&&&& RUNNING TensorRT.trtexec # ./trtexec --onnx=/media/nx091/Data/prashant/code/EfficientHandPose/models/checkpoint_256_256_128.onnx --avgRuns=25000 --exportProfile=/media/nx091/Data/prashant/code/EfficientHandPose/trtexec_FP16_256-256-128_profile_DLA.json --fp16 --shapes=input:1x3x480x640 --verbose --useDLACore=1 --allowGPUFallback
[10/13/2020-20:18:44] [I] === Model Options ===
[10/13/2020-20:18:44] [I] Format: ONNX
[10/13/2020-20:18:44] [I] Model: /media/nx091/Data/prashant/code/EfficientHandPose/models/checkpoint_256_256_128.onnx
[10/13/2020-20:18:44] [I] Output:
[10/13/2020-20:18:44] [I] === Build Options ===
[10/13/2020-20:18:44] [I] Max batch: explicit
[10/13/2020-20:18:44] [I] Workspace: 16 MB
[10/13/2020-20:18:44] [I] minTiming: 1
[10/13/2020-20:18:44] [I] avgTiming: 8
[10/13/2020-20:18:44] [I] Precision: FP32+FP16
[10/13/2020-20:18:44] [I] Calibration: 
[10/13/2020-20:18:44] [I] Safe mode: Disabled
[10/13/2020-20:18:44] [I] Save engine: 
[10/13/2020-20:18:44] [I] Load engine: 
[10/13/2020-20:18:44] [I] Builder Cache: Enabled
[10/13/2020-20:18:44] [I] NVTX verbosity: 0
[10/13/2020-20:18:44] [I] Inputs format: fp32:CHW
[10/13/2020-20:18:44] [I] Outputs format: fp32:CHW
[10/13/2020-20:18:44] [I] Input build shape: input=1x3x480x640+1x3x480x640+1x3x480x640
[10/13/2020-20:18:44] [I] Input calibration shapes: model
[10/13/2020-20:18:44] [I] === System Options ===
[10/13/2020-20:18:44] [I] Device: 0
[10/13/2020-20:18:44] [I] DLACore: 1(With GPU fallback)
[10/13/2020-20:18:44] [I] Plugins:
[10/13/2020-20:18:44] [I] === Inference Options ===
[10/13/2020-20:18:44] [I] Batch: Explicit
[10/13/2020-20:18:44] [I] Input inference shape: input=1x3x480x640
[10/13/2020-20:18:44] [I] Iterations: 10
[10/13/2020-20:18:44] [I] Duration: 3s (+ 200ms warm up)
[10/13/2020-20:18:44] [I] Sleep time: 0ms
[10/13/2020-20:18:44] [I] Streams: 1
[10/13/2020-20:18:44] [I] ExposeDMA: Disabled
[10/13/2020-20:18:44] [I] Spin-wait: Disabled
[10/13/2020-20:18:44] [I] Multithreading: Disabled
[10/13/2020-20:18:44] [I] CUDA Graph: Disabled
[10/13/2020-20:18:44] [I] Skip inference: Disabled
[10/13/2020-20:18:44] [I] Inputs:
[10/13/2020-20:18:44] [I] === Reporting Options ===
[10/13/2020-20:18:44] [I] Verbose: Enabled
[10/13/2020-20:18:44] [I] Averages: 25000 inferences
[10/13/2020-20:18:44] [I] Percentile: 99
[10/13/2020-20:18:44] [I] Dump output: Disabled
[10/13/2020-20:18:44] [I] Profile: Disabled
[10/13/2020-20:18:44] [I] Export timing to JSON file: 
[10/13/2020-20:18:44] [I] Export output to JSON file: 
[10/13/2020-20:18:44] [I] Export profile to JSON file: /media/nx091/Data/prashant/code/EfficientHandPose/trtexec_FP16_256-256-128_profile_DLA.json
[10/13/2020-20:18:44] [I] 
[10/13/2020-20:18:44] [V] [TRT] Registered plugin creator - ::GridAnchor_TRT version 1
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----------------------------------------------------------------
Input filename:   /media/nx091/Data/prashant/code/EfficientHandPose/models/checkpoint_256_256_128.onnx
ONNX IR version:  0.0.6
Opset version:    10
Producer name:    pytorch
Producer version: 1.6
Domain:           
Model version:    0
Doc string:       
----------------------------------------------------------------
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[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 333
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_1 [BatchNormalization] inputs: [333 -> (1, 32, 240, 320)], [features.0.1.weight -> (32)], [features.0.1.bias -> (32)], [features.0.1.running_mean -> (32)], [features.0.1.running_var -> (32)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_1 for ONNX node: BatchNormalization_1
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 334 for ONNX tensor: 334
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_1 [BatchNormalization] outputs: [334 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_2 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 334
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_2 [Clip] inputs: [334 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_2 for ONNX node: Clip_2
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 335 for ONNX tensor: 335
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_2 [Clip] outputs: [335 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_3 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 335
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_3 [Conv] inputs: [335 -> (1, 32, 240, 320)], [features.1.conv.0.0.weight -> (32, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 32, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_3 for ONNX node: Conv_3
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 32
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 32, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 336 for ONNX tensor: 336
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_3 [Conv] outputs: [336 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_4 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 336
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_4 [BatchNormalization] inputs: [336 -> (1, 32, 240, 320)], [features.1.conv.0.1.weight -> (32)], [features.1.conv.0.1.bias -> (32)], [features.1.conv.0.1.running_mean -> (32)], [features.1.conv.0.1.running_var -> (32)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_4 for ONNX node: BatchNormalization_4
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 337 for ONNX tensor: 337
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_4 [BatchNormalization] outputs: [337 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_5 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 337
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_5 [Clip] inputs: [337 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_5 for ONNX node: Clip_5
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 338 for ONNX tensor: 338
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_5 [Clip] outputs: [338 -> (1, 32, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_6 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 338
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_6 [Conv] inputs: [338 -> (1, 32, 240, 320)], [features.1.conv.1.weight -> (16, 32, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 32, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_6 for ONNX node: Conv_6
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 16
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 16, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 339 for ONNX tensor: 339
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_6 [Conv] outputs: [339 -> (1, 16, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_7 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 339
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.2.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.2.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.1.conv.2.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_7 [BatchNormalization] inputs: [339 -> (1, 16, 240, 320)], [features.1.conv.2.weight -> (16)], [features.1.conv.2.bias -> (16)], [features.1.conv.2.running_mean -> (16)], [features.1.conv.2.running_var -> (16)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_7 for ONNX node: BatchNormalization_7
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 340 for ONNX tensor: 340
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_7 [BatchNormalization] outputs: [340 -> (1, 16, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_8 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 340
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_8 [Conv] inputs: [340 -> (1, 16, 240, 320)], [features.2.conv.0.0.weight -> (96, 16, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 16, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_8 for ONNX node: Conv_8
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 96, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 341 for ONNX tensor: 341
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_8 [Conv] outputs: [341 -> (1, 96, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_9 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 341
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_9 [BatchNormalization] inputs: [341 -> (1, 96, 240, 320)], [features.2.conv.0.1.weight -> (96)], [features.2.conv.0.1.bias -> (96)], [features.2.conv.0.1.running_mean -> (96)], [features.2.conv.0.1.running_var -> (96)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_9 for ONNX node: BatchNormalization_9
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 342 for ONNX tensor: 342
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_9 [BatchNormalization] outputs: [342 -> (1, 96, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_10 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 342
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_10 [Clip] inputs: [342 -> (1, 96, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_10 for ONNX node: Clip_10
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 343 for ONNX tensor: 343
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_10 [Clip] outputs: [343 -> (1, 96, 240, 320)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_11 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 343
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_11 [Conv] inputs: [343 -> (1, 96, 240, 320)], [features.2.conv.1.0.weight -> (96, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 96, 240, 320)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_11 for ONNX node: Conv_11
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (2, 2), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 96
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 96, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 344 for ONNX tensor: 344
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_11 [Conv] outputs: [344 -> (1, 96, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_12 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 344
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_12 [BatchNormalization] inputs: [344 -> (1, 96, 120, 160)], [features.2.conv.1.1.weight -> (96)], [features.2.conv.1.1.bias -> (96)], [features.2.conv.1.1.running_mean -> (96)], [features.2.conv.1.1.running_var -> (96)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_12 for ONNX node: BatchNormalization_12
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 345 for ONNX tensor: 345
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_12 [BatchNormalization] outputs: [345 -> (1, 96, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_13 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 345
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_13 [Clip] inputs: [345 -> (1, 96, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_13 for ONNX node: Clip_13
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 346 for ONNX tensor: 346
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_13 [Clip] outputs: [346 -> (1, 96, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_14 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 346
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_14 [Conv] inputs: [346 -> (1, 96, 120, 160)], [features.2.conv.2.weight -> (24, 96, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 96, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_14 for ONNX node: Conv_14
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 24
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 24, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 347 for ONNX tensor: 347
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_14 [Conv] outputs: [347 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_15 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 347
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.2.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_15 [BatchNormalization] inputs: [347 -> (1, 24, 120, 160)], [features.2.conv.3.weight -> (24)], [features.2.conv.3.bias -> (24)], [features.2.conv.3.running_mean -> (24)], [features.2.conv.3.running_var -> (24)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_15 for ONNX node: BatchNormalization_15
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 348 for ONNX tensor: 348
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_15 [BatchNormalization] outputs: [348 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_16 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 348
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_16 [Conv] inputs: [348 -> (1, 24, 120, 160)], [features.3.conv.0.0.weight -> (144, 24, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 24, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_16 for ONNX node: Conv_16
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 144
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 349 for ONNX tensor: 349
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_16 [Conv] outputs: [349 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_17 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 349
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_17 [BatchNormalization] inputs: [349 -> (1, 144, 120, 160)], [features.3.conv.0.1.weight -> (144)], [features.3.conv.0.1.bias -> (144)], [features.3.conv.0.1.running_mean -> (144)], [features.3.conv.0.1.running_var -> (144)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_17 for ONNX node: BatchNormalization_17
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 350 for ONNX tensor: 350
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_17 [BatchNormalization] outputs: [350 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_18 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 350
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_18 [Clip] inputs: [350 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_18 for ONNX node: Clip_18
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 351 for ONNX tensor: 351
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_18 [Clip] outputs: [351 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_19 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 351
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_19 [Conv] inputs: [351 -> (1, 144, 120, 160)], [features.3.conv.1.0.weight -> (144, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_19 for ONNX node: Conv_19
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 144
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 352 for ONNX tensor: 352
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_19 [Conv] outputs: [352 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_20 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 352
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_20 [BatchNormalization] inputs: [352 -> (1, 144, 120, 160)], [features.3.conv.1.1.weight -> (144)], [features.3.conv.1.1.bias -> (144)], [features.3.conv.1.1.running_mean -> (144)], [features.3.conv.1.1.running_var -> (144)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_20 for ONNX node: BatchNormalization_20
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 353 for ONNX tensor: 353
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_20 [BatchNormalization] outputs: [353 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_21 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 353
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_21 [Clip] inputs: [353 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_21 for ONNX node: Clip_21
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 354 for ONNX tensor: 354
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_21 [Clip] outputs: [354 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_22 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 354
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_22 [Conv] inputs: [354 -> (1, 144, 120, 160)], [features.3.conv.2.weight -> (24, 144, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_22 for ONNX node: Conv_22
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 24
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 24, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 355 for ONNX tensor: 355
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_22 [Conv] outputs: [355 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_23 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 355
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.3.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_23 [BatchNormalization] inputs: [355 -> (1, 24, 120, 160)], [features.3.conv.3.weight -> (24)], [features.3.conv.3.bias -> (24)], [features.3.conv.3.running_mean -> (24)], [features.3.conv.3.running_var -> (24)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_23 for ONNX node: BatchNormalization_23
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 356 for ONNX tensor: 356
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_23 [BatchNormalization] outputs: [356 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_24 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 348
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 356
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_24 [Add] inputs: [348 -> (1, 24, 120, 160)], [356 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_24 for ONNX node: Add_24
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 357 for ONNX tensor: 357
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_24 [Add] outputs: [357 -> (1, 24, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_25 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 357
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_25 [Conv] inputs: [357 -> (1, 24, 120, 160)], [features.4.conv.0.0.weight -> (144, 24, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 24, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_25 for ONNX node: Conv_25
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 144
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 358 for ONNX tensor: 358
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_25 [Conv] outputs: [358 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_26 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 358
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_26 [BatchNormalization] inputs: [358 -> (1, 144, 120, 160)], [features.4.conv.0.1.weight -> (144)], [features.4.conv.0.1.bias -> (144)], [features.4.conv.0.1.running_mean -> (144)], [features.4.conv.0.1.running_var -> (144)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_26 for ONNX node: BatchNormalization_26
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 359 for ONNX tensor: 359
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_26 [BatchNormalization] outputs: [359 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_27 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 359
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_27 [Clip] inputs: [359 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_27 for ONNX node: Clip_27
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 360 for ONNX tensor: 360
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_27 [Clip] outputs: [360 -> (1, 144, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_28 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 360
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_28 [Conv] inputs: [360 -> (1, 144, 120, 160)], [features.4.conv.1.0.weight -> (144, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 144, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_28 for ONNX node: Conv_28
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (2, 2), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 144
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 144, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 361 for ONNX tensor: 361
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_28 [Conv] outputs: [361 -> (1, 144, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_29 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 361
