127711859985668 Time: 0.072732
[07/19/2022-13:01:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3066127711859985668
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(18816,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(18816,1,1344,96) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(18816,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,1,8064,576) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(56448,196:2,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,196,14,1), Float(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,1,8064,576), Float(18816,1,1344,96) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(112896,196,14,1), Half(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(56448,196:2,14,1), Half(9408,196:2,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(18816,1,1344,96) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(18816,196,14,1) -> Half(9408,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Float(18816,1,1344,96) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(9408,196:2,14,1) -> Half(18816,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(18816,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(18816,1,1344,96) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(18816,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:35] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Half(9408,196:2,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Float(112896,1,8064,576) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(112896,196,14,1) -> Half(56448,196:2,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Float(112896,1,8064,576) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning Reformat:Half(56448,196:2,14,1) -> Half(112896,196,14,1) ***************
[07/19/2022-13:01:35] [V] [TRT] *************** Autotuning format combination: Float(112896,196,14,1) -> Float(28224,49,7,1) ***************
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:01:35] [V] [TRT] Tactic: -1 Time: 0.18058
[07/19/2022-13:01:35] [V] [TRT] Fastest Tactic: -1 Time: 0.18058
[07/19/2022-13:01:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:35] [V] [TRT] Tactic: 0 Time: 0.239468
[07/19/2022-13:01:35] [V] [TRT] Tactic: 1 Time: 0.244736
[07/19/2022-13:01:35] [V] [TRT] Tactic: 2 Time: 0.2383
[07/19/2022-13:01:37] [V] [TRT] Tactic: 5 Time: 104.048
[07/19/2022-13:01:37] [V] [TRT] Fastest Tactic: 2 Time: 0.2383
[07/19/2022-13:01:37] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:37] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:37] [V] [TRT] Tactic: 1062367460111450758 Time: 13.0233
[07/19/2022-13:01:38] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:01:38] [V] [TRT] Tactic: 1754984623894446479 Time: 14.2295
[07/19/2022-13:01:38] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:01:38] [V] [TRT] Tactic: 3611739942397549984 Time: 13.978
[07/19/2022-13:01:38] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:01:39] [V] [TRT] Tactic: 4337000649858996379 Time: 14.013
[07/19/2022-13:01:39] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:39] [V] [TRT] Tactic: 4501471010995462441 Time: 13.0511
[07/19/2022-13:01:39] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:39] [V] [TRT] Tactic: 5137655947464784826 Time: 12.8573
[07/19/2022-13:01:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:40] [V] [TRT] Tactic: 5288347012147084929 Time: 13.0192
[07/19/2022-13:01:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:40] [V] [TRT] Tactic: 6645123197870846056 Time: 13.0814
[07/19/2022-13:01:40] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:41] [V] [TRT] Tactic: 7144526460361122478 Time: 13.1259
[07/19/2022-13:01:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:01:41] [V] [TRT] Tactic: -9137461792520977713 Time: 13.936
[07/19/2022-13:01:41] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:42] [V] [TRT] Tactic: -8262349710178828730 Time: 13.1786
[07/19/2022-13:01:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:01:42] [V] [TRT] Tactic: -8133971918129952780 Time: 14.207
[07/19/2022-13:01:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:01:42] [V] [TRT] Tactic: -6092040395344634144 Time: 13.9502
[07/19/2022-13:01:42] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:43] [V] [TRT] Tactic: -4787320710726427159 Time: 13.2714
[07/19/2022-13:01:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:43] [V] [TRT] Tactic: -3456450830548107839 Time: 12.9625
[07/19/2022-13:01:43] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:44] [V] [TRT] Tactic: -1218658103698133241 Time: 13.0359
[07/19/2022-13:01:44] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:44] [V] [TRT] Tactic: -836875257600482091 Time: 12.9554
[07/19/2022-13:01:44] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:44] [V] [TRT] Tactic: -410470605513481746 Time: 12.9116
[07/19/2022-13:01:44] [V] [TRT] Fastest Tactic: 5137655947464784826 Time: 12.8573
[07/19/2022-13:01:44] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -1
[07/19/2022-13:01:44] [V] [TRT] *************** Autotuning format combination: Float(112896,1,8064,576) -> Float(28224,1,4032,576) ***************
[07/19/2022-13:01:44] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:44] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:44] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:44] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:44] [V] [TRT] *************** Autotuning format combination: Half(112896,196,14,1) -> Half(28224,49,7,1) ***************
[07/19/2022-13:01:44] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:44] [V] [TRT] Tactic: 0 Time: 0.192964
[07/19/2022-13:01:44] [V] [TRT] Tactic: 1 Time: 0.194112
[07/19/2022-13:01:45] [V] [TRT] Tactic: 2 Time: 23.0456
[07/19/2022-13:01:47] [V] [TRT] Tactic: 5 Time: 104.176
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.192964
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:47] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:47] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 0
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning format combination: Half(56448,196:2,14,1) -> Half(14112,49:2,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:47] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,49,7,1) -> Float(28224,1,4032,576) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.028244
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.032376
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 1002 Time: 0.028244
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,49,7,1) -> Half(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.603644
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.02698
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.02698
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,49,7,1) -> Half(14112,49:2,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.039188
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.019396
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.019396
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,1,4032,576) -> Float(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.037964
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.029616
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.029616
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,1,4032,576) -> Half(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.029112
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.030104
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 1002 Time: 0.029112
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Float(28224,1,4032,576) -> Half(14112,49:2,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.03458
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.035668
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 1002 Time: 0.03458
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(28224,49,7,1) -> Float(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.620952
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.02158
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.02158
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(28224,49,7,1) -> Float(28224,1,4032,576) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.026328
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.03266
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 1002 Time: 0.026328
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(28224,49,7,1) -> Half(14112,49:2,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.040828
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.019164
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.019164
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(14112,49:2,7,1) -> Float(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.037096
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.01612
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.01612
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(14112,49:2,7,1) -> Float(28224,1,4032,576) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.02648
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.03732
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 1002 Time: 0.02648
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning Reformat:Half(14112,49:2,7,1) -> Half(28224,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1002 Time: 0.047408
[07/19/2022-13:01:47] [V] [TRT] Tactic: 0 Time: 0.016136
[07/19/2022-13:01:47] [V] [TRT] Fastest Tactic: 0 Time: 0.016136
[07/19/2022-13:01:47] [V] [TRT] *************** Autotuning format combination: Float(28224,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:01:47] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:47] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:01:47] [V] [TRT] Tactic: 589823 Time: 0.343252
[07/19/2022-13:01:47] [V] [TRT] Tactic: 655359 Time: 0.197584
[07/19/2022-13:01:47] [V] [TRT] Tactic: 786431 Time: 0.170128
[07/19/2022-13:01:47] [V] [TRT] Tactic: 851967 Time: 0.205896
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1179647 Time: 0.129616
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1310719 Time: 0.418396
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1376255 Time: 0.38584
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1441791 Time: 0.211988
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1507327 Time: 0.220852
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1638399 Time: 0.197896
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1835007 Time: 0.149344
[07/19/2022-13:01:47] [V] [TRT] Tactic: 1900543 Time: 0.405464
[07/19/2022-13:01:47] [V] [TRT] Tactic: 2097151 Time: 0.132
[07/19/2022-13:01:47] [V] [TRT] Tactic: 2162687 Time: 0.418176
[07/19/2022-13:01:47] [V] [TRT] Tactic: 2293759 Time: 0.39596
[07/19/2022-13:01:47] [V] [TRT] Tactic: 2359295 Time: 0.223748
[07/19/2022-13:01:47] [V] [TRT] Tactic: 2686975 Time: 0.3863
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3080191 Time: 0.150776
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3342335 Time: 0.370092
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3407871 Time: 0.210808
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3538943 Time: 0.124868
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3670015 Time: 0.357696
[07/19/2022-13:01:47] [V] [TRT] Tactic: 3932159 Time: 0.360248
[07/19/2022-13:01:48] [V] [TRT] Tactic: 3997695 Time: 0.172156
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4063231 Time: 0.208128
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4194303 Time: 0.144984
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4259839 Time: 0.134852
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4325375 Time: 0.155836
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4521983 Time: 0.38796
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4587519 Time: 0.160028
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4653055 Time: 0.172976
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4915199 Time: 0.100588
[07/19/2022-13:01:48] [V] [TRT] Tactic: 4980735 Time: 0.224396
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5177343 Time: 0.130528
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5242879 Time: 0.20818
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5373951 Time: 0.131948
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5439487 Time: 0.144724
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5570559 Time: 0.148296
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5636095 Time: 0.20748
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5701631 Time: 0.386348
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5767167 Time: 0.215796
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5832703 Time: 0.210884
[07/19/2022-13:01:48] [V] [TRT] Tactic: 5898239 Time: 0.089856
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6029311 Time: 0.382608
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6225919 Time: 0.118432
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6291455 Time: 0.128992
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6422527 Time: 0.204364
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6750207 Time: 0.133532
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6815743 Time: 0.21316
[07/19/2022-13:01:48] [V] [TRT] Tactic: 6946815 Time: 0.169172
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7012351 Time: 0.129208
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7077887 Time: 0.123004
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7143423 Time: 0.213096
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7208959 Time: 0.214548
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7340031 Time: 0.091664
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7405567 Time: 0.1703
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7536639 Time: 0.215384
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7602175 Time: 0.166732
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7733247 Time: 0.127204
[07/19/2022-13:01:48] [V] [TRT] Tactic: 7798783 Time: 0.169852
[07/19/2022-13:01:48] [V] [TRT] Tactic: 8191999 Time: 0.153308
[07/19/2022-13:01:48] [V] [TRT] Tactic: 8257535 Time: 0.10058
[07/19/2022-13:01:48] [V] [TRT] Tactic: 8323071 Time: 0.143036
[07/19/2022-13:01:48] [V] [TRT] Tactic: 8650751 Time: 0.169152
[07/19/2022-13:01:49] [V] [TRT] Tactic: 8716287 Time: 0.120228
[07/19/2022-13:01:49] [V] [TRT] Tactic: 9109503 Time: 0.132456
[07/19/2022-13:01:49] [V] [TRT] Tactic: 9568255 Time: 0.100572
[07/19/2022-13:01:49] [V] [TRT] Tactic: 9895935 Time: 0.145392
[07/19/2022-13:01:49] [V] [TRT] Tactic: 10223615 Time: 0.385608
[07/19/2022-13:01:49] [V] [TRT] Tactic: 10354687 Time: 0.135712
[07/19/2022-13:01:49] [V] [TRT] Tactic: 10551295 Time: 0.238304
[07/19/2022-13:01:49] [V] [TRT] Tactic: 10747903 Time: 0.125812
[07/19/2022-13:01:49] [V] [TRT] Tactic: 10944511 Time: 0.22404
[07/19/2022-13:01:49] [V] [TRT] Fastest Tactic: 5898239 Time: 0.089856
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:49] [V] [TRT] Tactic: 0 Time: 0.138896
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1 Time: 0.11204
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2 Time: 0.288944
[07/19/2022-13:01:49] [V] [TRT] Tactic: 4 skipped. Scratch requested: 215359488, available: 16777216
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5 Time: 2.21291
[07/19/2022-13:01:49] [V] [TRT] Fastest Tactic: 1 Time: 0.11204
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:49] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1062367460111450758 Time: 0.110316
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1698681053543049347 Time: 0.127792
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:49] [V] [TRT] Tactic: 4501471010995462441 Time: 0.09296
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5137655947464784826 Time: 0.088508
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5288347012147084929 Time: 0.099848
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5326823351883942011 Time: 0.089664
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5500448035057547314 Time: 0.136348
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:49] [V] [TRT] Tactic: 6645123197870846056 Time: 0.093536
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:49] [V] [TRT] Tactic: 7144526460361122478 Time: 0.1309
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:49] [V] [TRT] Tactic: -8262349710178828730 Time: 0.102288
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:49] [V] [TRT] Tactic: -6576203419454146580 Time: 0.09722
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:49] [V] [TRT] Tactic: -4787320710726427159 Time: 0.133308
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:49] [V] [TRT] Tactic: -3456450830548107839 Time: 0.099724
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:49] [V] [TRT] Tactic: -1218658103698133241 Time: 0.144272
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:49] [V] [TRT] Tactic: -836875257600482091 Time: 0.138856
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:49] [V] [TRT] Tactic: -410470605513481746 Time: 0.09032
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:49] [V] [TRT] Tactic: -377491875521947884 Time: 0.099732
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:49] [V] [TRT] Tactic: -37215280111360163 Time: 0.087552
[07/19/2022-13:01:49] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.087552
[07/19/2022-13:01:49] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:01:49] [V] [TRT] *************** Autotuning format combination: Float(28224,1,4032,576) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:49] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:49] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:49] [V] [TRT] Tactic: 3886731678879822788 Time: 0.075616
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:49] [V] [TRT] Tactic: 6629944304117643200 Time: 0.07984
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:49] [V] [TRT] Tactic: -9153228964338181824 Time: 0.082276
[07/19/2022-13:01:49] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:49] [V] [TRT] Tactic: -7394439838318485025 Time: 0.075596
[07/19/2022-13:01:49] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.075596
[07/19/2022-13:01:49] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:01:49] [V] [TRT] *************** Autotuning format combination: Half(28224,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:49] [V] [TRT] Tactic: 0 Time: 0.130172
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1 Time: 0.107152
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2 Time: 0.205456
[07/19/2022-13:01:49] [V] [TRT] Tactic: 4 skipped. Scratch requested: 215359488, available: 16777216
[07/19/2022-13:01:49] [V] [TRT] Tactic: 5 Time: 2.05058
[07/19/2022-13:01:49] [V] [TRT] Fastest Tactic: 1 Time: 0.107152
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:49] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:49] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:49] [V] [TRT] *************** Autotuning format combination: Half(14112,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:49] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:49] [V] [TRT] *************** Autotuning format combination: Half(14112,49:2,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:49] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:01:49] [V] [TRT] Tactic: 589823 Time: 0.091948
[07/19/2022-13:01:49] [V] [TRT] Tactic: 655359 Time: 0.11728
[07/19/2022-13:01:49] [V] [TRT] Tactic: 786431 Time: 0.123092
[07/19/2022-13:01:49] [V] [TRT] Tactic: 851967 Time: 0.086244
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1179647 Time: 0.055872
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1310719 Time: 0.240572