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_29 [BatchNormalization] inputs: [361 -> (1, 144, 60, 80)], [features.4.conv.1.1.weight -> (144)], [features.4.conv.1.1.bias -> (144)], [features.4.conv.1.1.running_mean -> (144)], [features.4.conv.1.1.running_var -> (144)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_29 for ONNX node: BatchNormalization_29
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 362 for ONNX tensor: 362
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_29 [BatchNormalization] outputs: [362 -> (1, 144, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_30 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 362
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_30 [Clip] inputs: [362 -> (1, 144, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_30 for ONNX node: Clip_30
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 363 for ONNX tensor: 363
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_30 [Clip] outputs: [363 -> (1, 144, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_31 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 363
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_31 [Conv] inputs: [363 -> (1, 144, 60, 80)], [features.4.conv.2.weight -> (32, 144, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 144, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_31 for ONNX node: Conv_31
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 364 for ONNX tensor: 364
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_31 [Conv] outputs: [364 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_32 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 364
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.4.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_32 [BatchNormalization] inputs: [364 -> (1, 32, 60, 80)], [features.4.conv.3.weight -> (32)], [features.4.conv.3.bias -> (32)], [features.4.conv.3.running_mean -> (32)], [features.4.conv.3.running_var -> (32)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_32 for ONNX node: BatchNormalization_32
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 365 for ONNX tensor: 365
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_32 [BatchNormalization] outputs: [365 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_33 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 365
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_33 [Conv] inputs: [365 -> (1, 32, 60, 80)], [features.5.conv.0.0.weight -> (192, 32, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_33 for ONNX node: Conv_33
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 366 for ONNX tensor: 366
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_33 [Conv] outputs: [366 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_34 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 366
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_34 [BatchNormalization] inputs: [366 -> (1, 192, 60, 80)], [features.5.conv.0.1.weight -> (192)], [features.5.conv.0.1.bias -> (192)], [features.5.conv.0.1.running_mean -> (192)], [features.5.conv.0.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_34 for ONNX node: BatchNormalization_34
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 367 for ONNX tensor: 367
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_34 [BatchNormalization] outputs: [367 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_35 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 367
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_35 [Clip] inputs: [367 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_35 for ONNX node: Clip_35
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 368 for ONNX tensor: 368
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_35 [Clip] outputs: [368 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_36 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 368
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_36 [Conv] inputs: [368 -> (1, 192, 60, 80)], [features.5.conv.1.0.weight -> (192, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_36 for ONNX node: Conv_36
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 369 for ONNX tensor: 369
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_36 [Conv] outputs: [369 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_37 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 369
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_37 [BatchNormalization] inputs: [369 -> (1, 192, 60, 80)], [features.5.conv.1.1.weight -> (192)], [features.5.conv.1.1.bias -> (192)], [features.5.conv.1.1.running_mean -> (192)], [features.5.conv.1.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_37 for ONNX node: BatchNormalization_37
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 370 for ONNX tensor: 370
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_37 [BatchNormalization] outputs: [370 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_38 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 370
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_38 [Clip] inputs: [370 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_38 for ONNX node: Clip_38
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 371 for ONNX tensor: 371
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_38 [Clip] outputs: [371 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_39 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 371
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_39 [Conv] inputs: [371 -> (1, 192, 60, 80)], [features.5.conv.2.weight -> (32, 192, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_39 for ONNX node: Conv_39
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 372 for ONNX tensor: 372
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_39 [Conv] outputs: [372 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_40 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 372
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.5.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_40 [BatchNormalization] inputs: [372 -> (1, 32, 60, 80)], [features.5.conv.3.weight -> (32)], [features.5.conv.3.bias -> (32)], [features.5.conv.3.running_mean -> (32)], [features.5.conv.3.running_var -> (32)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_40 for ONNX node: BatchNormalization_40
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 373 for ONNX tensor: 373
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_40 [BatchNormalization] outputs: [373 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_41 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 365
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 373
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_41 [Add] inputs: [365 -> (1, 32, 60, 80)], [373 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_41 for ONNX node: Add_41
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 374 for ONNX tensor: 374
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_41 [Add] outputs: [374 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_42 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 374
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_42 [Conv] inputs: [374 -> (1, 32, 60, 80)], [features.6.conv.0.0.weight -> (192, 32, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_42 for ONNX node: Conv_42
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 375 for ONNX tensor: 375
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_42 [Conv] outputs: [375 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_43 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 375
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_43 [BatchNormalization] inputs: [375 -> (1, 192, 60, 80)], [features.6.conv.0.1.weight -> (192)], [features.6.conv.0.1.bias -> (192)], [features.6.conv.0.1.running_mean -> (192)], [features.6.conv.0.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_43 for ONNX node: BatchNormalization_43
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 376 for ONNX tensor: 376
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_43 [BatchNormalization] outputs: [376 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_44 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 376
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_44 [Clip] inputs: [376 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_44 for ONNX node: Clip_44
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 377 for ONNX tensor: 377
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_44 [Clip] outputs: [377 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_45 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 377
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_45 [Conv] inputs: [377 -> (1, 192, 60, 80)], [features.6.conv.1.0.weight -> (192, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_45 for ONNX node: Conv_45
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 378 for ONNX tensor: 378
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_45 [Conv] outputs: [378 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_46 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 378
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_46 [BatchNormalization] inputs: [378 -> (1, 192, 60, 80)], [features.6.conv.1.1.weight -> (192)], [features.6.conv.1.1.bias -> (192)], [features.6.conv.1.1.running_mean -> (192)], [features.6.conv.1.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_46 for ONNX node: BatchNormalization_46
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 379 for ONNX tensor: 379
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_46 [BatchNormalization] outputs: [379 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_47 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 379
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_47 [Clip] inputs: [379 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_47 for ONNX node: Clip_47
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 380 for ONNX tensor: 380
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_47 [Clip] outputs: [380 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_48 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 380
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_48 [Conv] inputs: [380 -> (1, 192, 60, 80)], [features.6.conv.2.weight -> (32, 192, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_48 for ONNX node: Conv_48
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 32
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 381 for ONNX tensor: 381
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_48 [Conv] outputs: [381 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_49 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 381
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.6.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_49 [BatchNormalization] inputs: [381 -> (1, 32, 60, 80)], [features.6.conv.3.weight -> (32)], [features.6.conv.3.bias -> (32)], [features.6.conv.3.running_mean -> (32)], [features.6.conv.3.running_var -> (32)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_49 for ONNX node: BatchNormalization_49
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 382 for ONNX tensor: 382
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_49 [BatchNormalization] outputs: [382 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_50 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 374
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 382
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_50 [Add] inputs: [374 -> (1, 32, 60, 80)], [382 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_50 for ONNX node: Add_50
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 383 for ONNX tensor: 383
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_50 [Add] outputs: [383 -> (1, 32, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_51 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 383
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_51 [Conv] inputs: [383 -> (1, 32, 60, 80)], [features.7.conv.0.0.weight -> (192, 32, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 32, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_51 for ONNX node: Conv_51
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 384 for ONNX tensor: 384
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_51 [Conv] outputs: [384 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_52 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 384
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_52 [BatchNormalization] inputs: [384 -> (1, 192, 60, 80)], [features.7.conv.0.1.weight -> (192)], [features.7.conv.0.1.bias -> (192)], [features.7.conv.0.1.running_mean -> (192)], [features.7.conv.0.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_52 for ONNX node: BatchNormalization_52
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 385 for ONNX tensor: 385
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_52 [BatchNormalization] outputs: [385 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_53 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 385
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_53 [Clip] inputs: [385 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_53 for ONNX node: Clip_53
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 386 for ONNX tensor: 386
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_53 [Clip] outputs: [386 -> (1, 192, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_54 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 386
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_54 [Conv] inputs: [386 -> (1, 192, 60, 80)], [features.7.conv.1.0.weight -> (192, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 60, 80)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_54 for ONNX node: Conv_54
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (2, 2), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 192
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 192, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 387 for ONNX tensor: 387
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_54 [Conv] outputs: [387 -> (1, 192, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_55 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 387
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_55 [BatchNormalization] inputs: [387 -> (1, 192, 30, 40)], [features.7.conv.1.1.weight -> (192)], [features.7.conv.1.1.bias -> (192)], [features.7.conv.1.1.running_mean -> (192)], [features.7.conv.1.1.running_var -> (192)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_55 for ONNX node: BatchNormalization_55
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 388 for ONNX tensor: 388
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_55 [BatchNormalization] outputs: [388 -> (1, 192, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_56 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 388
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_56 [Clip] inputs: [388 -> (1, 192, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_56 for ONNX node: Clip_56
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 389 for ONNX tensor: 389
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_56 [Clip] outputs: [389 -> (1, 192, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_57 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 389
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_57 [Conv] inputs: [389 -> (1, 192, 30, 40)], [features.7.conv.2.weight -> (64, 192, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 192, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_57 for ONNX node: Conv_57
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 390 for ONNX tensor: 390
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_57 [Conv] outputs: [390 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_58 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 390
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.7.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_58 [BatchNormalization] inputs: [390 -> (1, 64, 30, 40)], [features.7.conv.3.weight -> (64)], [features.7.conv.3.bias -> (64)], [features.7.conv.3.running_mean -> (64)], [features.7.conv.3.running_var -> (64)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_58 for ONNX node: BatchNormalization_58
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 391 for ONNX tensor: 391
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_58 [BatchNormalization] outputs: [391 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_59 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 391
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_59 [Conv] inputs: [391 -> (1, 64, 30, 40)], [features.8.conv.0.0.weight -> (384, 64, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_59 for ONNX node: Conv_59
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 392 for ONNX tensor: 392
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_59 [Conv] outputs: [392 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_60 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 392
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_60 [BatchNormalization] inputs: [392 -> (1, 384, 30, 40)], [features.8.conv.0.1.weight -> (384)], [features.8.conv.0.1.bias -> (384)], [features.8.conv.0.1.running_mean -> (384)], [features.8.conv.0.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_60 for ONNX node: BatchNormalization_60
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 393 for ONNX tensor: 393
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_60 [BatchNormalization] outputs: [393 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_61 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 393
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_61 [Clip] inputs: [393 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_61 for ONNX node: Clip_61
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 394 for ONNX tensor: 394
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_61 [Clip] outputs: [394 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_62 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 394
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_62 [Conv] inputs: [394 -> (1, 384, 30, 40)], [features.8.conv.1.0.weight -> (384, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_62 for ONNX node: Conv_62
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 395 for ONNX tensor: 395
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_62 [Conv] outputs: [395 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_63 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 395
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_63 [BatchNormalization] inputs: [395 -> (1, 384, 30, 40)], [features.8.conv.1.1.weight -> (384)], [features.8.conv.1.1.bias -> (384)], [features.8.conv.1.1.running_mean -> (384)], [features.8.conv.1.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_63 for ONNX node: BatchNormalization_63
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 396 for ONNX tensor: 396
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_63 [BatchNormalization] outputs: [396 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_64 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 396
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_64 [Clip] inputs: [396 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_64 for ONNX node: Clip_64
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 397 for ONNX tensor: 397
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_64 [Clip] outputs: [397 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_65 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 397
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_65 [Conv] inputs: [397 -> (1, 384, 30, 40)], [features.8.conv.2.weight -> (64, 384, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_65 for ONNX node: Conv_65
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 398 for ONNX tensor: 398
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_65 [Conv] outputs: [398 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_66 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 398