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1376255 Time: 0.104328
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1441791 Time: 0.082484
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1507327 Time: 0.086204
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1638399 Time: 0.084356
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1835007 Time: 0.078904
[07/19/2022-13:01:49] [V] [TRT] Tactic: 1900543 Time: 0.12368
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2097151 Time: 0.071788
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2162687 Time: 0.117408
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2293759 Time: 0.104696
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2359295 Time: 0.092368
[07/19/2022-13:01:49] [V] [TRT] Tactic: 2686975 Time: 0.186716
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3080191 Time: 0.073228
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3342335 Time: 0.126624
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3407871 Time: 0.0688
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3538943 Time: 0.05896
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3670015 Time: 0.205884
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3932159 Time: 0.082712
[07/19/2022-13:01:50] [V] [TRT] Tactic: 3997695 Time: 0.104188
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4063231 Time: 0.075044
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4194303 Time: 0.06424
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4259839 Time: 0.072056
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4325375 Time: 0.096076
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4521983 Time: 0.113176
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4587519 Time: 0.080164
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4653055 Time: 0.075392
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4915199 Time: 0.065736
[07/19/2022-13:01:50] [V] [TRT] Tactic: 4980735 Time: 0.081644
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5177343 Time: 0.056496
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5242879 Time: 0.06218
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5373951 Time: 0.056396
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5439487 Time: 0.062756
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5570559 Time: 0.06512
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5636095 Time: 0.075192
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5701631 Time: 0.092476
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5767167 Time: 0.071428
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5832703 Time: 0.06694
[07/19/2022-13:01:50] [V] [TRT] Tactic: 5898239 Time: 0.051628
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6029311 Time: 0.094716
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6225919 Time: 0.052624
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6291455 Time: 0.05586
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6422527 Time: 0.070868
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6750207 Time: 0.062804
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6815743 Time: 0.06254
[07/19/2022-13:01:50] [V] [TRT] Tactic: 6946815 Time: 0.065676
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7012351 Time: 0.071636
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7077887 Time: 0.055728
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7143423 Time: 0.075684
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7208959 Time: 0.067384
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7340031 Time: 0.055224
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7405567 Time: 0.067932
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7536639 Time: 0.086152
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7602175 Time: 0.064872
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7733247 Time: 0.054192
[07/19/2022-13:01:50] [V] [TRT] Tactic: 7798783 Time: 0.124336
[07/19/2022-13:01:50] [V] [TRT] Tactic: 8191999 Time: 0.07196
[07/19/2022-13:01:50] [V] [TRT] Tactic: 8257535 Time: 0.066248
[07/19/2022-13:01:50] [V] [TRT] Tactic: 8323071 Time: 0.061828
[07/19/2022-13:01:50] [V] [TRT] Tactic: 8650751 Time: 0.065048
[07/19/2022-13:01:50] [V] [TRT] Tactic: 8716287 Time: 0.052292
[07/19/2022-13:01:50] [V] [TRT] Tactic: 9109503 Time: 0.0697
[07/19/2022-13:01:50] [V] [TRT] Tactic: 9568255 Time: 0.066748
[07/19/2022-13:01:50] [V] [TRT] Tactic: 9895935 Time: 0.06424
[07/19/2022-13:01:50] [V] [TRT] Tactic: 10223615 Time: 0.184124
[07/19/2022-13:01:50] [V] [TRT] Tactic: 10354687 Time: 0.067288
[07/19/2022-13:01:50] [V] [TRT] Tactic: 10551295 Time: 0.07176
[07/19/2022-13:01:50] [V] [TRT] Tactic: 10747903 Time: 0.051716
[07/19/2022-13:01:51] [V] [TRT] Tactic: 10944511 Time: 0.081684
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 5898239 Time: 0.051628
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CudnnConvolution)
[07/19/2022-13:01:51] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CublasConvolution)
[07/19/2022-13:01:51] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (CaskConvolution)
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:51] [V] [TRT] Tactic: 3066127711859985668 Time: 0.046072
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:51] [V] [TRT] Tactic: 3564772625446233998 Time: 0.054564
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:51] [V] [TRT] Tactic: 5319956359050645452 Time: 0.050572
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:51] [V] [TRT] Tactic: 7205456024582378848 Time: 0.045972
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:51] [V] [TRT] Tactic: 8163473458334948789 Time: 0.042652
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:51] [V] [TRT] Tactic: -4212163711445252890 Time: 0.040948
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:51] [V] [TRT] Tactic: -3898373634979201110 Time: 0.042632
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:51] [V] [TRT] Tactic: -2409163523992614473 Time: 0.044972
[07/19/2022-13:01:51] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:51] [V] [TRT] Tactic: -1716393687483585322 Time: 0.041044
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: -4212163711445252890 Time: 0.040948
[07/19/2022-13:01:51] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -4212163711445252890
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.011176
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.01132
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.011176
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.170704
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.009804
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.009804
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.016188
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007784
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007784
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.014224
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.010488
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.010488
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.01274
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.011184
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.011184
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.014576
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.012156
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.012156
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.175548
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007852
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007852
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.00952
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.011244
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.00952
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.014864
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007724
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007724
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.016128
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.0061
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.0061
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.009588
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.012668
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.009588
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.019388
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.006016
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.006016
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.011236
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.011308
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.011236
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.170912
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.009828
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.009828
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.016048
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007648
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007648
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.014164
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.01084
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.01084
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.012572
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.011044
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.011044
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.01446
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.012284
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.012284
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.175676
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007844
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007844
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.009568
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.011244
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.009568
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.015268
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.007752
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.007752
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.016212
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.006064
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.006064
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.009564
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.012816
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 1002 Time: 0.009564
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1002 Time: 0.019132
[07/19/2022-13:01:51] [V] [TRT] Tactic: 0 Time: 0.006048
[07/19/2022-13:01:51] [V] [TRT] Fastest Tactic: 0 Time: 0.006048
[07/19/2022-13:01:51] [V] [TRT] *************** Autotuning format combination: Float(7840,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:01:51] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:51] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:01:51] [V] [TRT] Tactic: 589823 Time: 0.34752
[07/19/2022-13:01:51] [V] [TRT] Tactic: 655359 Time: 0.29986
[07/19/2022-13:01:51] [V] [TRT] Tactic: 786431 Time: 0.460916
[07/19/2022-13:01:51] [V] [TRT] Tactic: 851967 Time: 0.437624
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1179647 Time: 0.377932
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1310719 Time: 0.579708
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1376255 Time: 0.353528
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1441791 Time: 0.472992
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1507327 Time: 0.418432
[07/19/2022-13:01:51] [V] [TRT] Tactic: 1638399 Time: 0.50828
[07/19/2022-13:01:52] [V] [TRT] Tactic: 1835007 Time: 0.437424
[07/19/2022-13:01:52] [V] [TRT] Tactic: 1900543 Time: 0.537956
[07/19/2022-13:01:52] [V] [TRT] Tactic: 2097151 Time: 0.3439
[07/19/2022-13:01:52] [V] [TRT] Tactic: 2162687 Time: 0.393628
[07/19/2022-13:01:52] [V] [TRT] Tactic: 2293759 Time: 0.348888
[07/19/2022-13:01:52] [V] [TRT] Tactic: 2359295 Time: 0.38286
[07/19/2022-13:01:52] [V] [TRT] Tactic: 2686975 Time: 0.361324
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3080191 Time: 0.356712
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3342335 Time: 0.549816
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3407871 Time: 0.347428
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3538943 Time: 0.356292
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3670015 Time: 0.344144
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3932159 Time: 0.379092
[07/19/2022-13:01:52] [V] [TRT] Tactic: 3997695 Time: 0.455876
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4063231 Time: 0.357068
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4194303 Time: 0.308608
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4259839 Time: 0.354204
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4325375 Time: 0.403544
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4521983 Time: 0.424684
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4587519 Time: 0.384628
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4653055 Time: 0.385292
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4915199 Time: 0.2951
[07/19/2022-13:01:52] [V] [TRT] Tactic: 4980735 Time: 0.41554
[07/19/2022-13:01:52] [V] [TRT] Tactic: 5177343 Time: 0.387272
[07/19/2022-13:01:52] [V] [TRT] Tactic: 5242879 Time: 0.301392
[07/19/2022-13:01:52] [V] [TRT] Tactic: 5373951 Time: 0.38686
[07/19/2022-13:01:52] [V] [TRT] Tactic: 5439487 Time: 0.3929
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5570559 Time: 0.282892
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5636095 Time: 0.35598
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5701631 Time: 0.377784
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5767167 Time: 0.465088
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5832703 Time: 0.34342
[07/19/2022-13:01:53] [V] [TRT] Tactic: 5898239 Time: 0.262056
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6029311 Time: 0.339868
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6225919 Time: 0.339632
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6291455 Time: 0.375892
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6422527 Time: 0.356864
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6750207 Time: 0.362896
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6815743 Time: 0.29992
[07/19/2022-13:01:53] [V] [TRT] Tactic: 6946815 Time: 0.443544
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7012351 Time: 0.342848
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7077887 Time: 0.354496
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7143423 Time: 0.445416
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7208959 Time: 0.3387
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7340031 Time: 0.263852
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7405567 Time: 0.357356
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7536639 Time: 0.307788
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7602175 Time: 0.417272
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7733247 Time: 0.281508
[07/19/2022-13:01:53] [V] [TRT] Tactic: 7798783 Time: 0.458084
[07/19/2022-13:01:53] [V] [TRT] Tactic: 8191999 Time: 0.475164
[07/19/2022-13:01:53] [V] [TRT] Tactic: 8257535 Time: 0.293876
[07/19/2022-13:01:53] [V] [TRT] Tactic: 8323071 Time: 0.3696
[07/19/2022-13:01:53] [V] [TRT] Tactic: 8650751 Time: 0.432592
[07/19/2022-13:01:53] [V] [TRT] Tactic: 8716287 Time: 0.372948
[07/19/2022-13:01:54] [V] [TRT] Tactic: 9109503 Time: 0.34392
[07/19/2022-13:01:54] [V] [TRT] Tactic: 9568255 Time: 0.295572
[07/19/2022-13:01:54] [V] [TRT] Tactic: 9895935 Time: 0.311852
[07/19/2022-13:01:54] [V] [TRT] Tactic: 10223615 Time: 0.360252
[07/19/2022-13:01:54] [V] [TRT] Tactic: 10354687 Time: 0.353412
[07/19/2022-13:01:54] [V] [TRT] Tactic: 10551295 Time: 0.367172
[07/19/2022-13:01:54] [V] [TRT] Tactic: 10747903 Time: 0.277912
[07/19/2022-13:01:54] [V] [TRT] Tactic: 10944511 Time: 0.414972
[07/19/2022-13:01:54] [V] [TRT] Fastest Tactic: 5898239 Time: 0.262056
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:54] [V] [TRT] Tactic: 0 Time: 0.258548
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1 Time: 0.230088
[07/19/2022-13:01:54] [V] [TRT] Tactic: 2 Time: 0.337804
[07/19/2022-13:01:54] [V] [TRT] Tactic: 4 skipped. Scratch requested: 355246080, available: 16777216
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5 skipped. Scratch requested: 23022080, available: 16777216
[07/19/2022-13:01:54] [V] [TRT] Fastest Tactic: 1 Time: 0.230088
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:54] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1062367460111450758 Time: 0.128108
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1698681053543049347 Time: 0.111932
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:01:54] [V] [TRT] Tactic: 4501471010995462441 Time: 0.101388
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5137655947464784826 Time: 0.101288
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5288347012147084929 Time: 0.102048
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5326823351883942011 Time: 0.100556
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5500448035057547314 Time: 0.111516
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:01:54] [V] [TRT] Tactic: 6645123197870846056 Time: 0.105096
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:01:54] [V] [TRT] Tactic: 7144526460361122478 Time: 0.123232
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:01:54] [V] [TRT] Tactic: -8262349710178828730 Time: 0.103444
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:01:54] [V] [TRT] Tactic: -6576203419454146580 Time: 0.114188
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:01:54] [V] [TRT] Tactic: -4787320710726427159 Time: 0.127548
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:01:54] [V] [TRT] Tactic: -3456450830548107839 Time: 0.119848
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:01:54] [V] [TRT] Tactic: -1218658103698133241 Time: 0.116844
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:01:54] [V] [TRT] Tactic: -836875257600482091 Time: 0.112348
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:01:54] [V] [TRT] Tactic: -410470605513481746 Time: 0.100064
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:01:54] [V] [TRT] Tactic: -377491875521947884 Time: 0.100264
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:01:54] [V] [TRT] Tactic: -37215280111360163 Time: 0.099664
[07/19/2022-13:01:54] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.099664
[07/19/2022-13:01:54] [V] [TRT] Setting workspace to 23022080enables more tactics for profiling
[07/19/2022-13:01:54] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:01:54] [V] [TRT] *************** Autotuning format combination: Float(7840,1,1120,160) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:54] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:54] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:01:54] [V] [TRT] Tactic: 3886731678879822788 Time: 0.101932
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:01:54] [V] [TRT] Tactic: 6629944304117643200 Time: 0.176428
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:01:54] [V] [TRT] Tactic: -9153228964338181824 Time: 0.178176
[07/19/2022-13:01:54] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:01:54] [V] [TRT] Tactic: -7394439838318485025 Time: 0.101496
[07/19/2022-13:01:54] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.101496