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.8.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_66 [BatchNormalization] inputs: [398 -> (1, 64, 30, 40)], [features.8.conv.3.weight -> (64)], [features.8.conv.3.bias -> (64)], [features.8.conv.3.running_mean -> (64)], [features.8.conv.3.running_var -> (64)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_66 for ONNX node: BatchNormalization_66
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 399 for ONNX tensor: 399
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_66 [BatchNormalization] outputs: [399 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_67 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 391
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 399
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_67 [Add] inputs: [391 -> (1, 64, 30, 40)], [399 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_67 for ONNX node: Add_67
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 400 for ONNX tensor: 400
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_67 [Add] outputs: [400 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_68 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 400
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_68 [Conv] inputs: [400 -> (1, 64, 30, 40)], [features.9.conv.0.0.weight -> (384, 64, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_68 for ONNX node: Conv_68
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 401 for ONNX tensor: 401
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_68 [Conv] outputs: [401 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_69 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 401
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_69 [BatchNormalization] inputs: [401 -> (1, 384, 30, 40)], [features.9.conv.0.1.weight -> (384)], [features.9.conv.0.1.bias -> (384)], [features.9.conv.0.1.running_mean -> (384)], [features.9.conv.0.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_69 for ONNX node: BatchNormalization_69
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 402 for ONNX tensor: 402
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_69 [BatchNormalization] outputs: [402 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_70 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 402
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_70 [Clip] inputs: [402 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_70 for ONNX node: Clip_70
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 403 for ONNX tensor: 403
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_70 [Clip] outputs: [403 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_71 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 403
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_71 [Conv] inputs: [403 -> (1, 384, 30, 40)], [features.9.conv.1.0.weight -> (384, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_71 for ONNX node: Conv_71
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 404 for ONNX tensor: 404
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_71 [Conv] outputs: [404 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_72 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 404
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_72 [BatchNormalization] inputs: [404 -> (1, 384, 30, 40)], [features.9.conv.1.1.weight -> (384)], [features.9.conv.1.1.bias -> (384)], [features.9.conv.1.1.running_mean -> (384)], [features.9.conv.1.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_72 for ONNX node: BatchNormalization_72
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 405 for ONNX tensor: 405
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_72 [BatchNormalization] outputs: [405 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_73 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 405
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_73 [Clip] inputs: [405 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_73 for ONNX node: Clip_73
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 406 for ONNX tensor: 406
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_73 [Clip] outputs: [406 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_74 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 406
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_74 [Conv] inputs: [406 -> (1, 384, 30, 40)], [features.9.conv.2.weight -> (64, 384, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_74 for ONNX node: Conv_74
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 407 for ONNX tensor: 407
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_74 [Conv] outputs: [407 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_75 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 407
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.9.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_75 [BatchNormalization] inputs: [407 -> (1, 64, 30, 40)], [features.9.conv.3.weight -> (64)], [features.9.conv.3.bias -> (64)], [features.9.conv.3.running_mean -> (64)], [features.9.conv.3.running_var -> (64)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_75 for ONNX node: BatchNormalization_75
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 408 for ONNX tensor: 408
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_75 [BatchNormalization] outputs: [408 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_76 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 400
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 408
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_76 [Add] inputs: [400 -> (1, 64, 30, 40)], [408 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_76 for ONNX node: Add_76
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 409 for ONNX tensor: 409
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_76 [Add] outputs: [409 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_77 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 409
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_77 [Conv] inputs: [409 -> (1, 64, 30, 40)], [features.10.conv.0.0.weight -> (384, 64, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_77 for ONNX node: Conv_77
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 410 for ONNX tensor: 410
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_77 [Conv] outputs: [410 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_78 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 410
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_78 [BatchNormalization] inputs: [410 -> (1, 384, 30, 40)], [features.10.conv.0.1.weight -> (384)], [features.10.conv.0.1.bias -> (384)], [features.10.conv.0.1.running_mean -> (384)], [features.10.conv.0.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_78 for ONNX node: BatchNormalization_78
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 411 for ONNX tensor: 411
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_78 [BatchNormalization] outputs: [411 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_79 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 411
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_79 [Clip] inputs: [411 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_79 for ONNX node: Clip_79
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 412 for ONNX tensor: 412
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_79 [Clip] outputs: [412 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_80 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 412
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_80 [Conv] inputs: [412 -> (1, 384, 30, 40)], [features.10.conv.1.0.weight -> (384, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_80 for ONNX node: Conv_80
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 413 for ONNX tensor: 413
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_80 [Conv] outputs: [413 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_81 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 413
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_81 [BatchNormalization] inputs: [413 -> (1, 384, 30, 40)], [features.10.conv.1.1.weight -> (384)], [features.10.conv.1.1.bias -> (384)], [features.10.conv.1.1.running_mean -> (384)], [features.10.conv.1.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_81 for ONNX node: BatchNormalization_81
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 414 for ONNX tensor: 414
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_81 [BatchNormalization] outputs: [414 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_82 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 414
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_82 [Clip] inputs: [414 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_82 for ONNX node: Clip_82
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 415 for ONNX tensor: 415
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_82 [Clip] outputs: [415 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_83 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 415
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_83 [Conv] inputs: [415 -> (1, 384, 30, 40)], [features.10.conv.2.weight -> (64, 384, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_83 for ONNX node: Conv_83
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 64
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 416 for ONNX tensor: 416
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_83 [Conv] outputs: [416 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_84 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 416
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.10.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_84 [BatchNormalization] inputs: [416 -> (1, 64, 30, 40)], [features.10.conv.3.weight -> (64)], [features.10.conv.3.bias -> (64)], [features.10.conv.3.running_mean -> (64)], [features.10.conv.3.running_var -> (64)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_84 for ONNX node: BatchNormalization_84
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 417 for ONNX tensor: 417
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_84 [BatchNormalization] outputs: [417 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_85 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 409
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 417
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_85 [Add] inputs: [409 -> (1, 64, 30, 40)], [417 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_85 for ONNX node: Add_85
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 418 for ONNX tensor: 418
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_85 [Add] outputs: [418 -> (1, 64, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_86 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 418
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_86 [Conv] inputs: [418 -> (1, 64, 30, 40)], [features.11.conv.0.0.weight -> (384, 64, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 64, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_86 for ONNX node: Conv_86
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 419 for ONNX tensor: 419
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_86 [Conv] outputs: [419 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_87 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 419
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_87 [BatchNormalization] inputs: [419 -> (1, 384, 30, 40)], [features.11.conv.0.1.weight -> (384)], [features.11.conv.0.1.bias -> (384)], [features.11.conv.0.1.running_mean -> (384)], [features.11.conv.0.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_87 for ONNX node: BatchNormalization_87
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 420 for ONNX tensor: 420
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_87 [BatchNormalization] outputs: [420 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_88 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 420
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_88 [Clip] inputs: [420 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_88 for ONNX node: Clip_88
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 421 for ONNX tensor: 421
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_88 [Clip] outputs: [421 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_89 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 421
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_89 [Conv] inputs: [421 -> (1, 384, 30, 40)], [features.11.conv.1.0.weight -> (384, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_89 for ONNX node: Conv_89
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 384
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 422 for ONNX tensor: 422
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_89 [Conv] outputs: [422 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_90 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 422
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_90 [BatchNormalization] inputs: [422 -> (1, 384, 30, 40)], [features.11.conv.1.1.weight -> (384)], [features.11.conv.1.1.bias -> (384)], [features.11.conv.1.1.running_mean -> (384)], [features.11.conv.1.1.running_var -> (384)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_90 for ONNX node: BatchNormalization_90
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 423 for ONNX tensor: 423
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_90 [BatchNormalization] outputs: [423 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_91 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 423
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_91 [Clip] inputs: [423 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_91 for ONNX node: Clip_91
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 424 for ONNX tensor: 424
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_91 [Clip] outputs: [424 -> (1, 384, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_92 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 424
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_92 [Conv] inputs: [424 -> (1, 384, 30, 40)], [features.11.conv.2.weight -> (96, 384, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 384, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_92 for ONNX node: Conv_92
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 425 for ONNX tensor: 425
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_92 [Conv] outputs: [425 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_93 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 425
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.11.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_93 [BatchNormalization] inputs: [425 -> (1, 96, 30, 40)], [features.11.conv.3.weight -> (96)], [features.11.conv.3.bias -> (96)], [features.11.conv.3.running_mean -> (96)], [features.11.conv.3.running_var -> (96)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_93 for ONNX node: BatchNormalization_93
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 426 for ONNX tensor: 426
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_93 [BatchNormalization] outputs: [426 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_94 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 426
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_94 [Conv] inputs: [426 -> (1, 96, 30, 40)], [features.12.conv.0.0.weight -> (576, 96, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_94 for ONNX node: Conv_94
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 427 for ONNX tensor: 427
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_94 [Conv] outputs: [427 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_95 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 427
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_95 [BatchNormalization] inputs: [427 -> (1, 576, 30, 40)], [features.12.conv.0.1.weight -> (576)], [features.12.conv.0.1.bias -> (576)], [features.12.conv.0.1.running_mean -> (576)], [features.12.conv.0.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_95 for ONNX node: BatchNormalization_95
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 428 for ONNX tensor: 428
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_95 [BatchNormalization] outputs: [428 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_96 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 428
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_96 [Clip] inputs: [428 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_96 for ONNX node: Clip_96
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 429 for ONNX tensor: 429
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_96 [Clip] outputs: [429 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_97 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 429
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_97 [Conv] inputs: [429 -> (1, 576, 30, 40)], [features.12.conv.1.0.weight -> (576, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_97 for ONNX node: Conv_97
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 430 for ONNX tensor: 430
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_97 [Conv] outputs: [430 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_98 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 430
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_98 [BatchNormalization] inputs: [430 -> (1, 576, 30, 40)], [features.12.conv.1.1.weight -> (576)], [features.12.conv.1.1.bias -> (576)], [features.12.conv.1.1.running_mean -> (576)], [features.12.conv.1.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_98 for ONNX node: BatchNormalization_98
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 431 for ONNX tensor: 431
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_98 [BatchNormalization] outputs: [431 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_99 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 431
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_99 [Clip] inputs: [431 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_99 for ONNX node: Clip_99
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 432 for ONNX tensor: 432
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_99 [Clip] outputs: [432 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_100 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 432
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_100 [Conv] inputs: [432 -> (1, 576, 30, 40)], [features.12.conv.2.weight -> (96, 576, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_100 for ONNX node: Conv_100
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 433 for ONNX tensor: 433
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_100 [Conv] outputs: [433 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_101 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 433
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.12.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_101 [BatchNormalization] inputs: [433 -> (1, 96, 30, 40)], [features.12.conv.3.weight -> (96)], [features.12.conv.3.bias -> (96)], [features.12.conv.3.running_mean -> (96)], [features.12.conv.3.running_var -> (96)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_101 for ONNX node: BatchNormalization_101
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 434 for ONNX tensor: 434
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_101 [BatchNormalization] outputs: [434 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_102 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 426
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 434
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_102 [Add] inputs: [426 -> (1, 96, 30, 40)], [434 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_102 for ONNX node: Add_102
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 435 for ONNX tensor: 435
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_102 [Add] outputs: [435 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_103 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 435