[07/19/2022-13:01:54] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:01:54] [V] [TRT] *************** Autotuning format combination: Half(7840,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:54] [V] [TRT] Tactic: 0 Time: 0.243412
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1 Time: 0.219736
[07/19/2022-13:01:54] [V] [TRT] Tactic: 2 Time: 0.301908
[07/19/2022-13:01:54] [V] [TRT] Tactic: 4 skipped. Scratch requested: 355246080, available: 16777216
[07/19/2022-13:01:54] [V] [TRT] Tactic: 5 skipped. Scratch requested: 23022080, available: 16777216
[07/19/2022-13:01:54] [V] [TRT] Fastest Tactic: 1 Time: 0.219736
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:54] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:54] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] Setting workspace to 23022080enables more tactics for profiling
[07/19/2022-13:01:54] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:01:54] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:54] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:54] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:01:54] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:01:54] [V] [TRT] Tactic: 589823 Time: 0.12444
[07/19/2022-13:01:54] [V] [TRT] Tactic: 655359 Time: 0.131536
[07/19/2022-13:01:54] [V] [TRT] Tactic: 786431 Time: 0.223624
[07/19/2022-13:01:54] [V] [TRT] Tactic: 851967 Time: 0.149608
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1179647 Time: 0.115824
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1310719 Time: 0.314456
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1376255 Time: 0.126412
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1441791 Time: 0.163712
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1507327 Time: 0.140952
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1638399 Time: 0.18756
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1835007 Time: 0.175608
[07/19/2022-13:01:54] [V] [TRT] Tactic: 1900543 Time: 0.176736
[07/19/2022-13:01:54] [V] [TRT] Tactic: 2162687 Time: 0.15256
[07/19/2022-13:01:54] [V] [TRT] Tactic: 2293759 Time: 0.123048
[07/19/2022-13:01:54] [V] [TRT] Tactic: 2359295 Time: 0.13808
[07/19/2022-13:01:55] [V] [TRT] Tactic: 2686975 Time: 0.216044
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3080191 Time: 0.112992
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3342335 Time: 0.178356
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3407871 Time: 0.111696
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3538943 Time: 0.107612
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3670015 Time: 0.150112
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3932159 Time: 0.114004
[07/19/2022-13:01:55] [V] [TRT] Tactic: 3997695 Time: 0.231096
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4063231 Time: 0.123176
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4194303 Time: 0.132076
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4325375 Time: 0.167248
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4521983 Time: 0.165424
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4587519 Time: 0.181436
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4653055 Time: 0.15066
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4915199 Time: 0.133956
[07/19/2022-13:01:55] [V] [TRT] Tactic: 4980735 Time: 0.178308
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5177343 Time: 0.116348
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5242879 Time: 0.103804
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5373951 Time: 0.113872
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5439487 Time: 0.135424
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5570559 Time: 0.10298
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5636095 Time: 0.12368
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5701631 Time: 0.116408
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5767167 Time: 0.140936
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5832703 Time: 0.107632
[07/19/2022-13:01:55] [V] [TRT] Tactic: 5898239 Time: 0.112708
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6029311 Time: 0.118676
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6225919 Time: 0.097372
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6291455 Time: 0.11566
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6422527 Time: 0.104364
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6750207 Time: 0.131968
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6815743 Time: 0.104472
[07/19/2022-13:01:55] [V] [TRT] Tactic: 6946815 Time: 0.143272
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7077887 Time: 0.101248
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7143423 Time: 0.149352
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7208959 Time: 0.108024
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7340031 Time: 0.113868
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7405567 Time: 0.120512
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7536639 Time: 0.11758
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7602175 Time: 0.143748
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7733247 Time: 0.099552
[07/19/2022-13:01:55] [V] [TRT] Tactic: 7798783 Time: 0.223552
[07/19/2022-13:01:55] [V] [TRT] Tactic: 8191999 Time: 0.155732
[07/19/2022-13:01:55] [V] [TRT] Tactic: 8257535 Time: 0.130632
[07/19/2022-13:01:55] [V] [TRT] Tactic: 8323071 Time: 0.135528
[07/19/2022-13:01:55] [V] [TRT] Tactic: 8650751 Time: 0.14404
[07/19/2022-13:01:56] [V] [TRT] Tactic: 8716287 Time: 0.094996
[07/19/2022-13:01:56] [V] [TRT] Tactic: 9568255 Time: 0.133904
[07/19/2022-13:01:56] [V] [TRT] Tactic: 9895935 Time: 0.13212
[07/19/2022-13:01:56] [V] [TRT] Tactic: 10223615 Time: 0.214768
[07/19/2022-13:01:56] [V] [TRT] Tactic: 10354687 Time: 0.167552
[07/19/2022-13:01:56] [V] [TRT] Tactic: 10551295 Time: 0.124652
[07/19/2022-13:01:56] [V] [TRT] Tactic: 10747903 Time: 0.095972
[07/19/2022-13:01:56] [V] [TRT] Tactic: 10944511 Time: 0.177716
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 8716287 Time: 0.094996
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:56] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CublasConvolution)
[07/19/2022-13:01:56] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:01:56] [V] [TRT] Tactic: 3066127711859985668 Time: 0.061584
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:01:56] [V] [TRT] Tactic: 3564772625446233998 Time: 0.068036
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:01:56] [V] [TRT] Tactic: 5319956359050645452 Time: 0.064284
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:01:56] [V] [TRT] Tactic: 7205456024582378848 Time: 0.05528
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:01:56] [V] [TRT] Tactic: 8163473458334948789 Time: 0.053436
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:01:56] [V] [TRT] Tactic: -4212163711445252890 Time: 0.050412
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:01:56] [V] [TRT] Tactic: -3898373634979201110 Time: 0.051748
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:01:56] [V] [TRT] Tactic: -2409163523992614473 Time: 0.054
[07/19/2022-13:01:56] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:01:56] [V] [TRT] Tactic: -1716393687483585322 Time: 0.05006
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: -1716393687483585322 Time: 0.05006
[07/19/2022-13:01:56] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -1716393687483585322
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.05064
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.074972
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 1002 Time: 0.05064
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 1.00315
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.046376
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.046376
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.072628
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.030656
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.030656
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.072768
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.048908
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.048908
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.046848
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.049076
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 1002 Time: 0.046848
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.056472
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.057796
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 1002 Time: 0.056472
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 1.03101
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.04078
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.04078
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.042276
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.053204
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 1002 Time: 0.042276
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.06356
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.029096
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.029096
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.0664
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.02788
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.02788
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.0436
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.060352
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 1002 Time: 0.0436
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1002 Time: 0.074976
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.025352
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: 0 Time: 0.025352
[07/19/2022-13:01:56] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:01:56] [V] [TRT] Tactic: -1 Time: 0.281088
[07/19/2022-13:01:56] [V] [TRT] Fastest Tactic: -1 Time: 0.281088
[07/19/2022-13:01:56] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:01:56] [V] [TRT] Tactic: 0 Time: 0.15528
[07/19/2022-13:01:56] [V] [TRT] Tactic: 1 Time: 0.157128
[07/19/2022-13:01:56] [V] [TRT] Tactic: 2 Time: 0.15516
[07/19/2022-13:01:59] [V] [TRT] Tactic: 4 Time: 149.958
[07/19/2022-13:02:01] [V] [TRT] Tactic: 5 Time: 173.858
[07/19/2022-13:02:03] [V] [TRT] Tactic: 6 Time: 81.9325
[07/19/2022-13:02:03] [V] [TRT] Fastest Tactic: 2 Time: 0.15516
[07/19/2022-13:02:03] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:03] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:02:03] [V] [TRT] Tactic: 1062367460111450758 Time: 22.0577
[07/19/2022-13:02:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v0 Tactic: 1754984623894446479
[07/19/2022-13:02:04] [V] [TRT] Tactic: 1754984623894446479 Time: 23.7618
[07/19/2022-13:02:04] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v0 Tactic: 3611739942397549984
[07/19/2022-13:02:05] [V] [TRT] Tactic: 3611739942397549984 Time: 23.419
[07/19/2022-13:02:05] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1 Tactic: 3827454225649558724
[07/19/2022-13:02:05] [V] [TRT] Tactic: 3827454225649558724 Time: 19.8272
[07/19/2022-13:02:05] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1 Tactic: 4337000649858996379
[07/19/2022-13:02:06] [V] [TRT] Tactic: 4337000649858996379 Time: 23.4164
[07/19/2022-13:02:06] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:02:07] [V] [TRT] Tactic: 4501471010995462441 Time: 21.9211
[07/19/2022-13:02:07] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:07] [V] [TRT] Tactic: 5137655947464784826 Time: 21.8214
[07/19/2022-13:02:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:02:08] [V] [TRT] Tactic: 5288347012147084929 Time: 21.9811
[07/19/2022-13:02:08] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1 Tactic: 5921334924264294896
[07/19/2022-13:02:08] [V] [TRT] Tactic: 5921334924264294896 Time: 19.9
[07/19/2022-13:02:09] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:02:09] [V] [TRT] Tactic: 6645123197870846056 Time: 21.8657
[07/19/2022-13:02:09] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:02:10] [V] [TRT] Tactic: 7144526460361122478 Time: 22.2417
[07/19/2022-13:02:10] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1 Tactic: 7852627285308570038
[07/19/2022-13:02:10] [V] [TRT] Tactic: 7852627285308570038 Time: 19.6258
[07/19/2022-13:02:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1 Tactic: -9137461792520977713
[07/19/2022-13:02:11] [V] [TRT] Tactic: -9137461792520977713 Time: 23.4464
[07/19/2022-13:02:11] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v0 Tactic: -8776506421218919509
[07/19/2022-13:02:11] [V] [TRT] Tactic: -8776506421218919509 Time: 19.9765
[07/19/2022-13:02:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:02:12] [V] [TRT] Tactic: -8262349710178828730 Time: 22.0188
[07/19/2022-13:02:12] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v0 Tactic: -8133971918129952780
[07/19/2022-13:02:13] [V] [TRT] Tactic: -8133971918129952780 Time: 23.6778
[07/19/2022-13:02:13] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1 Tactic: -6092040395344634144
[07/19/2022-13:02:14] [V] [TRT] Tactic: -6092040395344634144 Time: 23.5975
[07/19/2022-13:02:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:02:14] [V] [TRT] Tactic: -4787320710726427159 Time: 22.2605
[07/19/2022-13:02:14] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:15] [V] [TRT] Tactic: -3456450830548107839 Time: 21.8992
[07/19/2022-13:02:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v0 Tactic: -2318106587342035239
[07/19/2022-13:02:15] [V] [TRT] Tactic: -2318106587342035239 Time: 19.8046
[07/19/2022-13:02:15] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_mobile_relu_tile148t_nt_v0 Tactic: -1343271414618805657
[07/19/2022-13:02:16] [V] [TRT] Tactic: -1343271414618805657 Time: 19.9181
[07/19/2022-13:02:16] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:02:17] [V] [TRT] Tactic: -1218658103698133241 Time: 21.8731
[07/19/2022-13:02:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:02:17] [V] [TRT] Tactic: -836875257600482091 Time: 21.9649
[07/19/2022-13:02:17] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:02:18] [V] [TRT] Tactic: -410470605513481746 Time: 21.796
[07/19/2022-13:02:18] [V] [TRT] Fastest Tactic: 7852627285308570038 Time: 19.6258
[07/19/2022-13:02:18] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 2
[07/19/2022-13:02:18] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:18] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:18] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:18] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:18] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:18] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:18] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:18] [V] [TRT] Tactic: 0 Time: 0.124908
[07/19/2022-13:02:18] [V] [TRT] Tactic: 1 Time: 0.122444
[07/19/2022-13:02:18] [V] [TRT] Tactic: 2 Time: 0.152652
[07/19/2022-13:02:20] [V] [TRT] Tactic: 4 Time: 148.972
[07/19/2022-13:02:23] [V] [TRT] Tactic: 5 Time: 172.913
[07/19/2022-13:02:25] [V] [TRT] Tactic: 6 Time: 125.946
[07/19/2022-13:02:25] [V] [TRT] Fastest Tactic: 1 Time: 0.122444
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:25] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:25] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1), Float(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CudaDepthwiseConvolution)
[07/19/2022-13:02:25] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (FusedConvActConvolution)
[07/19/2022-13:02:25] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CudnnConvolution)
[07/19/2022-13:02:25] [V] [TRT] Tactic: 0 Time: 0.22256
[07/19/2022-13:02:25] [V] [TRT] Tactic: 1 Time: 0.179352
[07/19/2022-13:02:25] [V] [TRT] Tactic: 2 Time: 0.37414
[07/19/2022-13:02:25] [V] [TRT] Tactic: 4 skipped. Scratch requested: 358932480, available: 16777216
[07/19/2022-13:02:25] [V] [TRT] Tactic: 5 skipped. Scratch requested: 23022080, available: 16777216
[07/19/2022-13:02:25] [V] [TRT] Fastest Tactic: 1 Time: 0.179352
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CublasConvolution)
[07/19/2022-13:02:25] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:25] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CaskConvolution)
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:02:25] [V] [TRT] Tactic: 1062367460111450758 Time: 0.17556
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:25] [V] [TRT] Tactic: 1698681053543049347 Time: 0.209904
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:02:25] [V] [TRT] Tactic: 4501471010995462441 Time: 0.152076
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:25] [V] [TRT] Tactic: 5137655947464784826 Time: 0.145816
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:02:25] [V] [TRT] Tactic: 5288347012147084929 Time: 0.154636
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:25] [V] [TRT] Tactic: 5326823351883942011 Time: 0.147916
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:02:25] [V] [TRT] Tactic: 5500448035057547314 Time: 0.224056
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:02:25] [V] [TRT] Tactic: 6645123197870846056 Time: 0.152676
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:02:25] [V] [TRT] Tactic: 7144526460361122478 Time: 0.214204
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:02:25] [V] [TRT] Tactic: -8262349710178828730 Time: 0.159328
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:25] [V] [TRT] Tactic: -6576203419454146580 Time: 0.156348
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:02:25] [V] [TRT] Tactic: -4787320710726427159 Time: 0.220048
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:25] [V] [TRT] Tactic: -3456450830548107839 Time: 0.165156
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:02:25] [V] [TRT] Tactic: -1218658103698133241 Time: 0.238528
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:02:25] [V] [TRT] Tactic: -836875257600482091 Time: 0.22876
[07/19/2022-13:02:25] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:02:26] [V] [TRT] Tactic: -410470605513481746 Time: 0.147344
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:02:26] [V] [TRT] Tactic: -377491875521947884 Time: 0.1557
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:26] [V] [TRT] Tactic: -37215280111360163 Time: 0.139648
[07/19/2022-13:02:26] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.139648
[07/19/2022-13:02:26] [V] [TRT] Setting workspace to 23022080enables more tactics for profiling
[07/19/2022-13:02:26] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960), Float(7840,1,1120,160) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CudnnConvolution)
[07/19/2022-13:02:26] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CublasConvolution)
[07/19/2022-13:02:26] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:02:26] [V] [TRT] Tactic: 3886731678879822788 Time: 0.12242
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:02:26] [V] [TRT] Tactic: 6629944304117643200 Time: 0.154928
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:02:26] [V] [TRT] Tactic: -9153228964338181824 Time: 0.15574
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:02:26] [V] [TRT] Tactic: -7394439838318485025 Time: 0.12174
[07/19/2022-13:02:26] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.12174
[07/19/2022-13:02:26] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1), Half(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CudnnConvolution)
[07/19/2022-13:02:26] [V] [TRT] Tactic: 0 Time: 0.215064
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1 Time: 0.182236
[07/19/2022-13:02:26] [V] [TRT] Tactic: 2 Time: 0.36106
[07/19/2022-13:02:26] [V] [TRT] Tactic: 4 skipped. Scratch requested: 358932480, available: 16777216
[07/19/2022-13:02:26] [V] [TRT] Tactic: 5 skipped. Scratch requested: 23022080, available: 16777216
[07/19/2022-13:02:26] [V] [TRT] Fastest Tactic: 1 Time: 0.182236
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CublasConvolution)
[07/19/2022-13:02:26] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] Setting workspace to 23022080enables more tactics for profiling
[07/19/2022-13:02:26] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1), Half(3920,49:2,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (FusedConvActConvolution)
[07/19/2022-13:02:26] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CudnnConvolution)
[07/19/2022-13:02:26] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CublasConvolution)
[07/19/2022-13:02:26] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:02:26] [V] [TRT] Tactic: 3066127711859985668 Time: 0.081436
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:02:26] [V] [TRT] Tactic: 3564772625446233998 Time: 0.0954
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:02:26] [V] [TRT] Tactic: 5319956359050645452 Time: 0.08862
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:02:26] [V] [TRT] Tactic: 7205456024582378848 Time: 0.0795
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:02:26] [V] [TRT] Tactic: 8163473458334948789 Time: 0.06984
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:26] [V] [TRT] Tactic: -4212163711445252890 Time: 0.069372
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:02:26] [V] [TRT] Tactic: -3898373634979201110 Time: 0.071376
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:02:26] [V] [TRT] Tactic: -2409163523992614473 Time: 0.078372
[07/19/2022-13:02:26] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:26] [V] [TRT] Tactic: -1716393687483585322 Time: 0.069248
[07/19/2022-13:02:26] [V] [TRT] Fastest Tactic: -1716393687483585322 Time: 0.069248
[07/19/2022-13:02:26] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -1716393687483585322
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(7840,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(7840,1,1120,160) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(7840,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:26] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1), Float(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960), Float(7840,1,1120,160) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1), Half(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1), Half(3920,49:2,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(7840,1,1120,160) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(7840,49,7,1) -> Half(3920,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Float(7840,1,1120,160) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(3920,49:2,7,1) -> Half(7840,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(7840,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(7840,1,1120,160) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(7840,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(3920,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:26] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:26] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Float(47040,1,6720,960) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(47040,49,7,1) -> Half(23520,49:2,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Float(47040,1,6720,960) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning Reformat:Half(23520,49:2,7,1) -> Half(47040,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] *************** Autotuning format combination: Float(47040,49,7,1) -> Float(15680,49,7,1) ***************
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CudaDepthwiseConvolution)
[07/19/2022-13:02:26] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:26] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:02:26] [V] [TRT] Tactic: 589823 Time: 0.620436
[07/19/2022-13:02:26] [V] [TRT] Tactic: 655359 Time: 0.389948
[07/19/2022-13:02:26] [V] [TRT] Tactic: 786431 Time: 0.53338
[07/19/2022-13:02:26] [V] [TRT] Tactic: 851967 Time: 0.594084
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1179647 Time: 0.456724
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1310719 Time: 0.87246
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1376255 Time: 0.692908
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1441791 Time: 0.614812
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1507327 Time: 0.758688
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1638399 Time: 0.675468
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1835007 Time: 0.506676
[07/19/2022-13:02:26] [V] [TRT] Tactic: 1900543 Time: 0.739136
[07/19/2022-13:02:27] [V] [TRT] Tactic: 2097151 Time: 0.367824
[07/19/2022-13:02:27] [V] [TRT] Tactic: 2162687 Time: 0.712272
[07/19/2022-13:02:27] [V] [TRT] Tactic: 2293759 Time: 0.680404
[07/19/2022-13:02:27] [V] [TRT] Tactic: 2359295 Time: 0.404268
[07/19/2022-13:02:27] [V] [TRT] Tactic: 2686975 Time: 0.668952
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3080191 Time: 0.499144
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3342335 Time: 0.766628
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3407871 Time: 0.382304
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3538943 Time: 0.400752
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3670015 Time: 0.629664
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3932159 Time: 0.662184
[07/19/2022-13:02:27] [V] [TRT] Tactic: 3997695 Time: 0.577776
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4063231 Time: 0.58862
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4194303 Time: 0.304476
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4259839 Time: 0.382076
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4325375 Time: 0.487908
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4521983 Time: 0.673928
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4587519 Time: 0.451868
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4653055 Time: 0.473988
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4915199 Time: 0.320468
[07/19/2022-13:02:27] [V] [TRT] Tactic: 4980735 Time: 0.477564
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5177343 Time: 0.46144
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5242879 Time: 0.37192
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5373951 Time: 0.47046
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5439487 Time: 0.486248
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5570559 Time: 0.273396
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5636095 Time: 0.59004
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5701631 Time: 0.674264
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5767167 Time: 0.736588
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5832703 Time: 0.3797
[07/19/2022-13:02:28] [V] [TRT] Tactic: 5898239 Time: 0.287352
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6029311 Time: 0.667156
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6225919 Time: 0.384636
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6291455 Time: 0.457108
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6422527 Time: 0.37368
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6750207 Time: 0.399656
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6815743 Time: 0.376524
[07/19/2022-13:02:28] [V] [TRT] Tactic: 6946815 Time: 0.551988
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7012351 Time: 0.368388
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7077887 Time: 0.39662
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7143423 Time: 0.723712
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7208959 Time: 0.382132
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7340031 Time: 0.29446
[07/19/2022-13:02:28] [V] [TRT] Tactic: 7405567 Time: 0.40222
[07/19/2022-13:02:29] [V] [TRT] Tactic: 7536639 Time: 0.400708
[07/19/2022-13:02:29] [V] [TRT] Tactic: 7602175 Time: 0.53396
[07/19/2022-13:02:29] [V] [TRT] Tactic: 7733247 Time: 0.406004
[07/19/2022-13:02:29] [V] [TRT] Tactic: 7798783 Time: 0.534404
[07/19/2022-13:02:29] [V] [TRT] Tactic: 8191999 Time: 0.509844
[07/19/2022-13:02:29] [V] [TRT] Tactic: 8257535 Time: 0.32516
[07/19/2022-13:02:29] [V] [TRT] Tactic: 8323071 Time: 0.47424
[07/19/2022-13:02:29] [V] [TRT] Tactic: 8650751 Time: 0.54004
[07/19/2022-13:02:29] [V] [TRT] Tactic: 8716287 Time: 0.394176
[07/19/2022-13:02:29] [V] [TRT] Tactic: 9109503 Time: 0.375592
[07/19/2022-13:02:29] [V] [TRT] Tactic: 9568255 Time: 0.3207
[07/19/2022-13:02:29] [V] [TRT] Tactic: 9895935 Time: 0.30422
[07/19/2022-13:02:29] [V] [TRT] Tactic: 10223615 Time: 0.667268
[07/19/2022-13:02:29] [V] [TRT] Tactic: 10354687 Time: 0.461064
[07/19/2022-13:02:29] [V] [TRT] Tactic: 10551295 Time: 0.415364
[07/19/2022-13:02:29] [V] [TRT] Tactic: 10747903 Time: 0.394636
[07/19/2022-13:02:29] [V] [TRT] Tactic: 10944511 Time: 0.474656
[07/19/2022-13:02:29] [V] [TRT] Fastest Tactic: 5570559 Time: 0.273396
[07/19/2022-13:02:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CudnnConvolution)
[07/19/2022-13:02:29] [V] [TRT] Tactic: 0 Time: 0.424308
[07/19/2022-13:02:29] [V] [TRT] Tactic: 1 Time: 0.315708
[07/19/2022-13:02:29] [V] [TRT] Tactic: 2 Time: 0.442216
[07/19/2022-13:02:29] [V] [TRT] Tactic: 4 skipped. Scratch requested: 713441280, available: 16777216
[07/19/2022-13:02:29] [V] [TRT] Tactic: 5 skipped. Scratch requested: 44216320, available: 16777216
[07/19/2022-13:02:29] [V] [TRT] Fastest Tactic: 1 Time: 0.315708
[07/19/2022-13:02:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CublasConvolution)
[07/19/2022-13:02:29] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:29] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CaskConvolution)
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:02:29] [V] [TRT] Tactic: 1062367460111450758 Time: 0.225004
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:29] [V] [TRT] Tactic: 1698681053543049347 Time: 0.213456
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:02:29] [V] [TRT] Tactic: 4501471010995462441 Time: 0.23238
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:29] [V] [TRT] Tactic: 5137655947464784826 Time: 0.192
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:02:29] [V] [TRT] Tactic: 5288347012147084929 Time: 0.228356
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:29] [V] [TRT] Tactic: 5326823351883942011 Time: 0.22506
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:02:29] [V] [TRT] Tactic: 5500448035057547314 Time: 0.24432
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:02:29] [V] [TRT] Tactic: 6645123197870846056 Time: 0.199544
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:02:29] [V] [TRT] Tactic: 7144526460361122478 Time: 0.222632
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:02:29] [V] [TRT] Tactic: -8262349710178828730 Time: 0.233308
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:29] [V] [TRT] Tactic: -6576203419454146580 Time: 0.200012
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:02:29] [V] [TRT] Tactic: -4787320710726427159 Time: 0.232956
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:29] [V] [TRT] Tactic: -3456450830548107839 Time: 0.209988
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:02:29] [V] [TRT] Tactic: -1218658103698133241 Time: 0.26592
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:02:29] [V] [TRT] Tactic: -836875257600482091 Time: 0.258932
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:02:29] [V] [TRT] Tactic: -410470605513481746 Time: 0.22778
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:02:29] [V] [TRT] Tactic: -377491875521947884 Time: 0.226456
[07/19/2022-13:02:29] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:30] [V] [TRT] Tactic: -37215280111360163 Time: 0.18806
[07/19/2022-13:02:30] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.18806
[07/19/2022-13:02:30] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:02:30] [V] [TRT] *************** Autotuning format combination: Float(47040,1,6720,960) -> Float(15680,1,2240,320) ***************
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CudnnConvolution)
[07/19/2022-13:02:30] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CublasConvolution)
[07/19/2022-13:02:30] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CaskConvolution)
[07/19/2022-13:02:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3886731678879822788 Time: 0.20628
[07/19/2022-13:02:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:02:30] [V] [TRT] Tactic: 6629944304117643200 Time: 0.244508
[07/19/2022-13:02:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:02:30] [V] [TRT] Tactic: -9153228964338181824 Time: 0.247184
[07/19/2022-13:02:30] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:02:30] [V] [TRT] Tactic: -7394439838318485025 Time: 0.208064
[07/19/2022-13:02:30] [V] [TRT] Fastest Tactic: 3886731678879822788 Time: 0.20628
[07/19/2022-13:02:30] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 3886731678879822788
[07/19/2022-13:02:30] [V] [TRT] *************** Autotuning format combination: Half(47040,49,7,1) -> Half(15680,49,7,1) ***************
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CudnnConvolution)
[07/19/2022-13:02:30] [V] [TRT] Tactic: 0 Time: 0.395448
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1 Time: 0.316496
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2 Time: 0.422564
[07/19/2022-13:02:30] [V] [TRT] Tactic: 4 skipped. Scratch requested: 713441280, available: 16777216
[07/19/2022-13:02:30] [V] [TRT] Tactic: 5 skipped. Scratch requested: 44216320, available: 16777216
[07/19/2022-13:02:30] [V] [TRT] Fastest Tactic: 1 Time: 0.316496
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CublasConvolution)
[07/19/2022-13:02:30] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CaskConvolution)
[07/19/2022-13:02:30] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:30] [V] [TRT] Setting workspace to 44216320enables more tactics for profiling
[07/19/2022-13:02:30] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:02:30] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1) -> Half(15680,49,7,1) ***************
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CaskConvolution)
[07/19/2022-13:02:30] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:30] [V] [TRT] *************** Autotuning format combination: Half(23520,49:2,7,1) -> Half(7840,49:2,7,1) ***************
[07/19/2022-13:02:30] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (FusedConvActConvolution)
[07/19/2022-13:02:30] [V] [TRT] Tactic: 589823 Time: 0.321744
[07/19/2022-13:02:30] [V] [TRT] Tactic: 655359 Time: 0.369104
[07/19/2022-13:02:30] [V] [TRT] Tactic: 786431 Time: 0.409772
[07/19/2022-13:02:30] [V] [TRT] Tactic: 851967 Time: 0.31436
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1179647 Time: 0.207792
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1310719 Time: 0.59138
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1376255 Time: 0.3434
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1441791 Time: 0.262152
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1507327 Time: 0.389936
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1638399 Time: 0.347876
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1835007 Time: 0.277788
[07/19/2022-13:02:30] [V] [TRT] Tactic: 1900543 Time: 0.378552
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2097151 Time: 0.243012
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2162687 Time: 0.357828
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2293759 Time: 0.33636
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2359295 Time: 0.21182
[07/19/2022-13:02:30] [V] [TRT] Tactic: 2686975 Time: 0.528524
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3080191 Time: 0.33794
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3342335 Time: 0.391924
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3407871 Time: 0.185768
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3538943 Time: 0.193596
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3670015 Time: 0.696528
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3932159 Time: 0.308032
[07/19/2022-13:02:30] [V] [TRT] Tactic: 3997695 Time: 0.377188
[07/19/2022-13:02:30] [V] [TRT] Tactic: 4063231 Time: 0.29712
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4194303 Time: 0.248536
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4259839 Time: 0.254336
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4325375 Time: 0.288108
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4521983 Time: 0.339012
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4587519 Time: 0.263212
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4653055 Time: 0.24054
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4915199 Time: 0.206376
[07/19/2022-13:02:31] [V] [TRT] Tactic: 4980735 Time: 0.340224
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5177343 Time: 0.209648
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5242879 Time: 0.17742
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5373951 Time: 0.212528
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5439487 Time: 0.255752
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5570559 Time: 0.199636
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5636095 Time: 0.298276
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5701631 Time: 0.32682
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5767167 Time: 0.362248
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5832703 Time: 0.180312
[07/19/2022-13:02:31] [V] [TRT] Tactic: 5898239 Time: 0.179564
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6029311 Time: 0.344008
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6225919 Time: 0.184064
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6291455 Time: 0.207736
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6422527 Time: 0.192128
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6750207 Time: 0.216396
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6815743 Time: 0.177528
[07/19/2022-13:02:31] [V] [TRT] Tactic: 6946815 Time: 0.252828
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7012351 Time: 0.2427
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7077887 Time: 0.187676
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7143423 Time: 0.35962
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7208959 Time: 0.18082
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7340031 Time: 0.188804
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7405567 Time: 0.202544
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7536639 Time: 0.32312
[07/19/2022-13:02:31] [V] [TRT] Tactic: 7602175 Time: 0.24692
[07/19/2022-13:02:32] [V] [TRT] Tactic: 7733247 Time: 0.211384
[07/19/2022-13:02:32] [V] [TRT] Tactic: 7798783 Time: 0.411704
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8191999 Time: 0.239372
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8257535 Time: 0.207004
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8323071 Time: 0.248508
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8650751 Time: 0.2493
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8716287 Time: 0.188048
[07/19/2022-13:02:32] [V] [TRT] Tactic: 9109503 Time: 0.240232
[07/19/2022-13:02:32] [V] [TRT] Tactic: 9568255 Time: 0.2065
[07/19/2022-13:02:32] [V] [TRT] Tactic: 9895935 Time: 0.248156
[07/19/2022-13:02:32] [V] [TRT] Tactic: 10223615 Time: 0.530988
[07/19/2022-13:02:32] [V] [TRT] Tactic: 10354687 Time: 0.266416
[07/19/2022-13:02:32] [V] [TRT] Tactic: 10551295 Time: 0.208308
[07/19/2022-13:02:32] [V] [TRT] Tactic: 10747903 Time: 0.194216