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_103 [Conv] inputs: [435 -> (1, 96, 30, 40)], [features.13.conv.0.0.weight -> (576, 96, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_103 for ONNX node: Conv_103
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 436 for ONNX tensor: 436
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_103 [Conv] outputs: [436 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_104 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 436
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_104 [BatchNormalization] inputs: [436 -> (1, 576, 30, 40)], [features.13.conv.0.1.weight -> (576)], [features.13.conv.0.1.bias -> (576)], [features.13.conv.0.1.running_mean -> (576)], [features.13.conv.0.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_104 for ONNX node: BatchNormalization_104
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 437 for ONNX tensor: 437
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_104 [BatchNormalization] outputs: [437 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_105 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 437
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_105 [Clip] inputs: [437 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_105 for ONNX node: Clip_105
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 438 for ONNX tensor: 438
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_105 [Clip] outputs: [438 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_106 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 438
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_106 [Conv] inputs: [438 -> (1, 576, 30, 40)], [features.13.conv.1.0.weight -> (576, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_106 for ONNX node: Conv_106
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 439 for ONNX tensor: 439
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_106 [Conv] outputs: [439 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_107 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 439
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_107 [BatchNormalization] inputs: [439 -> (1, 576, 30, 40)], [features.13.conv.1.1.weight -> (576)], [features.13.conv.1.1.bias -> (576)], [features.13.conv.1.1.running_mean -> (576)], [features.13.conv.1.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_107 for ONNX node: BatchNormalization_107
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 440 for ONNX tensor: 440
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_107 [BatchNormalization] outputs: [440 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_108 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 440
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_108 [Clip] inputs: [440 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_108 for ONNX node: Clip_108
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 441 for ONNX tensor: 441
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_108 [Clip] outputs: [441 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_109 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 441
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_109 [Conv] inputs: [441 -> (1, 576, 30, 40)], [features.13.conv.2.weight -> (96, 576, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_109 for ONNX node: Conv_109
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 96
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 442 for ONNX tensor: 442
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_109 [Conv] outputs: [442 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_110 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 442
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.13.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_110 [BatchNormalization] inputs: [442 -> (1, 96, 30, 40)], [features.13.conv.3.weight -> (96)], [features.13.conv.3.bias -> (96)], [features.13.conv.3.running_mean -> (96)], [features.13.conv.3.running_var -> (96)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_110 for ONNX node: BatchNormalization_110
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 443 for ONNX tensor: 443
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_110 [BatchNormalization] outputs: [443 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_111 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 435
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 443
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_111 [Add] inputs: [435 -> (1, 96, 30, 40)], [443 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_111 for ONNX node: Add_111
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 444 for ONNX tensor: 444
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_111 [Add] outputs: [444 -> (1, 96, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_112 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 444
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_112 [Conv] inputs: [444 -> (1, 96, 30, 40)], [features.14.conv.0.0.weight -> (576, 96, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 96, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_112 for ONNX node: Conv_112
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 445 for ONNX tensor: 445
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_112 [Conv] outputs: [445 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_113 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 445
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_113 [BatchNormalization] inputs: [445 -> (1, 576, 30, 40)], [features.14.conv.0.1.weight -> (576)], [features.14.conv.0.1.bias -> (576)], [features.14.conv.0.1.running_mean -> (576)], [features.14.conv.0.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_113 for ONNX node: BatchNormalization_113
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 446 for ONNX tensor: 446
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_113 [BatchNormalization] outputs: [446 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_114 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 446
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_114 [Clip] inputs: [446 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_114 for ONNX node: Clip_114
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 447 for ONNX tensor: 447
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_114 [Clip] outputs: [447 -> (1, 576, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_115 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 447
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_115 [Conv] inputs: [447 -> (1, 576, 30, 40)], [features.14.conv.1.0.weight -> (576, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 30, 40)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_115 for ONNX node: Conv_115
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (2, 2), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 576
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 576, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 448 for ONNX tensor: 448
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_115 [Conv] outputs: [448 -> (1, 576, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_116 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 448
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_116 [BatchNormalization] inputs: [448 -> (1, 576, 15, 20)], [features.14.conv.1.1.weight -> (576)], [features.14.conv.1.1.bias -> (576)], [features.14.conv.1.1.running_mean -> (576)], [features.14.conv.1.1.running_var -> (576)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_116 for ONNX node: BatchNormalization_116
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 449 for ONNX tensor: 449
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_116 [BatchNormalization] outputs: [449 -> (1, 576, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_117 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 449
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_117 [Clip] inputs: [449 -> (1, 576, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_117 for ONNX node: Clip_117
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 450 for ONNX tensor: 450
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_117 [Clip] outputs: [450 -> (1, 576, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_118 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 450
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_118 [Conv] inputs: [450 -> (1, 576, 15, 20)], [features.14.conv.2.weight -> (160, 576, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 576, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_118 for ONNX node: Conv_118
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 451 for ONNX tensor: 451
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_118 [Conv] outputs: [451 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_119 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 451
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.14.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_119 [BatchNormalization] inputs: [451 -> (1, 160, 15, 20)], [features.14.conv.3.weight -> (160)], [features.14.conv.3.bias -> (160)], [features.14.conv.3.running_mean -> (160)], [features.14.conv.3.running_var -> (160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_119 for ONNX node: BatchNormalization_119
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 452 for ONNX tensor: 452
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_119 [BatchNormalization] outputs: [452 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_120 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 452
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_120 [Conv] inputs: [452 -> (1, 160, 15, 20)], [features.15.conv.0.0.weight -> (960, 160, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_120 for ONNX node: Conv_120
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 453 for ONNX tensor: 453
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_120 [Conv] outputs: [453 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_121 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 453
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_121 [BatchNormalization] inputs: [453 -> (1, 960, 15, 20)], [features.15.conv.0.1.weight -> (960)], [features.15.conv.0.1.bias -> (960)], [features.15.conv.0.1.running_mean -> (960)], [features.15.conv.0.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_121 for ONNX node: BatchNormalization_121
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 454 for ONNX tensor: 454
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_121 [BatchNormalization] outputs: [454 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_122 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 454
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_122 [Clip] inputs: [454 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_122 for ONNX node: Clip_122
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 455 for ONNX tensor: 455
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_122 [Clip] outputs: [455 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_123 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 455
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_123 [Conv] inputs: [455 -> (1, 960, 15, 20)], [features.15.conv.1.0.weight -> (960, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_123 for ONNX node: Conv_123
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 456 for ONNX tensor: 456
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_123 [Conv] outputs: [456 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_124 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 456
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_124 [BatchNormalization] inputs: [456 -> (1, 960, 15, 20)], [features.15.conv.1.1.weight -> (960)], [features.15.conv.1.1.bias -> (960)], [features.15.conv.1.1.running_mean -> (960)], [features.15.conv.1.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_124 for ONNX node: BatchNormalization_124
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 457 for ONNX tensor: 457
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_124 [BatchNormalization] outputs: [457 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_125 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 457
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_125 [Clip] inputs: [457 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_125 for ONNX node: Clip_125
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 458 for ONNX tensor: 458
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_125 [Clip] outputs: [458 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_126 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 458
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_126 [Conv] inputs: [458 -> (1, 960, 15, 20)], [features.15.conv.2.weight -> (160, 960, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_126 for ONNX node: Conv_126
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 459 for ONNX tensor: 459
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_126 [Conv] outputs: [459 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_127 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 459
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.15.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_127 [BatchNormalization] inputs: [459 -> (1, 160, 15, 20)], [features.15.conv.3.weight -> (160)], [features.15.conv.3.bias -> (160)], [features.15.conv.3.running_mean -> (160)], [features.15.conv.3.running_var -> (160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_127 for ONNX node: BatchNormalization_127
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 460 for ONNX tensor: 460
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_127 [BatchNormalization] outputs: [460 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_128 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 452
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 460
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_128 [Add] inputs: [452 -> (1, 160, 15, 20)], [460 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_128 for ONNX node: Add_128
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 461 for ONNX tensor: 461
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_128 [Add] outputs: [461 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_129 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 461
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_129 [Conv] inputs: [461 -> (1, 160, 15, 20)], [features.16.conv.0.0.weight -> (960, 160, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_129 for ONNX node: Conv_129
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 462 for ONNX tensor: 462
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_129 [Conv] outputs: [462 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_130 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 462
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_130 [BatchNormalization] inputs: [462 -> (1, 960, 15, 20)], [features.16.conv.0.1.weight -> (960)], [features.16.conv.0.1.bias -> (960)], [features.16.conv.0.1.running_mean -> (960)], [features.16.conv.0.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_130 for ONNX node: BatchNormalization_130
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 463 for ONNX tensor: 463
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_130 [BatchNormalization] outputs: [463 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_131 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 463
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_131 [Clip] inputs: [463 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_131 for ONNX node: Clip_131
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 464 for ONNX tensor: 464
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_131 [Clip] outputs: [464 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_132 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 464
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_132 [Conv] inputs: [464 -> (1, 960, 15, 20)], [features.16.conv.1.0.weight -> (960, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_132 for ONNX node: Conv_132
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 465 for ONNX tensor: 465
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_132 [Conv] outputs: [465 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_133 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 465
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_133 [BatchNormalization] inputs: [465 -> (1, 960, 15, 20)], [features.16.conv.1.1.weight -> (960)], [features.16.conv.1.1.bias -> (960)], [features.16.conv.1.1.running_mean -> (960)], [features.16.conv.1.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_133 for ONNX node: BatchNormalization_133
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 466 for ONNX tensor: 466
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_133 [BatchNormalization] outputs: [466 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_134 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 466
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_134 [Clip] inputs: [466 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_134 for ONNX node: Clip_134
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 467 for ONNX tensor: 467
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_134 [Clip] outputs: [467 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_135 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 467
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_135 [Conv] inputs: [467 -> (1, 960, 15, 20)], [features.16.conv.2.weight -> (160, 960, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_135 for ONNX node: Conv_135
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 160
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 468 for ONNX tensor: 468
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_135 [Conv] outputs: [468 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_136 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 468
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.16.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_136 [BatchNormalization] inputs: [468 -> (1, 160, 15, 20)], [features.16.conv.3.weight -> (160)], [features.16.conv.3.bias -> (160)], [features.16.conv.3.running_mean -> (160)], [features.16.conv.3.running_var -> (160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_136 for ONNX node: BatchNormalization_136
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 469 for ONNX tensor: 469
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_136 [BatchNormalization] outputs: [469 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Add_137 [Add]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 461
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 469
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Add_137 [Add] inputs: [461 -> (1, 160, 15, 20)], [469 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Add_137 for ONNX node: Add_137
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 470 for ONNX tensor: 470
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Add_137 [Add] outputs: [470 -> (1, 160, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_138 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 470
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.0.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_138 [Conv] inputs: [470 -> (1, 160, 15, 20)], [features.17.conv.0.0.weight -> (960, 160, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 160, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_138 for ONNX node: Conv_138
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 471 for ONNX tensor: 471
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_138 [Conv] outputs: [471 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_139 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 471