[07/19/2022-13:02:32] [V] [TRT] Tactic: 10944511 Time: 0.340428
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 5242879 Time: 0.17742
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CudnnConvolution)
[07/19/2022-13:02:32] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CublasConvolution)
[07/19/2022-13:02:32] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (CaskConvolution)
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:02:32] [V] [TRT] Tactic: 3066127711859985668 Time: 0.109576
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:02:32] [V] [TRT] Tactic: 3564772625446233998 Time: 0.124436
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5319956359050645452 Time: 0.117944
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:02:32] [V] [TRT] Tactic: 7205456024582378848 Time: 0.105096
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:02:32] [V] [TRT] Tactic: 8163473458334948789 Time: 0.0973
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:32] [V] [TRT] Tactic: -4212163711445252890 Time: 0.116196
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:02:32] [V] [TRT] Tactic: -3898373634979201110 Time: 0.1177
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:02:32] [V] [TRT] Tactic: -2409163523992614473 Time: 0.10228
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:32] [V] [TRT] Tactic: -1716393687483585322 Time: 0.114628
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.0973
[07/19/2022-13:02:32] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 8163473458334948789
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,49,7,1) -> Float(15680,1,2240,320) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.01794
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.01966
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 1002 Time: 0.01794
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,49,7,1) -> Half(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.3374
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.016532
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.016532
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,49,7,1) -> Half(7840,49:2,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.024536
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.011576
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.011576
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,1,2240,320) -> Float(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.024192
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.017676
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.017676
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,1,2240,320) -> Half(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.0182
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.01776
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.01776
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Float(15680,1,2240,320) -> Half(7840,49:2,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.021916
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.02102
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.02102
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(15680,49,7,1) -> Float(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.347256
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.013172
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.013172
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(15680,49,7,1) -> Float(15680,1,2240,320) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.016268
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.019476
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 1002 Time: 0.016268
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(15680,49,7,1) -> Half(7840,49:2,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.024552
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.011332
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.011332
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(7840,49:2,7,1) -> Float(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.023572
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.010732
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.010732
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(7840,49:2,7,1) -> Float(15680,1,2240,320) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.016136
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.022444
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 1002 Time: 0.016136
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning Reformat:Half(7840,49:2,7,1) -> Half(15680,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1002 Time: 0.030692
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.010556
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 0 Time: 0.010556
[07/19/2022-13:02:32] [V] [TRT] *************** Autotuning format combination: Float(15680,49,7,1) -> Float(62720,49,7,1) ***************
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CudaDepthwiseConvolution)
[07/19/2022-13:02:32] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:02:32] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:32] [V] [TRT] Tactic: 0 Time: 0.545168
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1 Time: 0.463996
[07/19/2022-13:02:32] [V] [TRT] Tactic: 2 Time: 0.602308
[07/19/2022-13:02:32] [V] [TRT] Tactic: 4 skipped. Scratch requested: 946831360, available: 16777216
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5 skipped. Scratch requested: 58752000, available: 16777216
[07/19/2022-13:02:32] [V] [TRT] Fastest Tactic: 1 Time: 0.463996
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CublasConvolution)
[07/19/2022-13:02:32] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:32] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1062367460111450758 Time: 0.298964
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:32] [V] [TRT] Tactic: 1698681053543049347 Time: 0.290036
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:02:32] [V] [TRT] Tactic: 4501471010995462441 Time: 0.254528
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5137655947464784826 Time: 0.230228
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5288347012147084929 Time: 0.253268
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5326823351883942011 Time: 0.243428
[07/19/2022-13:02:32] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:02:32] [V] [TRT] Tactic: 5500448035057547314 Time: 0.281108
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:02:33] [V] [TRT] Tactic: 6645123197870846056 Time: 0.234916
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:02:33] [V] [TRT] Tactic: 7144526460361122478 Time: 0.315068
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:02:33] [V] [TRT] Tactic: -8262349710178828730 Time: 0.25828
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:33] [V] [TRT] Tactic: -6576203419454146580 Time: 0.265964
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:02:33] [V] [TRT] Tactic: -4787320710726427159 Time: 0.326088
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:33] [V] [TRT] Tactic: -3456450830548107839 Time: 0.275932
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:02:33] [V] [TRT] Tactic: -1218658103698133241 Time: 0.304416
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:02:33] [V] [TRT] Tactic: -836875257600482091 Time: 0.29538
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:02:33] [V] [TRT] Tactic: -410470605513481746 Time: 0.241872
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:02:33] [V] [TRT] Tactic: -377491875521947884 Time: 0.247664
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:33] [V] [TRT] Tactic: -37215280111360163 Time: 0.22552
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -37215280111360163 Time: 0.22552
[07/19/2022-13:02:33] [V] [TRT] Setting workspace to 58752000enables more tactics for profiling
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -37215280111360163
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Float(15680,1,2240,320) -> Float(62720,1,8960,1280) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:33] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CublasConvolution)
[07/19/2022-13:02:33] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:02:33] [V] [TRT] Tactic: 3886731678879822788 Time: 0.222452
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:02:33] [V] [TRT] Tactic: 6629944304117643200 Time: 0.343716
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:02:33] [V] [TRT] Tactic: -9153228964338181824 Time: 0.35386
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:02:33] [V] [TRT] Tactic: -7394439838318485025 Time: 0.220836
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -7394439838318485025 Time: 0.220836
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -7394439838318485025
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Half(15680,49,7,1) -> Half(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.52118
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1 Time: 0.46058
[07/19/2022-13:02:33] [V] [TRT] Tactic: 2 Time: 0.568628
[07/19/2022-13:02:33] [V] [TRT] Tactic: 4 skipped. Scratch requested: 946831360, available: 16777216
[07/19/2022-13:02:33] [V] [TRT] Tactic: 5 skipped. Scratch requested: 58752000, available: 16777216
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 1 Time: 0.46058
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CublasConvolution)
[07/19/2022-13:02:33] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:33] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] Setting workspace to 58752000enables more tactics for profiling
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnConvolution Tactic: 1
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Half(7840,49:2,7,1) -> Half(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:33] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Half(7840,49:2,7,1) -> Half(31360,49:2,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (FusedConvActConvolution)
[07/19/2022-13:02:33] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CudnnConvolution)
[07/19/2022-13:02:33] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CublasConvolution)
[07/19/2022-13:02:33] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 (CaskConvolution)
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:02:33] [V] [TRT] Tactic: 3066127711859985668 Time: 0.139312
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:02:33] [V] [TRT] Tactic: 3564772625446233998 Time: 0.158588
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:02:33] [V] [TRT] Tactic: 5319956359050645452 Time: 0.148048
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:02:33] [V] [TRT] Tactic: 7205456024582378848 Time: 0.119708
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:02:33] [V] [TRT] Tactic: 8163473458334948789 Time: 0.114848
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:33] [V] [TRT] Tactic: -4212163711445252890 Time: 0.11218
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:02:33] [V] [TRT] Tactic: -3898373634979201110 Time: 0.114268
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:02:33] [V] [TRT] Tactic: -2409163523992614473 Time: 0.116948
[07/19/2022-13:02:33] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:33] [V] [TRT] Tactic: -1716393687483585322 Time: 0.112472
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -4212163711445252890 Time: 0.11218
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: -4212163711445252890
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(62720,49,7,1) -> Half(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 1.33635
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.064992
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.064992
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(62720,49,7,1) -> Half(31360,49:2,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.10762
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.039848
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.039848
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(62720,1,8960,1280) -> Float(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.091768
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.06354
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.06354
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(62720,1,8960,1280) -> Half(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.060708
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.064836
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.060708
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(62720,1,8960,1280) -> Half(31360,49:2,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.091352
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.075364
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.075364
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(62720,49,7,1) -> Float(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 1.37257
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.06096
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.06096
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(62720,49,7,1) -> Half(31360,49:2,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.085372
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.038484
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.038484
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(31360,49:2,7,1) -> Float(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.08716
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.037544
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.037544
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(31360,49:2,7,1) -> Half(62720,49,7,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.100768
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.03324
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.03324
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Float(62720,49,7,1) -> Float(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (TiledPooling)
[07/19/2022-13:02:33] [V] [TRT] TiledPooling has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (CudnnPooling)
[07/19/2022-13:02:33] [V] [TRT] Tactic: -1 Time: 0.025428
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -1 Time: 0.025428
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnPooling Tactic: -1
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Half(62720,49,7,1) -> Half(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (TiledPooling)
[07/19/2022-13:02:33] [V] [TRT] TiledPooling has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (CudnnPooling)
[07/19/2022-13:02:33] [V] [TRT] Tactic: -1 Time: 0.018624
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -1 Time: 0.018624
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnPooling Tactic: -1
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Half(31360,49:2,7,1) -> Half(640,1:2,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (TiledPooling)
[07/19/2022-13:02:33] [V] [TRT] TiledPooling has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/average_pooling2d_4/AvgPool (CudaPooling)
[07/19/2022-13:02:33] [V] [TRT] Tactic: -3 Time: 0.013144
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: -3 Time: 0.013144
[07/19/2022-13:02:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaPooling Tactic: -3
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1,1) -> Float(1280,1,1280,1280) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.004592
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004344
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004344
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1,1) -> Half(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.005052
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004396
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004396
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1,1) -> Half(640,1:2,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.024468
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.0028
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.0028
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1280,1280) -> Float(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.004888
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004364
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004364
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1280,1280) -> Half(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.004452
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004284
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004284
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Float(1280,1,1280,1280) -> Half(640,1:2,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.024332
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004396
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004396
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(1280,1,1,1) -> Float(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.006056
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004388
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004388
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(1280,1,1,1) -> Float(1280,1,1280,1280) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.004504
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.00442
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.00442
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(1280,1,1,1) -> Half(640,1:2,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.026304
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.002752
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.002752
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(640,1:2,1,1) -> Float(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.025784
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.002704
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.002704
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(640,1:2,1,1) -> Float(1280,1,1280,1280) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.014464
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.004388
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.004388
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning Reformat:Half(640,1:2,1,1) -> Half(1280,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:33] [V] [TRT] Tactic: 1002 Time: 0.025256
[07/19/2022-13:02:33] [V] [TRT] Tactic: 0 Time: 0.002752
[07/19/2022-13:02:33] [V] [TRT] Fastest Tactic: 0 Time: 0.002752
[07/19/2022-13:02:33] [V] [TRT] *************** Autotuning format combination: Float(1280,1,1,1) -> Float(4,1,1,1) ***************
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CudaDepthwiseConvolution)
[07/19/2022-13:02:33] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:33] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (FusedConvActConvolution)
[07/19/2022-13:02:33] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CudnnConvolution)
[07/19/2022-13:02:34] [V] [TRT] Tactic: 0 Time: 0.122036
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1 Time: 0.097528
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2 Time: 0.22684
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4 skipped. Scratch requested: 17715200, available: 16777216
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5 Time: 0.50948
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 1 Time: 0.097528
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CublasConvolution)
[07/19/2022-13:02:34] [V] [TRT] Tactic: 0 Time: 0.009292
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1 Time: 0.012572
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 0 Time: 0.009292
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CaskConvolution)
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1 Tactic: 1062367460111450758
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1062367460111450758 Time: 0.138044
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1698681053543049347 Time: 0.097432
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1 Tactic: 4501471010995462441
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4501471010995462441 Time: 0.164388
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5137655947464784826 Time: 0.108276
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v0 Tactic: 5288347012147084929
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5288347012147084929 Time: 0.159496
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5326823351883942011 Time: 0.158704
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v0 Tactic: 5500448035057547314
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5500448035057547314 Time: 0.126008
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1 Tactic: 6645123197870846056
[07/19/2022-13:02:34] [V] [TRT] Tactic: 6645123197870846056 Time: 0.118236
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v0 Tactic: 7144526460361122478
[07/19/2022-13:02:34] [V] [TRT] Tactic: 7144526460361122478 Time: 0.10276
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v0 Tactic: -8262349710178828730
[07/19/2022-13:02:34] [V] [TRT] Tactic: -8262349710178828730 Time: 0.16298
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:34] [V] [TRT] Tactic: -6576203419454146580 Time: 0.113344
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v0 Tactic: -4787320710726427159
[07/19/2022-13:02:34] [V] [TRT] Tactic: -4787320710726427159 Time: 0.110876
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:34] [V] [TRT] Tactic: -3456450830548107839 Time: 0.118216
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v0 Tactic: -1218658103698133241
[07/19/2022-13:02:34] [V] [TRT] Tactic: -1218658103698133241 Time: 0.13856
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v0 Tactic: -836875257600482091
[07/19/2022-13:02:34] [V] [TRT] Tactic: -836875257600482091 Time: 0.129748
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1 Tactic: -410470605513481746
[07/19/2022-13:02:34] [V] [TRT] Tactic: -410470605513481746 Time: 0.15786
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v0 Tactic: -377491875521947884
[07/19/2022-13:02:34] [V] [TRT] Tactic: -377491875521947884 Time: 0.157004
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:34] [V] [TRT] Tactic: -37215280111360163 Time: 0.10522
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 1698681053543049347 Time: 0.097432
[07/19/2022-13:02:34] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CublasConvolution Tactic: 0
[07/19/2022-13:02:34] [V] [TRT] *************** Autotuning format combination: Float(1280,1,1280,1280) -> Float(4,1,4,4) ***************
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CudnnConvolution)
[07/19/2022-13:02:34] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CublasConvolution)
[07/19/2022-13:02:34] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CaskConvolution)
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 3886731678879822788
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3886731678879822788 Time: 0.0819
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_interior_nhwc_tn_v1 Tactic: 6629944304117643200
[07/19/2022-13:02:34] [V] [TRT] Tactic: 6629944304117643200 Time: 0.046144
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x32_sliced1x4_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -9153228964338181824
[07/19/2022-13:02:34] [V] [TRT] Tactic: -9153228964338181824 Time: 0.046548
[07/19/2022-13:02:34] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_scudnn_128x64_sliced1x2_ldg4_relu_exp_small_nhwc_tn_v1 Tactic: -7394439838318485025
[07/19/2022-13:02:34] [V] [TRT] Tactic: -7394439838318485025 Time: 0.085264
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 6629944304117643200 Time: 0.046144
[07/19/2022-13:02:34] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 6629944304117643200
[07/19/2022-13:02:34] [V] [TRT] *************** Autotuning format combination: Half(1280,1,1,1) -> Half(4,1,1,1) ***************
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CudnnConvolution)
[07/19/2022-13:02:34] [V] [TRT] Tactic: 0 Time: 0.124116
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1 Time: 0.11378
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2 Time: 0.230288
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4 skipped. Scratch requested: 17715200, available: 16777216
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5 Time: 0.518892
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 1 Time: 0.11378
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CublasConvolution)
[07/19/2022-13:02:34] [V] [TRT] Tactic: 0 Time: 0.009232
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1 Time: 0.013696
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4 Time: 0.009512
[07/19/2022-13:02:34] [V] [TRT] Tactic: 5 Time: 0.022448
[07/19/2022-13:02:34] [V] [TRT] Fastest Tactic: 0 Time: 0.009232
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CaskConvolution)
[07/19/2022-13:02:34] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:34] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CublasConvolution Tactic: 0
[07/19/2022-13:02:34] [V] [TRT] *************** Autotuning format combination: Half(640,1:2,1,1) -> Half(4,1,1,1) ***************
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CaskConvolution)
[07/19/2022-13:02:34] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:34] [V] [TRT] *************** Autotuning format combination: Half(640,1:2,1,1) -> Half(2,1:2,1,1) ***************
[07/19/2022-13:02:34] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (FusedConvActConvolution)
[07/19/2022-13:02:34] [V] [TRT] Tactic: 589823 Time: 0.164864
[07/19/2022-13:02:34] [V] [TRT] Tactic: 655359 Time: 0.204732
[07/19/2022-13:02:34] [V] [TRT] Tactic: 786431 Time: 0.100024
[07/19/2022-13:02:34] [V] [TRT] Tactic: 851967 Time: 0.061748
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1179647 Time: 0.03092
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1310719 Time: 0.46668
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1376255 Time: 0.181952
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1441791 Time: 0.044928
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1507327 Time: 0.11424
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1638399 Time: 0.053972
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1835007 Time: 0.09132
[07/19/2022-13:02:34] [V] [TRT] Tactic: 1900543 Time: 0.213088
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2097151 Time: 0.041632
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2162687 Time: 0.198752
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2293759 Time: 0.180632
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2359295 Time: 0.12232
[07/19/2022-13:02:34] [V] [TRT] Tactic: 2686975 Time: 0.339968
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3080191 Time: 0.101612
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3342335 Time: 0.114272
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3407871 Time: 0.0948
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3538943 Time: 0.05164
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3670015 Time: 0.385592
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3932159 Time: 0.080824
[07/19/2022-13:02:34] [V] [TRT] Tactic: 3997695 Time: 0.053768
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4063231 Time: 0.064624
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4194303 Time: 0.087592
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4259839 Time: 0.038372
[07/19/2022-13:02:34] [V] [TRT] Tactic: 4325375 Time: 0.057996
[07/19/2022-13:02:35] [V] [TRT] Tactic: 4521983 Time: 0.17728
[07/19/2022-13:02:35] [V] [TRT] Tactic: 4587519 Time: 0.04178
[07/19/2022-13:02:35] [V] [TRT] Tactic: 4653055 Time: 0.041128
[07/19/2022-13:02:35] [V] [TRT] Tactic: 4915199 Time: 0.047516
[07/19/2022-13:02:35] [V] [TRT] Tactic: 4980735 Time: 0.10686
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5177343 Time: 0.03038
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5242879 Time: 0.082972
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5373951 Time: 0.030512
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5439487 Time: 0.081728
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5570559 Time: 0.107108
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5636095 Time: 0.064388
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5701631 Time: 0.150828
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5767167 Time: 0.085268
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5832703 Time: 0.084648
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5898239 Time: 0.043228
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6029311 Time: 0.17456
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6225919 Time: 0.049788
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6291455 Time: 0.0325
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6422527 Time: 0.098828
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6750207 Time: 0.048768
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6815743 Time: 0.087072
[07/19/2022-13:02:35] [V] [TRT] Tactic: 6946815 Time: 0.082136
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7012351 Time: 0.044472
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7077887 Time: 0.052264
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7143423 Time: 0.091412
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7208959 Time: 0.08884
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7340031 Time: 0.049008
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7405567 Time: 0.055568
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7536639 Time: 0.14654
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7602175 Time: 0.084472
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7733247 Time: 0.080408
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7798783 Time: 0.107268
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8191999 Time: 0.058556
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8257535 Time: 0.049264
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8323071 Time: 0.085564
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8650751 Time: 0.082092
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8716287 Time: 0.050924
[07/19/2022-13:02:35] [V] [TRT] Tactic: 9109503 Time: 0.042136
[07/19/2022-13:02:35] [V] [TRT] Tactic: 9568255 Time: 0.049036
[07/19/2022-13:02:35] [V] [TRT] Tactic: 9895935 Time: 0.092372
[07/19/2022-13:02:35] [V] [TRT] Tactic: 10223615 Time: 0.362828
[07/19/2022-13:02:35] [V] [TRT] Tactic: 10354687 Time: 0.048552
[07/19/2022-13:02:35] [V] [TRT] Tactic: 10551295 Time: 0.112912
[07/19/2022-13:02:35] [V] [TRT] Tactic: 10747903 Time: 0.073084
[07/19/2022-13:02:35] [V] [TRT] Tactic: 10944511 Time: 0.11408
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 5177343 Time: 0.03038
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CudnnConvolution)
[07/19/2022-13:02:35] [V] [TRT] CudnnConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CublasConvolution)
[07/19/2022-13:02:35] [V] [TRT] CublasConvolution has no valid tactics for this config, skipping
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/dense_4/MatMul (CaskConvolution)
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_interior_nn_v1 Tactic: 3066127711859985668
[07/19/2022-13:02:35] [V] [TRT] Tactic: 3066127711859985668 Time: 0.063536
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1 Tactic: 3564772625446233998
[07/19/2022-13:02:35] [V] [TRT] Tactic: 3564772625446233998 Time: 0.085012
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1 Tactic: 5319956359050645452
[07/19/2022-13:02:35] [V] [TRT] Tactic: 5319956359050645452 Time: 0.066488
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1 Tactic: 7205456024582378848
[07/19/2022-13:02:35] [V] [TRT] Tactic: 7205456024582378848 Time: 0.067516
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:02:35] [V] [TRT] Tactic: 8163473458334948789 Time: 0.058936
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:35] [V] [TRT] Tactic: -4212163711445252890 Time: 0.0847
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1 Tactic: -3898373634979201110
[07/19/2022-13:02:35] [V] [TRT] Tactic: -3898373634979201110 Time: 0.08692
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1 Tactic: -2409163523992614473
[07/19/2022-13:02:35] [V] [TRT] Tactic: -2409163523992614473 Time: 0.06296
[07/19/2022-13:02:35] [V] [TRT] sequential/sequential_4/dense_4/MatMul Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:35] [V] [TRT] Tactic: -1716393687483585322 Time: 0.084592
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 8163473458334948789 Time: 0.058936
[07/19/2022-13:02:35] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: FusedConvActConvolution Tactic: 5177343
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Float(4,1,1,1) -> Half(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006132
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.00442
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.00442
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Float(4,1,4,4) -> Float(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006132
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.002792
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.002792
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Float(4,1,4,4) -> Half(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006128
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.002804
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.002804
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Half(4,1,1,1) -> Float(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006184
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.003168
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.003168
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Half(2,1:2,1,1) -> Float(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006128
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.002816
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.002816
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning Reformat:Half(2,1:2,1,1) -> Half(4,1,1,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:35] [V] [TRT] Tactic: 1002 Time: 0.006132
[07/19/2022-13:02:35] [V] [TRT] Tactic: 0 Time: 0.002776
[07/19/2022-13:02:35] [V] [TRT] Fastest Tactic: 0 Time: 0.002776
[07/19/2022-13:02:35] [V] [TRT] *************** Autotuning format combination: Float(4,1,1,1) -> Float(4,1) ***************
[07/19/2022-13:02:35] [V] [TRT] --------------- Timing Runner: (Unnamed Layer* 115) [Shuffle] + (Unnamed Layer* 116) [Shuffle] (Shuffle)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.002748
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.002748
[07/19/2022-13:02:36] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning format combination: Half(4,1,1,1) -> Half(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: (Unnamed Layer* 115) [Shuffle] + (Unnamed Layer* 116) [Shuffle] (Shuffle)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.002736
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.002736
[07/19/2022-13:02:36] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: Shuffle Tactic: 0
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning Reformat:Float(4,1) -> Half(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 1002 Time: 0.006168
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.004392
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.004392
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning Reformat:Half(4,1) -> Float(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 1002 Time: 0.006136
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.003364
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.003364
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning format combination: Float(4,1) -> Float(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/softmax_4/Softmax (CudaSoftMax)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 1001 Time: 0.002912
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 1001 Time: 0.002912
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/softmax_4/Softmax (CudnnSoftMax)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.006116
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.006116
[07/19/2022-13:02:36] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaSoftMax Tactic: 1001
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning format combination: Half(4,1) -> Half(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/softmax_4/Softmax (CudaSoftMax)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 1001 Time: 0.002932
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 1001 Time: 0.002932
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: sequential/sequential_4/softmax_4/Softmax (CudnnSoftMax)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.00612
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.00612
[07/19/2022-13:02:36] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaSoftMax Tactic: 1001
[07/19/2022-13:02:36] [V] [TRT] *************** Autotuning Reformat:Half(4,1) -> Float(4,1) ***************
[07/19/2022-13:02:36] [V] [TRT] --------------- Timing Runner: Optimizer Reformat (Reformat)
[07/19/2022-13:02:36] [V] [TRT] Tactic: 1002 Time: 0.006132
[07/19/2022-13:02:36] [V] [TRT] Tactic: 0 Time: 0.003148
[07/19/2022-13:02:36] [V] [TRT] Fastest Tactic: 0 Time: 0.003148
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D (sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0) from Float(28224,49,7,1) to Half(14112,49:2,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 (sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0) from Half(23520,49:2,7,1) to Half(47040,49,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add (sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0) from Half(47040,49,7,1) to Half(23520,49:2,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 (sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0) from Half(23520,49:2,7,1) to Half(47040,49,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add (sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0) from Half(47040,49,7,1) to Half(23520,49:2,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 (sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0) from Half(23520,49:2,7,1) to Half(47040,49,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D (sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0) from Half(47040,49,7,1) to Half(23520,49:2,7,1)
[07/19/2022-13:02:36] [V] [TRT] Adding reformat layer: Reformatted Input Tensor 0 to sequential/sequential_4/dense_4/MatMul (sequential/sequential_4/average_pooling2d_4/AvgPool:0) from Half(640,1:2,1,1) to Float(1280,1,1,1)
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/dense_4/MatMul a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer (Unnamed Layer* 115) [Shuffle] + (Unnamed Layer* 116) [Shuffle] a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] For layer sequential/sequential_4/softmax_4/Softmax a non-conforming implementation was chosen than was requested i.e. requested layer computation precision and output precision types were ignored because it resulted in faster network performance. Enable strict mode to try force choose a conforming implementation.