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.0.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.0.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.0.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.0.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_139 [BatchNormalization] inputs: [471 -> (1, 960, 15, 20)], [features.17.conv.0.1.weight -> (960)], [features.17.conv.0.1.bias -> (960)], [features.17.conv.0.1.running_mean -> (960)], [features.17.conv.0.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_139 for ONNX node: BatchNormalization_139
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 472 for ONNX tensor: 472
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_139 [BatchNormalization] outputs: [472 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_140 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 472
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_140 [Clip] inputs: [472 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_140 for ONNX node: Clip_140
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 473 for ONNX tensor: 473
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_140 [Clip] outputs: [473 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_141 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 473
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.1.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_141 [Conv] inputs: [473 -> (1, 960, 15, 20)], [features.17.conv.1.0.weight -> (960, 1, 3, 3)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_141 for ONNX node: Conv_141
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (3, 3), strides: (1, 1), prepadding: (1, 1), postpadding: (1, 1), dilations: (1, 1), numOutputs: 960
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 474 for ONNX tensor: 474
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_141 [Conv] outputs: [474 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_142 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 474
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.1.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.1.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.1.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.1.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_142 [BatchNormalization] inputs: [474 -> (1, 960, 15, 20)], [features.17.conv.1.1.weight -> (960)], [features.17.conv.1.1.bias -> (960)], [features.17.conv.1.1.running_mean -> (960)], [features.17.conv.1.1.running_var -> (960)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_142 for ONNX node: BatchNormalization_142
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 475 for ONNX tensor: 475
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_142 [BatchNormalization] outputs: [475 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_143 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 475
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_143 [Clip] inputs: [475 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_143 for ONNX node: Clip_143
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 476 for ONNX tensor: 476
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_143 [Clip] outputs: [476 -> (1, 960, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_144 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 476
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.2.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_144 [Conv] inputs: [476 -> (1, 960, 15, 20)], [features.17.conv.2.weight -> (320, 960, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 960, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_144 for ONNX node: Conv_144
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 320
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 320, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 477 for ONNX tensor: 477
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_144 [Conv] outputs: [477 -> (1, 320, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_145 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 477
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.3.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.3.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.17.conv.3.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_145 [BatchNormalization] inputs: [477 -> (1, 320, 15, 20)], [features.17.conv.3.weight -> (320)], [features.17.conv.3.bias -> (320)], [features.17.conv.3.running_mean -> (320)], [features.17.conv.3.running_var -> (320)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_145 for ONNX node: BatchNormalization_145
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 478 for ONNX tensor: 478
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_145 [BatchNormalization] outputs: [478 -> (1, 320, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_146 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 478
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.18.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_146 [Conv] inputs: [478 -> (1, 320, 15, 20)], [features.18.0.weight -> (1280, 320, 1, 1)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 320, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_146 for ONNX node: Conv_146
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 1280
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 1280, 15, 20)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 479 for ONNX tensor: 479
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_146 [Conv] outputs: [479 -> (1, 1280, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_147 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 479
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.18.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.18.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.18.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: features.18.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_147 [BatchNormalization] inputs: [479 -> (1, 1280, 15, 20)], [features.18.1.weight -> (1280)], [features.18.1.bias -> (1280)], [features.18.1.running_mean -> (1280)], [features.18.1.running_var -> (1280)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_147 for ONNX node: BatchNormalization_147
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 480 for ONNX tensor: 480
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_147 [BatchNormalization] outputs: [480 -> (1, 1280, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Clip_148 [Clip]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 480
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Clip_148 [Clip] inputs: [480 -> (1, 1280, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Clip_148 for ONNX node: Clip_148
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 481 for ONNX tensor: 481
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Clip_148 [Clip] outputs: [481 -> (1, 1280, 15, 20)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: ConvTranspose_149 [ConvTranspose]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 481
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.0.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: ConvTranspose_149 [ConvTranspose] inputs: [481 -> (1, 1280, 15, 20)], [deconv_layers.0.weight -> (1280, 256, 4, 4)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:697: Running deconvolution with: 
Padding mode: NOTSET
Pre-padding: (1, 1)
Post-padding: (1, 1)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: ConvTranspose_149 for ONNX node: ConvTranspose_149
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 482 for ONNX tensor: 482
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: ConvTranspose_149 [ConvTranspose] outputs: [482 -> (1, 256, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_150 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 482
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.1.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.1.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.1.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.1.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_150 [BatchNormalization] inputs: [482 -> (1, 256, 30, 40)], [deconv_layers.1.weight -> (256)], [deconv_layers.1.bias -> (256)], [deconv_layers.1.running_mean -> (256)], [deconv_layers.1.running_var -> (256)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_150 for ONNX node: BatchNormalization_150
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 483 for ONNX tensor: 483
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_150 [BatchNormalization] outputs: [483 -> (1, 256, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Relu_151 [Relu]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 483
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Relu_151 [Relu] inputs: [483 -> (1, 256, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Relu_151 for ONNX node: Relu_151
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 484 for ONNX tensor: 484
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Relu_151 [Relu] outputs: [484 -> (1, 256, 30, 40)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: ConvTranspose_152 [ConvTranspose]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 484
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.3.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: ConvTranspose_152 [ConvTranspose] inputs: [484 -> (1, 256, 30, 40)], [deconv_layers.3.weight -> (256, 256, 4, 4)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:697: Running deconvolution with: 
Padding mode: NOTSET
Pre-padding: (1, 1)
Post-padding: (1, 1)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: ConvTranspose_152 for ONNX node: ConvTranspose_152
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 485 for ONNX tensor: 485
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: ConvTranspose_152 [ConvTranspose] outputs: [485 -> (1, 256, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_153 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 485
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.4.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.4.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.4.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.4.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_153 [BatchNormalization] inputs: [485 -> (1, 256, 60, 80)], [deconv_layers.4.weight -> (256)], [deconv_layers.4.bias -> (256)], [deconv_layers.4.running_mean -> (256)], [deconv_layers.4.running_var -> (256)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_153 for ONNX node: BatchNormalization_153
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 486 for ONNX tensor: 486
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_153 [BatchNormalization] outputs: [486 -> (1, 256, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Relu_154 [Relu]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 486
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Relu_154 [Relu] inputs: [486 -> (1, 256, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Relu_154 for ONNX node: Relu_154
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 487 for ONNX tensor: 487
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Relu_154 [Relu] outputs: [487 -> (1, 256, 60, 80)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: ConvTranspose_155 [ConvTranspose]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 487
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.6.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: ConvTranspose_155 [ConvTranspose] inputs: [487 -> (1, 256, 60, 80)], [deconv_layers.6.weight -> (256, 128, 4, 4)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:697: Running deconvolution with: 
Padding mode: NOTSET
Pre-padding: (1, 1)
Post-padding: (1, 1)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: ConvTranspose_155 for ONNX node: ConvTranspose_155
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 488 for ONNX tensor: 488
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: ConvTranspose_155 [ConvTranspose] outputs: [488 -> (1, 128, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: BatchNormalization_156 [BatchNormalization]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 488
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.7.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.7.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.7.running_mean
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: deconv_layers.7.running_var
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: BatchNormalization_156 [BatchNormalization] inputs: [488 -> (1, 128, 120, 160)], [deconv_layers.7.weight -> (128)], [deconv_layers.7.bias -> (128)], [deconv_layers.7.running_mean -> (128)], [deconv_layers.7.running_var -> (128)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: BatchNormalization_156 for ONNX node: BatchNormalization_156
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 489 for ONNX tensor: 489
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: BatchNormalization_156 [BatchNormalization] outputs: [489 -> (1, 128, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Relu_157 [Relu]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 489
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Relu_157 [Relu] inputs: [489 -> (1, 128, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Relu_157 for ONNX node: Relu_157
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: 490 for ONNX tensor: 490
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Relu_157 [Relu] outputs: [490 -> (1, 128, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:103: Parsing node: Conv_158 [Conv]
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: 490
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: final_layer.weight
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:119: Searching for input: final_layer.bias
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:125: Conv_158 [Conv] inputs: [490 -> (1, 128, 120, 160)], [final_layer.weight -> (21, 128, 1, 1)], [final_layer.bias -> (21)], 
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:450: Convolution input dimensions: (1, 128, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:141: Registering layer: Conv_158 for ONNX node: Conv_158
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:533: Using kernel: (1, 1), strides: (1, 1), prepadding: (0, 0), postpadding: (0, 0), dilations: (1, 1), numOutputs: 21
[10/13/2020-20:18:46] [V] [TRT] builtin_op_importers.cpp:534: Convolution output dimensions: (1, 21, 120, 160)
[10/13/2020-20:18:46] [V] [TRT] ImporterContext.hpp:116: Registering tensor: output_1 for ONNX tensor: output
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:179: Conv_158 [Conv] outputs: [output -> (1, 21, 120, 160)], 
[10/13/2020-20:18:46] [V] [TRT] ModelImporter.cpp:507: Marking output_1 as output: output
 ----- Parsing of ONNX model /media/nx091/Data/prashant/code/EfficientHandPose/models/checkpoint_256_256_128.onnx is Done ---- 
[10/13/2020-20:18:46] [V] [TRT] Applying generic optimizations to the graph for inference.
[10/13/2020-20:18:46] [V] [TRT] Original: 159 layers
[10/13/2020-20:18:46] [V] [TRT] After dead-layer removal: 159 layers
[10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_0 with scale BatchNormalization_1
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_3 with scale BatchNormalization_4
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_6 with scale BatchNormalization_7
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_8 with scale BatchNormalization_9
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_11 with scale BatchNormalization_12
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_14 with scale BatchNormalization_15
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_16 with scale BatchNormalization_17
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_19 with scale BatchNormalization_20
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_22 with scale BatchNormalization_23
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_25 with scale BatchNormalization_26
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_28 with scale BatchNormalization_29
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_31 with scale BatchNormalization_32
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_33 with scale BatchNormalization_34
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_36 with scale BatchNormalization_37
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_39 with scale BatchNormalization_40
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_42 with scale BatchNormalization_43
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_45 with scale BatchNormalization_46
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_48 with scale BatchNormalization_49
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_51 with scale BatchNormalization_52
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_54 with scale BatchNormalization_55
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_57 with scale BatchNormalization_58
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_59 with scale BatchNormalization_60
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_62 with scale BatchNormalization_63
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_65 with scale BatchNormalization_66
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_68 with scale BatchNormalization_69
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_71 with scale BatchNormalization_72
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_74 with scale BatchNormalization_75
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_77 with scale BatchNormalization_78
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_80 with scale BatchNormalization_81
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_83 with scale BatchNormalization_84
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_86 with scale BatchNormalization_87
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_89 with scale BatchNormalization_90
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_92 with scale BatchNormalization_93
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_94 with scale BatchNormalization_95
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_97 with scale BatchNormalization_98
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_100 with scale BatchNormalization_101
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_103 with scale BatchNormalization_104
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_106 with scale BatchNormalization_107
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_109 with scale BatchNormalization_110
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_112 with scale BatchNormalization_113
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_115 with scale BatchNormalization_116
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_118 with scale BatchNormalization_119
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_120 with scale BatchNormalization_121
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_126 with scale BatchNormalization_127
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_129 with scale BatchNormalization_130
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_135 with scale BatchNormalization_136
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_138 with scale BatchNormalization_139
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_144 with scale BatchNormalization_145
[10/13/2020-20:18:47] [V] [TRT] Fusing convolution weights from Conv_146 with scale BatchNormalization_147
[10/13/2020-20:18:47] [V] [TRT] After DLA optimization: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After Myelin optimization: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After scale fusion: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After vertical fusions: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After final dead-layer removal: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After tensor merging: 15 layers
[10/13/2020-20:18:47] [V] [TRT] After concat removal: 15 layers
[10/13/2020-20:18:47] [V] [TRT] Graph construction and optimization completed in 1.04614 seconds.