[07/19/2022-13:02:36] [V] [TRT] Formats and tactics selection completed in 191.55 seconds.
[07/19/2022-13:02:36] [V] [TRT] After reformat layers: 65 layers
[07/19/2022-13:02:36] [V] [TRT] Block size 16777216
[07/19/2022-13:02:36] [V] [TRT] Block size 9633792
[07/19/2022-13:02:36] [V] [TRT] Block size 3612672
[07/19/2022-13:02:36] [V] [TRT] Block size 1605632
[07/19/2022-13:02:36] [V] [TRT] Block size 602112
[07/19/2022-13:02:36] [V] [TRT] Total Activation Memory: 32231424
[07/19/2022-13:02:36] [I] [TRT] Detected 1 inputs and 1 output network tensors.
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1 Tactic: -3456450830548107839
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v0 Tactic: 1698681053543049347
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1 Tactic: 5137655947464784826
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x128_relu_interior_nn_v1 Tactic: 5326823351883942011
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add Set Tactic Name: maxwell_scudnn_128x32_relu_interior_nn_v1 Tactic: -6576203419454146580
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 Set Tactic Name: maxwell_scudnn_128x64_relu_interior_nn_v1 Tactic: -37215280111360163
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_interior_nn_v1 Tactic: -1716393687483585322
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_interior_nn_v1 Tactic: 8163473458334948789
[07/19/2022-13:02:36] [V] [TRT] sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1 Tactic: -4212163711445252890
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6 HostPersistent: 1664 DevicePersistent: 79360
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D HostPersistent: 3200 DevicePersistent: 77824
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 81920
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D HostPersistent: 3200 DevicePersistent: 28672
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 33792
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add HostPersistent: 3200 DevicePersistent: 33280
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 33792
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D HostPersistent: 3200 DevicePersistent: 23552
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6 HostPersistent: 1664 DevicePersistent: 30208
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add HostPersistent: 3200 DevicePersistent: 29696
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6 HostPersistent: 1664 DevicePersistent: 30208
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add HostPersistent: 3200 DevicePersistent: 29696
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6 HostPersistent: 1664 DevicePersistent: 30208
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D HostPersistent: 1664 DevicePersistent: 50688
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 101376
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add HostPersistent: 1664 DevicePersistent: 99840
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 101376
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add HostPersistent: 1664 DevicePersistent: 99840
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 101376
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add HostPersistent: 1664 DevicePersistent: 99840
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 101376
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D HostPersistent: 3200 DevicePersistent: 149504
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 224768
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add HostPersistent: 3200 DevicePersistent: 223232
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 224768
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add HostPersistent: 3200 DevicePersistent: 223232
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 224768
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D HostPersistent: 1664 DevicePersistent: 185344
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 309760
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6 HostPersistent: 24 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add HostPersistent: 3200 DevicePersistent: 308224
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 309760
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6 HostPersistent: 24 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add HostPersistent: 3200 DevicePersistent: 308224
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6 HostPersistent: 3200 DevicePersistent: 309760
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6 HostPersistent: 24 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D HostPersistent: 3200 DevicePersistent: 615424
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6 HostPersistent: 1664 DevicePersistent: 822272
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/average_pooling2d_4/AvgPool HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/dense_4/MatMul HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/dense_4/MatMul HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [V] [TRT] Layer: sequential/sequential_4/softmax_4/Softmax HostPersistent: 0 DevicePersistent: 0
[07/19/2022-13:02:36] [I] [TRT] Total Host Persistent Memory: 96736
[07/19/2022-13:02:36] [I] [TRT] Total Device Persistent Memory: 5736960
[07/19/2022-13:02:36] [I] [TRT] Total Scratch Memory: 0
[07/19/2022-13:02:36] [I] [TRT] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 10 MiB, GPU 32 MiB
[07/19/2022-13:02:36] [V] [TRT] Using cublas a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 942, GPU 3215 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Using cuDNN as a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +0, now: CPU 942, GPU 3215 (MiB)
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 942, GPU 3215 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Engine generation completed in 194.148 seconds.
[07/19/2022-13:02:36] [V] [TRT] Deleting timing cache: 429 entries, 653 hits
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 941, GPU 3215 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Engine Layer Information:
Layer(Shuffle): sequential/reshape/Reshape + sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14, Tactic: 0, input_1[Float(2,3,224,224)] -> sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0[Float(2,3,224,224)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6, Tactic: -3456450830548107839, sequential/sequential_4/mobilenetv2_1.00_224/Conv1/Conv2D__14:0[Float(2,3,224,224)] -> sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0[Float(2,32,112,112)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/Conv1_relu/Relu6:0[Float(2,32,112,112)] -> sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0[Float(2,32,112,112)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project/Conv2D, Tactic: 1698681053543049347, sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_depthwise_relu/Relu6:0[Float(2,32,112,112)] -> sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0[Float(2,16,112,112)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6, Tactic: 1698681053543049347, sequential/sequential_4/mobilenetv2_1.00_224/expanded_conv_project_BN/FusedBatchNormV3:0[Float(2,16,112,112)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0[Float(2,96,112,112)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_1_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_1_expand_relu/Relu6:0[Float(2,96,112,112)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0[Float(2,96,56,56)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_1_project/Conv2D, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_1_depthwise_relu/Relu6:0[Float(2,96,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0[Float(2,24,56,56)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6, Tactic: -37215280111360163, sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0[Float(2,24,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0[Float(2,144,56,56)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_2_expand_relu/Relu6:0[Float(2,144,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0[Float(2,144,56,56)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_2_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_2_depthwise_relu/Relu6:0[Float(2,144,56,56)], sequential/sequential_4/mobilenetv2_1.00_224/block_1_project_BN/FusedBatchNormV3:0[Float(2,24,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0[Float(2,24,56,56)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6, Tactic: -37215280111360163, sequential/sequential_4/mobilenetv2_1.00_224/block_2_add/add:0[Float(2,24,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0[Float(2,144,56,56)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_3_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_3_expand_relu/Relu6:0[Float(2,144,56,56)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0[Float(2,144,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_3_project/Conv2D, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_3_depthwise_relu/Relu6:0[Float(2,144,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0[Float(2,32,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0[Float(2,32,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0[Float(2,192,28,28)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_4_expand_relu/Relu6:0[Float(2,192,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0[Float(2,192,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_4_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_4_depthwise_relu/Relu6:0[Float(2,192,28,28)], sequential/sequential_4/mobilenetv2_1.00_224/block_3_project_BN/FusedBatchNormV3:0[Float(2,32,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0[Float(2,32,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0[Float(2,32,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0[Float(2,192,28,28)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_5_expand_relu/Relu6:0[Float(2,192,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0[Float(2,192,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_5_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_5_depthwise_relu/Relu6:0[Float(2,192,28,28)], sequential/sequential_4/mobilenetv2_1.00_224/block_4_add/add:0[Float(2,32,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0[Float(2,32,28,28)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_5_add/add:0[Float(2,32,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0[Float(2,192,28,28)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_6_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_6_expand_relu/Relu6:0[Float(2,192,28,28)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0[Float(2,192,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_6_project/Conv2D, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_6_depthwise_relu/Relu6:0[Float(2,192,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0[Float(2,64,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6, Tactic: 5326823351883942011, sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0[Float(2,384,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_7_expand_relu/Relu6:0[Float(2,384,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0[Float(2,384,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_7_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_7_depthwise_relu/Relu6:0[Float(2,384,14,14)], sequential/sequential_4/mobilenetv2_1.00_224/block_6_project_BN/FusedBatchNormV3:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0[Float(2,64,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6, Tactic: 5326823351883942011, sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0[Float(2,384,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_8_expand_relu/Relu6:0[Float(2,384,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0[Float(2,384,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_8_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_8_depthwise_relu/Relu6:0[Float(2,384,14,14)], sequential/sequential_4/mobilenetv2_1.00_224/block_7_add/add:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0[Float(2,64,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6, Tactic: 5326823351883942011, sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0[Float(2,384,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_9_expand_relu/Relu6:0[Float(2,384,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0[Float(2,384,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_9_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add, Tactic: 5137655947464784826, sequential/sequential_4/mobilenetv2_1.00_224/block_9_depthwise_relu/Relu6:0[Float(2,384,14,14)], sequential/sequential_4/mobilenetv2_1.00_224/block_8_add/add:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0[Float(2,64,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6, Tactic: 5326823351883942011, sequential/sequential_4/mobilenetv2_1.00_224/block_9_add/add:0[Float(2,64,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0[Float(2,384,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_10_expand_relu/Relu6:0[Float(2,384,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0[Float(2,384,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_10_project/Conv2D, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_10_depthwise_relu/Relu6:0[Float(2,384,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0[Float(2,96,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6, Tactic: -37215280111360163, sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0[Float(2,96,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0[Float(2,576,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_11_expand_relu/Relu6:0[Float(2,576,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0[Float(2,576,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_11_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_11_depthwise_relu/Relu6:0[Float(2,576,14,14)], sequential/sequential_4/mobilenetv2_1.00_224/block_10_project_BN/FusedBatchNormV3:0[Float(2,96,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0[Float(2,96,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6, Tactic: -37215280111360163, sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0[Float(2,96,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0[Float(2,576,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_12_expand_relu/Relu6:0[Float(2,576,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0[Float(2,576,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_12_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add, Tactic: -6576203419454146580, sequential/sequential_4/mobilenetv2_1.00_224/block_12_depthwise_relu/Relu6:0[Float(2,576,14,14)], sequential/sequential_4/mobilenetv2_1.00_224/block_11_add/add:0[Float(2,96,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0[Float(2,96,14,14)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6, Tactic: -37215280111360163, sequential/sequential_4/mobilenetv2_1.00_224/block_12_add/add:0[Float(2,96,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0[Float(2,576,14,14)]