[10/13/2020-20:18:47] [I] [TRT] 
[10/13/2020-20:18:47] [I] [TRT] --------------- Layers running on DLA: 
[10/13/2020-20:18:47] [I] [TRT] {Conv_0,BatchNormalization_1,Clip_2,Conv_3,BatchNormalization_4,Clip_5,Conv_6,BatchNormalization_7,Conv_8,BatchNormalization_9,Clip_10,Conv_11,BatchNormalization_12,Clip_13,Conv_14,BatchNormalization_15,Conv_16,BatchNormalization_17,Clip_18,Conv_19,BatchNormalization_20,Clip_21,Conv_22,BatchNormalization_23,Add_24,Conv_25,BatchNormalization_26,Clip_27,Conv_28,BatchNormalization_29,Clip_30,Conv_31,BatchNormalization_32,Conv_33,BatchNormalization_34,Clip_35,Conv_36,BatchNormalization_37,Clip_38,Conv_39,BatchNormalization_40,Add_41,Conv_42,BatchNormalization_43,Clip_44,Conv_45,BatchNormalization_46,Clip_47,Conv_48,BatchNormalization_49,Add_50,Conv_51,BatchNormalization_52,Clip_53,Conv_54,BatchNormalization_55,Clip_56,Conv_57,BatchNormalization_58,Conv_59,BatchNormalization_60,Clip_61,Conv_62,BatchNormalization_63,Clip_64,Conv_65,BatchNormalization_66,Add_67,Conv_68,BatchNormalization_69,Clip_70,Conv_71,BatchNormalization_72,Clip_73,Conv_74,BatchNormalization_75,Add_76,Conv_77,BatchNormalization_78,Clip_79,Conv_80,BatchNormalization_81,Clip_82,Conv_83,BatchNormalization_84,Add_85,Conv_86,BatchNormalization_87,Clip_88,Conv_89,BatchNormalization_90,Clip_91,Conv_92,BatchNormalization_93,Conv_94,BatchNormalization_95,Clip_96,Conv_97,BatchNormalization_98,Clip_99,Conv_100,BatchNormalization_101,Add_102,Conv_103,BatchNormalization_104,Clip_105,Conv_106,BatchNormalization_107,Clip_108,Conv_109,BatchNormalization_110,Add_111,Conv_112,BatchNormalization_113,Clip_114,Conv_115,BatchNormalization_116,Clip_117,Conv_118,BatchNormalization_119,Conv_120,BatchNormalization_121,Clip_122}, {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131}, {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140}, {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148}, {BatchNormalization_150,Relu_151}, {BatchNormalization_153,Relu_154}, {BatchNormalization_156,Relu_157,Conv_158}, 
[10/13/2020-20:18:47] [I] [TRT] --------------- Layers running on GPU: 
[10/13/2020-20:18:47] [I] [TRT] Conv_123, Conv_132, Conv_141, ConvTranspose_149, ConvTranspose_152, ConvTranspose_155, 
[10/13/2020-20:18:49] [V] [TRT] Constructing optimization profile number 0 [1/1].
[10/13/2020-20:18:49] [V] [TRT] --------------- Timing Runner: input to nvm (Reformat)
[10/13/2020-20:18:49] [V] [TRT] Tactic: 1002 time 4.5874
[10/13/2020-20:18:49] [V] [TRT] Tactic: 0 time 0.204248
[10/13/2020-20:18:49] [V] [TRT] Fastest Tactic: 0 Time: 0.204248
[10/13/2020-20:18:49] [V] [TRT] --------------- Timing Runner: input to nvm (Reformat)
[10/13/2020-20:18:49] [V] [TRT] Tactic: 1002 time 2.55815
[10/13/2020-20:18:50] [V] [TRT] Tactic: 0 time 3.76096
[10/13/2020-20:18:50] [V] [TRT] Fastest Tactic: 1002 Time: 2.55815
[10/13/2020-20:18:50] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:18:50] [V] [TRT] Tactic: 1002 time 2.24745
[10/13/2020-20:18:50] [V] [TRT] Tactic: 0 time 4.35355
[10/13/2020-20:18:50] [V] [TRT] Fastest Tactic: 1002 Time: 2.24745
[10/13/2020-20:18:50] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:18:50] [V] [TRT] Tactic: 1002 time 2.08289
[10/13/2020-20:18:50] [V] [TRT] Tactic: 0 time 0.381484
[10/13/2020-20:18:50] [V] [TRT] Fastest Tactic: 0 Time: 0.381484
[10/13/2020-20:18:50] [V] [TRT] *************** Autotuning format combination: Half(1,640,1:4,307200) -> Half(1,20,300:16,3000), Half(1,20,300:16,18000) ***************
[10/13/2020-20:18:50] [V] [TRT] --------------- Timing Runner: {Conv_0,BatchNormalization_1,Clip_2,Conv_3,BatchNormalization_4,Clip_5,Conv_6,BatchNormalization_7,Conv_8,BatchNormalization_9,Clip_10,Conv_11,BatchNormalization_12,Clip_13,Conv_14,BatchNormalization_15,Conv_16,BatchNormalization_17,Clip_18,Conv_19,BatchNormalization_20,Clip_21,Conv_22,BatchNormalization_23,Add_24,Conv_25,BatchNormalization_26,Clip_27,Conv_28,BatchNormalization_29,Clip_30,Conv_31,BatchNormalization_32,Conv_33,BatchNormalization_34,Clip_35,Conv_36,BatchNormalization_37,Clip_38,Conv_39,BatchNormalization_40,Add_41,Conv_42,BatchNormalization_43,Clip_44,Conv_45,BatchNormalization_46,Clip_47,Conv_48,BatchNormalization_49,Add_50,Conv_51,BatchNormalization_52,Clip_53,Conv_54,BatchNormalization_55,Clip_56,Conv_57,BatchNormalization_58,Conv_59,BatchNormalization_60,Clip_61,Conv_62,BatchNormalization_63,Clip_64,Conv_65,BatchNormalization_66,Add_67,Conv_68,BatchNormalization_69,Clip_70,Conv_71,BatchNormalization_72,Clip_73,Conv_74,BatchNormalization_75,Add_76,Conv_77,BatchNormalization_78,Clip_79,Conv_80,BatchNormalization_81,Clip_82,Conv_83,BatchNormalization_84,Add_85,Conv_86,BatchNormalization_87,Clip_88,Conv_89,BatchNormalization_90,Clip_91,Conv_92,BatchNormalization_93,Conv_94,BatchNormalization_95,Clip_96,Conv_97,BatchNormalization_98,Clip_99,Conv_100,BatchNormalization_101,Add_102,Conv_103,BatchNormalization_104,Clip_105,Conv_106,BatchNormalization_107,Clip_108,Conv_109,BatchNormalization_110,Add_111,Conv_112,BatchNormalization_113,Clip_114,Conv_115,BatchNormalization_116,Clip_117,Conv_118,BatchNormalization_119,Conv_120,BatchNormalization_121,Clip_122} (DLA)
[10/13/2020-20:18:59] [V] [TRT] Tactic: 549229989443 time 0.270632
[10/13/2020-20:19:00] [V] [TRT] Fastest Tactic: 549229989443 Time: 0.270632
[10/13/2020-20:19:00] [V] [TRT] *************** Autotuning format combination: Half(1,640,307200:16,307200) -> Half(1,20,300:16,3000), Half(1,20,300:16,18000) ***************
[10/13/2020-20:19:00] [V] [TRT] --------------- Timing Runner: {Conv_0,BatchNormalization_1,Clip_2,Conv_3,BatchNormalization_4,Clip_5,Conv_6,BatchNormalization_7,Conv_8,BatchNormalization_9,Clip_10,Conv_11,BatchNormalization_12,Clip_13,Conv_14,BatchNormalization_15,Conv_16,BatchNormalization_17,Clip_18,Conv_19,BatchNormalization_20,Clip_21,Conv_22,BatchNormalization_23,Add_24,Conv_25,BatchNormalization_26,Clip_27,Conv_28,BatchNormalization_29,Clip_30,Conv_31,BatchNormalization_32,Conv_33,BatchNormalization_34,Clip_35,Conv_36,BatchNormalization_37,Clip_38,Conv_39,BatchNormalization_40,Add_41,Conv_42,BatchNormalization_43,Clip_44,Conv_45,BatchNormalization_46,Clip_47,Conv_48,BatchNormalization_49,Add_50,Conv_51,BatchNormalization_52,Clip_53,Conv_54,BatchNormalization_55,Clip_56,Conv_57,BatchNormalization_58,Conv_59,BatchNormalization_60,Clip_61,Conv_62,BatchNormalization_63,Clip_64,Conv_65,BatchNormalization_66,Add_67,Conv_68,BatchNormalization_69,Clip_70,Conv_71,BatchNormalization_72,Clip_73,Conv_74,BatchNormalization_75,Add_76,Conv_77,BatchNormalization_78,Clip_79,Conv_80,BatchNormalization_81,Clip_82,Conv_83,BatchNormalization_84,Add_85,Conv_86,BatchNormalization_87,Clip_88,Conv_89,BatchNormalization_90,Clip_91,Conv_92,BatchNormalization_93,Conv_94,BatchNormalization_95,Clip_96,Conv_97,BatchNormalization_98,Clip_99,Conv_100,BatchNormalization_101,Add_102,Conv_103,BatchNormalization_104,Clip_105,Conv_106,BatchNormalization_107,Clip_108,Conv_109,BatchNormalization_110,Add_111,Conv_112,BatchNormalization_113,Clip_114,Conv_115,BatchNormalization_116,Clip_117,Conv_118,BatchNormalization_119,Conv_120,BatchNormalization_121,Clip_122} (DLA)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 549229989443 time 1.25364
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 549229989443 Time: 1.25364
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 2.08152
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.4813
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.4813
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 1.79049
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.250468
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.250468
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.460276
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.31426
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.31426
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.20928
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.355072
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.20928
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.470796
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.150784
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.150784
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.216696
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.332796
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 1002 Time: 0.216696
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.473212
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.148996
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.148996
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.457344
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.142196
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.142196
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.462464
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.111752
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.111752
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 1.17274
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.272508
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.272508
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 1.05625
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.250388
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.250388
[10/13/2020-20:19:11] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:11] [V] [TRT] Tactic: 1002 time 0.45878
[10/13/2020-20:19:11] [V] [TRT] Tactic: 0 time 0.313484
[10/13/2020-20:19:11] [V] [TRT] Fastest Tactic: 0 Time: 0.313484
[10/13/2020-20:19:11] [V] [TRT] *************** Autotuning format combination: Float(1,20,300,288000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_medium_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn_winograd) Set Tactic Name: volta_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_xregs_large_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_small_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_xregs_large_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_small_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_medium_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x32_relu_medium_nn_v1
[10/13/2020-20:19:11] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x32_relu_small_nn_v1
[10/13/2020-20:19:12] [V] [TRT] --------------- Timing Runner: Conv_123 (FusedConvActConvolution)
[10/13/2020-20:19:12] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:12] [V] [TRT] --------------- Timing Runner: Conv_123 (CaskConvolution)
[10/13/2020-20:19:12] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_medium_nn_v1
[10/13/2020-20:19:12] [V] [TRT] Tactic: 1825138533642645384 time 15.4161
[10/13/2020-20:19:12] [V] [TRT] Conv_123 (scudnn_winograd) Set Tactic Name: volta_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1
[10/13/2020-20:19:12] [V] [TRT] Tactic: 2775507031594384867 time 9.91375
[10/13/2020-20:19:12] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_xregs_large_nn_v1
[10/13/2020-20:19:12] [V] [TRT] Tactic: 2842488832350522458 time 13.5044
[10/13/2020-20:19:12] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_small_nn_v1
[10/13/2020-20:19:13] [V] [TRT] Tactic: 3915320020053085238 time 15.3704
[10/13/2020-20:19:13] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x128_relu_xregs_large_nn_v1
[10/13/2020-20:19:13] [V] [TRT] Tactic: 6448355332020552203 time 15.1745
[10/13/2020-20:19:13] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_small_nn_v1
[10/13/2020-20:19:13] [V] [TRT] Tactic: 6808617066150061604 time 13.5901
[10/13/2020-20:19:13] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x64_relu_medium_nn_v1
[10/13/2020-20:19:14] [V] [TRT] Tactic: -8060443123034038864 time 13.6701
[10/13/2020-20:19:14] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x32_relu_medium_nn_v1
[10/13/2020-20:19:14] [V] [TRT] Tactic: -4420849921117327522 time 10.1447
[10/13/2020-20:19:14] [V] [TRT] Conv_123 (scudnn) Set Tactic Name: volta_scudnn_128x32_relu_small_nn_v1
[10/13/2020-20:19:14] [V] [TRT] Tactic: -3946921629105938337 time 12.3349
[10/13/2020-20:19:14] [V] [TRT] Fastest Tactic: 2775507031594384867 Time: 9.91375
[10/13/2020-20:19:14] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaConvolution)
[10/13/2020-20:19:15] [V] [TRT] Tactic: 0 time 0.095936
[10/13/2020-20:19:15] [V] [TRT] Tactic: 2 time 0.096036
[10/13/2020-20:19:16] [V] [TRT] Tactic: 5 time 55.9064
[10/13/2020-20:19:16] [V] [TRT] Tactic: 6 time 8.01804
[10/13/2020-20:19:16] [V] [TRT] Tactic: 57 time 0.092904
[10/13/2020-20:19:16] [V] [TRT] Fastest Tactic: 57 Time: 0.092904
[10/13/2020-20:19:16] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaDepthwiseConvolution)
[10/13/2020-20:19:16] [V] [TRT] Tactic: -1 time 0.121812
[10/13/2020-20:19:16] [V] [TRT] Fastest Tactic: -1 Time: 0.121812
[10/13/2020-20:19:16] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaConvolution Tactic: 57
[10/13/2020-20:19:16] [V] [TRT] 
[10/13/2020-20:19:16] [V] [TRT] *************** Autotuning format combination: Half(1,20,300,288000) -> Half(1,20,300,288000) ***************
[10/13/2020-20:19:16] [V] [TRT] --------------- Timing Runner: Conv_123 (FusedConvActConvolution)
[10/13/2020-20:19:16] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:16] [V] [TRT] --------------- Timing Runner: Conv_123 (CaskConvolution)
[10/13/2020-20:19:16] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:16] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaConvolution)
[10/13/2020-20:19:16] [V] [TRT] Tactic: 0 time 0.035332
[10/13/2020-20:19:16] [V] [TRT] Tactic: 1 time 0.035212
[10/13/2020-20:19:16] [V] [TRT] Tactic: 2 time 0.103168
[10/13/2020-20:19:17] [V] [TRT] Tactic: 4 time 30.2369
[10/13/2020-20:19:18] [V] [TRT] Tactic: 5 time 56.5406
[10/13/2020-20:19:19] [V] [TRT] Tactic: 6 time 54.3378
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1 Time: 0.035212
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaDepthwiseConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaConvolution Tactic: 1
[10/13/2020-20:19:19] [V] [TRT] 
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (FusedConvActConvolution)
[10/13/2020-20:19:19] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CaskConvolution)
[10/13/2020-20:19:19] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaDepthwiseConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Half(120,2400,1:8,36000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (FusedConvActConvolution)
[10/13/2020-20:19:19] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CaskConvolution)
[10/13/2020-20:19:19] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_123 (CudaDepthwiseConvolution)
[10/13/2020-20:19:19] [V] [TRT] Tactic: -2 time 0.047456
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: -2 Time: 0.047456
[10/13/2020-20:19:19] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaDepthwiseConvolution Tactic: -2
[10/13/2020-20:19:19] [V] [TRT] 
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.066428
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.069944
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.066428
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.09728
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.042968
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.042968
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.0974
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.12326
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.0974
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.075848
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.064496
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.064496
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.097564
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.034332
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.034332
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.097572
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.1226
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.097572
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.0956
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.042788
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.042788
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.095504
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.031392
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.031392
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.09928
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.152684
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.09928
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.097444
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.123524
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.097444
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.097384
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.122796
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.097384
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.099176
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.152548
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.099176
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(1,20,300:16,18000), Half(1,20,300:16,3000) -> Half(1,20,300:16,3000), Half(1,20,300:16,18000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} (DLA)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Float(1,20,300,288000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(1,20,300,288000) -> Half(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_132 (FusedConvActConvolution)
[10/13/2020-20:19:19] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_132 (CaskConvolution)
[10/13/2020-20:19:19] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_132 (CudaConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_132 (CudaDepthwiseConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Half(120,2400,1:8,36000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(1,20,300:16,18000), Half(1,20,300:16,3000) -> Half(1,20,300:16,18000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} (DLA)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Float(1,20,300,288000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(1,20,300,288000) -> Half(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Float(1,20,300,288000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_141 (FusedConvActConvolution)
[10/13/2020-20:19:19] [V] [TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_141 (CaskConvolution)
[10/13/2020-20:19:19] [V] [TRT] CaskConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_141 (CudaConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: Conv_141 (CudaDepthwiseConvolution)
[10/13/2020-20:19:19] [V] [TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(120,2400,1:8,36000) -> Half(120,2400,1:8,36000) ***************
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Half(1,20,300:16,18000) -> Half(1,20,300:16,24000) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} (DLA)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.293872
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.073628
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.073628
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.293492
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.066136
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.066136
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.153704
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.044932
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.044932
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.117464
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.07994
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.07994
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.088428
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.089212
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 1002 Time: 0.088428
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.164972
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.056048
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.056048
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.125768
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.056496
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.056496
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.096252
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.083588
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.083588
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.163672
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.046008
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.046008
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.126712
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.044352
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.044352
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.308188
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.062836
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.062836
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.309964
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.045348
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.045348
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.124868
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.04656
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.04656
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.1252
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.056196
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.056196
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.122944
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.040584
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.040584
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.177796
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.038156
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.038156
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.293112
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.07348
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.07348
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.294684
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.066168
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.066168
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.153668
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.044352
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.044352
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:19] [V] [TRT] Tactic: 1002 time 0.118672
[10/13/2020-20:19:19] [V] [TRT] Tactic: 0 time 0.080028
[10/13/2020-20:19:19] [V] [TRT] Fastest Tactic: 0 Time: 0.080028
[10/13/2020-20:19:19] [V] [TRT] *************** Autotuning format combination: Float(1,20,300,384000) -> Float(1,40,1200,307200) ***************
[10/13/2020-20:19:19] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CudnnDeconvolution)
[10/13/2020-20:19:20] [V] [TRT] Tactic: 0 time 18.9769
[10/13/2020-20:19:21] [V] [TRT] Tactic: 1 time 59.3505
[10/13/2020-20:19:21] [V] [TRT] Fastest Tactic: 0 Time: 18.9769
[10/13/2020-20:19:21] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CaskDeconvolution)
[10/13/2020-20:19:21] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:21] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (GemmDeconvolution)
[10/13/2020-20:19:21] [V] [TRT] Tactic: 0 time 5.46919
[10/13/2020-20:19:21] [V] [TRT] Fastest Tactic: 0 Time: 5.46919
[10/13/2020-20:19:21] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:21] [V] [TRT] 
[10/13/2020-20:19:21] [V] [TRT] *************** Autotuning format combination: Half(1,20,300,384000) -> Half(1,40,1200,307200) ***************
[10/13/2020-20:19:21] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CudnnDeconvolution)
[10/13/2020-20:19:22] [V] [TRT] Tactic: 0 time 48.3939
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1 time 59.4361
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 48.3939
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CaskDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (GemmDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 4.99417
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 4.99417
[10/13/2020-20:19:23] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:23] [V] [TRT] 
[10/13/2020-20:19:23] [V] [TRT] *************** Autotuning format combination: Half(1,20,300:2,192000) -> Half(1,40,1200:2,153600) ***************
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CudnnDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CaskDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (GemmDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] GemmDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] *************** Autotuning format combination: Half(160,3200,1:8,48000) -> Half(32,1280,1:8,38400) ***************
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CudnnDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (CaskDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: ConvTranspose_149 (GemmDeconvolution)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.949184
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.949184
[10/13/2020-20:19:23] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:23] [V] [TRT] 
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.069964
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.073344
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.069964
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.132912
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.045444
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.045444
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097256
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.046644
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.046644
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.09754
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.132692
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.09754
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.0807
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.06872
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.06872
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.135976
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.038052
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.038052
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.098396
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.03692
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.03692
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097224
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.131184
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.097224
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.162556
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.051572
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.051572
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.169072
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.036992
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.036992
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.096992
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.038144
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.038144
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097076
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.069188
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.069188
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097612
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.045656
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.045656
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.096488
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.031768
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.031768
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.141416
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.031656
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.031656
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.09722
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.159728
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.09722
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.098744
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.13156
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.098744
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097072
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.131184
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.097072
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.096728
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.068996
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.068996
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.097424
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.160912
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.097424
[10/13/2020-20:19:23] [V] [TRT] *************** Autotuning format combination: Half(1,40,1200:16,19200) -> Half(1,40,1200:16,19200) ***************
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: {BatchNormalization_150,Relu_151} (DLA)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.1531
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.06358
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.06358
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.15586
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.05546
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.05546
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.127036
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.036488
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.036488
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.090892
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.06524
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 0 Time: 0.06524
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:23] [V] [TRT] Tactic: 1002 time 0.070684
[10/13/2020-20:19:23] [V] [TRT] Tactic: 0 time 0.074136
[10/13/2020-20:19:23] [V] [TRT] Fastest Tactic: 1002 Time: 0.070684
[10/13/2020-20:19:23] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.132456
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.045684
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.045684
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.09728
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.046636
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.046636
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.079484
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.068284
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.068284
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.132816
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.037872
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.037872
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.097832
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.036716
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.036716
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.163572
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.05256
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.05256
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.16882
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.036976
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.036976
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.096908
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.038128
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.038128
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.098948
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.044
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.044
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.097536
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.031632
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.031632
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.140664
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.03094
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.03094
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.156808
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.062684
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.062684
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.153768
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.05594
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.05594
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.126596
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.036712
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.036712
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 1002 time 0.091272
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 0.066064
[10/13/2020-20:19:24] [V] [TRT] Fastest Tactic: 0 Time: 0.066064
[10/13/2020-20:19:24] [V] [TRT] *************** Autotuning format combination: Float(1,40,1200,307200) -> Float(1,80,4800,1228800) ***************
[10/13/2020-20:19:24] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CudnnDeconvolution)
[10/13/2020-20:19:24] [V] [TRT] Tactic: 0 time 27.93
[10/13/2020-20:19:25] [V] [TRT] Tactic: 1 time 20.3537
[10/13/2020-20:19:25] [V] [TRT] Fastest Tactic: 1 Time: 20.3537
[10/13/2020-20:19:25] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CaskDeconvolution)
[10/13/2020-20:19:25] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:25] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (GemmDeconvolution)
[10/13/2020-20:19:25] [V] [TRT] Tactic: 0 time 3.98565
[10/13/2020-20:19:25] [V] [TRT] Fastest Tactic: 0 Time: 3.98565
[10/13/2020-20:19:25] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:25] [V] [TRT] 
[10/13/2020-20:19:25] [V] [TRT] *************** Autotuning format combination: Half(1,40,1200,307200) -> Half(1,80,4800,1228800) ***************
[10/13/2020-20:19:25] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CudnnDeconvolution)
[10/13/2020-20:19:26] [V] [TRT] Tactic: 0 time 87.1455
[10/13/2020-20:19:26] [V] [TRT] Tactic: 1 time 20.6503
[10/13/2020-20:19:26] [V] [TRT] Fastest Tactic: 1 Time: 20.6503
[10/13/2020-20:19:26] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CaskDeconvolution)
[10/13/2020-20:19:26] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:26] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (GemmDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 3.74694
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 3.74694
[10/13/2020-20:19:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:27] [V] [TRT] 
[10/13/2020-20:19:27] [V] [TRT] *************** Autotuning format combination: Half(1,40,1200:2,153600) -> Half(1,80,4800:2,614400) ***************
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CudnnDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CaskDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (GemmDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] GemmDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:27] [V] [TRT] *************** Autotuning format combination: Half(32,1280,1:8,38400) -> Half(32,2560,1:8,153600) ***************
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CudnnDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (CaskDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: ConvTranspose_152 (GemmDeconvolution)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.782052
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.782052
[10/13/2020-20:19:27] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:27] [V] [TRT] 
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.259916
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.261904
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.259916
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.476652