Layer(CudaDepthwiseConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_13_pad/Pad + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6, Tactic: -1, sequential/sequential_4/mobilenetv2_1.00_224/block_13_expand_relu/Relu6:0[Float(2,576,14,14)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0[Float(2,576,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_13_depthwise_relu/Relu6:0[Float(2,576,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D[Half(2,576,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D, Tactic: -4212163711445252890, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_13_project/Conv2D[Half(2,576,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0[Half(2,160,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6, Tactic: -1716393687483585322, sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0[Half(2,160,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_14_expand_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6[Half(2,960,7,7)]
Layer(CudnnConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6, Tactic: 1, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6[Half(2,960,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_14_depthwise_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add[Half(2,960,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add, Tactic: -1716393687483585322, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_14_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add[Half(2,960,7,7)], sequential/sequential_4/mobilenetv2_1.00_224/block_13_project_BN/FusedBatchNormV3:0[Half(2,160,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0[Half(2,160,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6, Tactic: -1716393687483585322, sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0[Half(2,160,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_15_expand_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6[Half(2,960,7,7)]
Layer(CudnnConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6, Tactic: 1, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6[Half(2,960,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_15_depthwise_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add[Half(2,960,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add, Tactic: -1716393687483585322, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_15_project/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add[Half(2,960,7,7)], sequential/sequential_4/mobilenetv2_1.00_224/block_14_add/add:0[Half(2,160,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0[Half(2,160,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6, Tactic: -1716393687483585322, sequential/sequential_4/mobilenetv2_1.00_224/block_15_add/add:0[Half(2,160,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_16_expand_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6[Half(2,960,7,7)]
Layer(CudnnConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6, Tactic: 1, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise/depthwise + sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6[Half(2,960,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0[Half(2,960,7,7)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D, Tactic: 0, sequential/sequential_4/mobilenetv2_1.00_224/block_16_depthwise_relu/Relu6:0[Half(2,960,7,7)] -> Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D[Half(2,960,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D, Tactic: 8163473458334948789, Reformatted Input Tensor 0 to sequential/sequential_4/mobilenetv2_1.00_224/block_16_project/Conv2D[Half(2,960,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0[Half(2,320,7,7)]
Layer(CaskConvolution): sequential/sequential_4/mobilenetv2_1.00_224/Conv_1/Conv2D + sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6, Tactic: -4212163711445252890, sequential/sequential_4/mobilenetv2_1.00_224/block_16_project_BN/FusedBatchNormV3:0[Half(2,320,7,7)] -> sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0[Half(2,1280,7,7)]
Layer(CudaPooling): sequential/sequential_4/average_pooling2d_4/AvgPool, Tactic: -3, sequential/sequential_4/mobilenetv2_1.00_224/out_relu/Relu6:0[Half(2,1280,7,7)] -> sequential/sequential_4/average_pooling2d_4/AvgPool:0[Half(2,1280,1,1)]
Layer(Reformat): Reformatting CopyNode for Input Tensor 0 to sequential/sequential_4/dense_4/MatMul, Tactic: 0, sequential/sequential_4/average_pooling2d_4/AvgPool:0[Half(2,1280,1,1)] -> Reformatted Input Tensor 0 to sequential/sequential_4/dense_4/MatMul[Float(2,1280,1,1)]
Layer(CublasConvolution): sequential/sequential_4/dense_4/MatMul, Tactic: 0, Reformatted Input Tensor 0 to sequential/sequential_4/dense_4/MatMul[Float(2,1280,1,1)] -> (Unnamed Layer* 114) [Fully Connected]_output[Float(2,4,1,1)]
Layer(CudaSoftMax): sequential/sequential_4/softmax_4/Softmax, Tactic: 1001, (Unnamed Layer* 116) [Shuffle]_output[Float(2,4)] -> sequential_4[Float(2,4)]
[07/19/2022-13:02:36] [I] [TRT] [MemUsageSnapshot] Builder end: CPU 939 MiB, GPU 3215 MiB
[07/19/2022-13:02:36] [I] [TRT] Loaded engine size: 6 MB
[07/19/2022-13:02:36] [I] [TRT] [MemUsageSnapshot] deserializeCudaEngine begin: CPU 939 MiB, GPU 3218 MiB
[07/19/2022-13:02:36] [V] [TRT] Using cublas a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 939, GPU 3218 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Using cuDNN as a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +0, now: CPU 939, GPU 3218 (MiB)
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 939, GPU 3218 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Deserialization required 32460 microseconds.
[07/19/2022-13:02:36] [I] [TRT] [MemUsageSnapshot] deserializeCudaEngine end: CPU 939 MiB, GPU 3218 MiB
[07/19/2022-13:02:36] [I] Engine built in 196.119 sec.
[07/19/2022-13:02:36] [I] [TRT] [MemUsageSnapshot] ExecutionContext creation begin: CPU 931 MiB, GPU 3224 MiB
[07/19/2022-13:02:36] [V] [TRT] Using cublas a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 931, GPU 3223 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Using cuDNN as a tactic source
[07/19/2022-13:02:36] [I] [TRT] [MemUsageChange] Init cuDNN: CPU +0, GPU +0, now: CPU 931, GPU 3223 (MiB)
[07/19/2022-13:02:36] [V] [TRT] Total per-runner device memory is 5736960
[07/19/2022-13:02:36] [V] [TRT] Total per-runner host memory is 96736
[07/19/2022-13:02:36] [V] [TRT] Allocated activation device memory of size 15454208
[07/19/2022-13:02:36] [I] [TRT] [MemUsageSnapshot] ExecutionContext creation end: CPU 931 MiB, GPU 3222 MiB
[07/19/2022-13:02:36] [I] Created input binding for input_1 with dimensions 2x3x224x224
[07/19/2022-13:02:36] [I] Created output binding for sequential_4 with dimensions 2x4
[07/19/2022-13:02:36] [I] Starting inference
[07/19/2022-13:02:39] [I] Warmup completed 21 queries over 200 ms
[07/19/2022-13:02:39] [I] Timing trace has 322 queries over 3.01922 s
[07/19/2022-13:02:39] [I] 
[07/19/2022-13:02:39] [I] === Trace details ===
[07/19/2022-13:02:39] [I] Trace averages of 10 runs:
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.29554 ms - Host latency: 9.36566 ms (end to end 9.37515 ms, enqueue 3.98037 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.30727 ms - Host latency: 9.37698 ms (end to end 9.38649 ms, enqueue 3.80732 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.29076 ms - Host latency: 9.36047 ms (end to end 9.37027 ms, enqueue 3.63414 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.46846 ms - Host latency: 9.53894 ms (end to end 9.54868 ms, enqueue 3.67242 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27621 ms - Host latency: 9.34605 ms (end to end 9.35557 ms, enqueue 4.34125 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27117 ms - Host latency: 9.34096 ms (end to end 9.35013 ms, enqueue 4.38091 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28163 ms - Host latency: 9.35153 ms (end to end 9.36116 ms, enqueue 4.48873 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.26193 ms - Host latency: 9.33213 ms (end to end 9.34129 ms, enqueue 4.13091 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.2963 ms - Host latency: 9.36772 ms (end to end 9.37709 ms, enqueue 4.49839 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.30143 ms - Host latency: 9.37148 ms (end to end 9.38105 ms, enqueue 3.98296 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28235 ms - Host latency: 9.35265 ms (end to end 9.36168 ms, enqueue 4.66748 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.39666 ms - Host latency: 9.46752 ms (end to end 9.47753 ms, enqueue 5.29913 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28925 ms - Host latency: 9.36187 ms (end to end 9.37123 ms, enqueue 5.83135 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.26748 ms - Host latency: 9.33878 ms (end to end 9.3484 ms, enqueue 5.5151 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27646 ms - Host latency: 9.34696 ms (end to end 9.35591 ms, enqueue 4.88616 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.3154 ms - Host latency: 9.38907 ms (end to end 9.39862 ms, enqueue 3.70111 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28086 ms - Host latency: 9.35277 ms (end to end 9.36267 ms, enqueue 4.28981 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27379 ms - Host latency: 9.3437 ms (end to end 9.35308 ms, enqueue 4.60719 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.29557 ms - Host latency: 9.36642 ms (end to end 9.37605 ms, enqueue 3.88926 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27633 ms - Host latency: 9.34729 ms (end to end 9.3567 ms, enqueue 4.8537 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27605 ms - Host latency: 9.34619 ms (end to end 9.35593 ms, enqueue 4.02498 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.26472 ms - Host latency: 9.33586 ms (end to end 9.34487 ms, enqueue 5.26321 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28677 ms - Host latency: 9.35759 ms (end to end 9.36751 ms, enqueue 4.24302 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.2929 ms - Host latency: 9.36362 ms (end to end 9.37329 ms, enqueue 3.77432 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28086 ms - Host latency: 9.35068 ms (end to end 9.36006 ms, enqueue 3.86411 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27649 ms - Host latency: 9.3478 ms (end to end 9.35745 ms, enqueue 4.48611 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28772 ms - Host latency: 9.35879 ms (end to end 9.36851 ms, enqueue 4.34451 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.37105 ms - Host latency: 9.44155 ms (end to end 9.45127 ms, enqueue 4.42009 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.2728 ms - Host latency: 9.34265 ms (end to end 9.3519 ms, enqueue 4.24905 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.28499 ms - Host latency: 9.35564 ms (end to end 9.36511 ms, enqueue 4.56987 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.27568 ms - Host latency: 9.34573 ms (end to end 9.35537 ms, enqueue 4.66226 ms)
[07/19/2022-13:02:39] [I] Average on 10 runs - GPU latency: 9.29248 ms - Host latency: 9.36379 ms (end to end 9.37351 ms, enqueue 4.04912 ms)
[07/19/2022-13:02:39] [I] 
[07/19/2022-13:02:39] [I] === Performance summary ===
[07/19/2022-13:02:39] [I] Throughput: 106.65 qps
[07/19/2022-13:02:39] [I] Latency: min = 9.27417 ms, max = 10.5217 ms, mean = 9.36637 ms, median = 9.34973 ms, percentile(99%) = 9.75085 ms
[07/19/2022-13:02:39] [I] End-to-End Host Latency: min = 9.27979 ms, max = 10.532 ms, mean = 9.37589 ms, median = 9.35956 ms, percentile(99%) = 9.75867 ms
[07/19/2022-13:02:39] [I] Enqueue Time: min = 2.38208 ms, max = 9.8501 ms, mean = 4.38956 ms, median = 4.25946 ms, percentile(99%) = 8.36462 ms
[07/19/2022-13:02:39] [I] H2D Latency: min = 0.0656738 ms, max = 0.0749512 ms, mean = 0.0682682 ms, median = 0.067627 ms, percentile(99%) = 0.0731201 ms
[07/19/2022-13:02:39] [I] GPU Compute Time: min = 9.20532 ms, max = 10.451 ms, mean = 9.29571 ms, median = 9.27985 ms, percentile(99%) = 9.68164 ms
[07/19/2022-13:02:39] [I] D2H Latency: min = 0.000976562 ms, max = 0.00341797 ms, mean = 0.00238971 ms, median = 0.00238037 ms, percentile(99%) = 0.0032959 ms
[07/19/2022-13:02:39] [I] Total Host Walltime: 3.01922 s
[07/19/2022-13:02:39] [I] Total GPU Compute Time: 2.99322 s
[07/19/2022-13:02:39] [I] Explanations of the performance metrics are printed in the verbose logs.
[07/19/2022-13:02:39] [V] 
[07/19/2022-13:02:39] [V] === Explanations of the performance metrics ===
[07/19/2022-13:02:39] [V] Total Host Walltime: the host walltime from when the first query (after warmups) is enqueued to when the last query is completed.
[07/19/2022-13:02:39] [V] GPU Compute Time: the GPU latency to execute the kernels for a query.
[07/19/2022-13:02:39] [V] Total GPU Compute Time: the summation of the GPU Compute Time of all the queries. If this is significantly shorter than Total Host Walltime, the GPU may be under-utilized because of host-side overheads or data transfers.
[07/19/2022-13:02:39] [V] Throughput: the observed throughput computed by dividing the number of queries by the Total Host Walltime. If this is significantly lower than the reciprocal of GPU Compute Time, the GPU may be under-utilized because of host-side overheads or data transfers.
[07/19/2022-13:02:39] [V] Enqueue Time: the host latency to enqueue a query. If this is longer than GPU Compute Time, the GPU may be under-utilized.
[07/19/2022-13:02:39] [V] H2D Latency: the latency for host-to-device data transfers for input tensors of a single query.
[07/19/2022-13:02:39] [V] D2H Latency: the latency for device-to-host data transfers for output tensors of a single query.
[07/19/2022-13:02:39] [V] Latency: the summation of H2D Latency, GPU Compute Time, and D2H Latency. This is the latency to infer a single query.
[07/19/2022-13:02:39] [V] End-to-End Host Latency: the duration from when the H2D of a query is called to when the D2H of the same query is completed, which includes the latency to wait for the completion of the previous query. This is the latency of a query if multiple queries are enqueued consecutively.
[07/19/2022-13:02:39] [I] 
&&&& PASSED TensorRT.trtexec [TensorRT v8001] # /usr/src/tensorrt/bin/trtexec --onnx=onnx_model.onnx --saveEngine=TRTBS2.trt --explicitBatch --verbose --fp16
[07/19/2022-13:02:39] [I] [TRT] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +0, now: CPU 931, GPU 3202 (MiB)