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.162676
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.162676
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.346104
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.160952
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.160952
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.352792
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.523852
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.352792
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.301456
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.253212
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.253212
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.475428
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.132576
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.132576
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.350612
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.124568
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.124568
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.351496
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.52066
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.351496
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.579112
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.18238
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.18238
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.57778
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.130768
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.130768
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.348432
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.129072
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.129072
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.346244
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.272732
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.272732
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.353356
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.1671
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.1671
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.34624
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.110868
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.110868
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.523724
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.107768
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.107768
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.357244
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 1.5525
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.357244
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.350672
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.523052
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.350672
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.348936
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.523084
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.348936
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.3443
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.272528
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.272528
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.355284
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 1.55238
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.355284
[10/13/2020-20:19:27] [V] [TRT] *************** Autotuning format combination: Half(1,80,4800:16,76800) -> Half(1,80,4800:16,76800) ***************
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: {BatchNormalization_153,Relu_154} (DLA)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.579416
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.246324
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.246324
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.568848
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.227596
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.227596
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.46132
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.145788
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.145788
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.327736
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.240676
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.240676
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.260752
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.261936
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 1002 Time: 0.260752
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.481928
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.162572
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.162572
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.347896
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.163116
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.163116
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.301228
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.253304
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.253304
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.482748
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.132788
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.132788
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.349608
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.124988
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.124988
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.580952
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.185848
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.185848
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.581164
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.13092
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.13092
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.34832
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.12894
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.12894
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:27] [V] [TRT] Tactic: 1002 time 0.353888
[10/13/2020-20:19:27] [V] [TRT] Tactic: 0 time 0.167416
[10/13/2020-20:19:27] [V] [TRT] Fastest Tactic: 0 Time: 0.167416
[10/13/2020-20:19:27] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.349716
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.115772
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.115772
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.520724
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.11146
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.11146
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.581988
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.246748
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.246748
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.58672
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.227676
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.227676
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.463992
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.1463
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.1463
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 1002 time 0.328148
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 0.240264
[10/13/2020-20:19:28] [V] [TRT] Fastest Tactic: 0 Time: 0.240264
[10/13/2020-20:19:28] [V] [TRT] *************** Autotuning format combination: Float(1,80,4800,1228800) -> Float(1,160,19200,2457600) ***************
[10/13/2020-20:19:28] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CudnnDeconvolution)
[10/13/2020-20:19:28] [V] [TRT] Tactic: 0 time 36.1402
[10/13/2020-20:19:29] [V] [TRT] Tactic: 1 time 37.9105
[10/13/2020-20:19:29] [V] [TRT] Fastest Tactic: 0 Time: 36.1402
[10/13/2020-20:19:29] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CaskDeconvolution)
[10/13/2020-20:19:29] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:29] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (GemmDeconvolution)
[10/13/2020-20:19:29] [V] [TRT] Tactic: 0 skipped. Scratch requested: 30357504, available: 16777216
[10/13/2020-20:19:29] [I] [TRT] Some tactics do not have sufficient workspace memory to run. Increasing workspace size may increase performance, please check verbose output.
[10/13/2020-20:19:29] [V] [TRT] Fastest Tactic: -3360065831133338131 Time: 3.40282e+38
[10/13/2020-20:19:29] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudnnDeconvolution Tactic: 0
[10/13/2020-20:19:29] [V] [TRT] 
[10/13/2020-20:19:29] [V] [TRT] *************** Autotuning format combination: Half(1,80,4800,1228800) -> Half(1,160,19200,2457600) ***************
[10/13/2020-20:19:29] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CudnnDeconvolution)
[10/13/2020-20:19:32] [V] [TRT] Tactic: 0 time 187.91
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1 time 39.2082
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 1 Time: 39.2082
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CaskDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (GemmDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 7.81634
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 7.81634
[10/13/2020-20:19:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:33] [V] [TRT] 
[10/13/2020-20:19:33] [V] [TRT] *************** Autotuning format combination: Half(1,80,4800:2,614400) -> Half(1,160,19200:2,1228800) ***************
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CudnnDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CaskDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (GemmDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] GemmDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] *************** Autotuning format combination: Half(32,2560,1:8,153600) -> Half(16,2560,1:8,307200) ***************
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CudnnDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] CudnnDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (CaskDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] CaskDeconvolution has no valid tactics for this config, skipping
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: ConvTranspose_155 (GemmDeconvolution)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 1.5302
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 1.5302
[10/13/2020-20:19:33] [V] [TRT] >>>>>>>>>>>>>>> Chose Runner Type: GemmDeconvolution Tactic: 0
[10/13/2020-20:19:33] [V] [TRT] 
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.514808
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.51188
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.51188
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 1.06961
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.320916
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.320916
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.656188
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.3187
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.3187
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.656868
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 2.0298
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.656868
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.611704
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.498008
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.498008
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 1.06559
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.267176
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.267176
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.66006
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.241968
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.241968
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.663248
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 1.9869
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.663248
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 1.17596
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.333124
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.333124
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 1.16684
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.249504
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.249504
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.6509
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.254428
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.254428
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.653212
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 1.02103
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 1002 Time: 0.653212
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.671192
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.325564
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.325564
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.65926
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.211124
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.211124
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 1.06685
[10/13/2020-20:19:33] [V] [TRT] Tactic: 0 time 0.210452
[10/13/2020-20:19:33] [V] [TRT] Fastest Tactic: 0 Time: 0.210452
[10/13/2020-20:19:33] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:33] [V] [TRT] Tactic: 1002 time 0.673844
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 4.11334
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.673844
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 1002 time 0.65754
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 2.03167
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.65754
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 1002 time 0.66212
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 1.90454
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.66212
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 1002 time 0.652916
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 1.03513
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.652916
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: <reformat> (Reformat)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 1002 time 0.673492
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 4.2003
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.673492
[10/13/2020-20:19:34] [V] [TRT] *************** Autotuning format combination: Half(1,160,19200:16,153600) -> Half(1,160,19200:16,38400) ***************
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: {BatchNormalization_156,Relu_157,Conv_158} (DLA)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 549229989443 is the only option, timing skipped
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 549229989443 Time: 0
[10/13/2020-20:19:34] [V] [TRT] --------------- Timing Runner: output from nvm (Reformat)
[10/13/2020-20:19:34] [V] [TRT] Tactic: 1002 time 0.23924
[10/13/2020-20:19:34] [V] [TRT] Tactic: 0 time 0.281644
[10/13/2020-20:19:34] [V] [TRT] Fastest Tactic: 1002 Time: 0.23924
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: Conv_123 reformatted input 0 (455) from Half(1,20,300:16,18000) to Half(1,20,300,288000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0 (456) from Half(1,20,300,288000) to Half(1,20,300:16,18000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: Conv_132 reformatted input 0 (464) from Half(1,20,300:16,18000) to Half(1,20,300,288000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0 (465) from Half(1,20,300,288000) to Half(1,20,300:16,18000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: Conv_141 reformatted input 0 (473) from Half(1,20,300:16,18000) to Half(1,20,300,288000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0 (474) from Half(1,20,300,288000) to Half(1,20,300:16,18000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0 (481) from Half(160,3200,1:8,48000) to Half(1,20,300:16,24000)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: ConvTranspose_149 output to be reformatted 0 (482) from Half(1,40,1200:16,19200) to Half(32,1280,1:8,38400)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_150,Relu_151} output to be reformatted 0 (484) from Half(32,1280,1:8,38400) to Half(1,40,1200:16,19200)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_153,Relu_154} reformatted input 0 (485) from Half(32,2560,1:8,153600) to Half(1,80,4800:16,76800)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: ConvTranspose_155 reformatted input 0 (487) from Half(1,80,4800:16,76800) to Half(32,2560,1:8,153600)
[10/13/2020-20:19:34] [V] [TRT] Adding reformat layer: {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0 (488) from Half(16,2560,1:8,307200) to Half(1,160,19200:16,153600)
[10/13/2020-20:19:34] [V] [TRT] Formats and tactics selection completed in 44.5567 seconds.
[10/13/2020-20:19:34] [V] [TRT] After reformat layers: 43 layers
[10/13/2020-20:19:34] [V] [TRT] Block size 16777216
[10/13/2020-20:19:34] [V] [TRT] Block size 4915200
[10/13/2020-20:19:34] [V] [TRT] Block size 4915200
[10/13/2020-20:19:34] [V] [TRT] Total Activation Memory: 26607616
[10/13/2020-20:19:34] [I] [TRT] Detected 1 inputs and 1 output network tensors.
[10/13/2020-20:19:43] [V] [TRT] Layer: input to nvm Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {Conv_0,BatchNormalization_1,Clip_2,Conv_3,BatchNormalization_4,Clip_5,Conv_6,BatchNormalization_7,Conv_8,BatchNormalization_9,Clip_10,Conv_11,BatchNormalization_12,Clip_13,Conv_14,BatchNormalization_15,Conv_16,BatchNormalization_17,Clip_18,Conv_19,BatchNormalization_20,Clip_21,Conv_22,BatchNormalization_23,Add_24,Conv_25,BatchNormalization_26,Clip_27,Conv_28,BatchNormalization_29,Clip_30,Conv_31,BatchNormalization_32,Conv_33,BatchNormalization_34,Clip_35,Conv_36,BatchNormalization_37,Clip_38,Conv_39,BatchNormalization_40,Add_41,Conv_42,BatchNormalization_43,Clip_44,Conv_45,BatchNormalization_46,Clip_47,Conv_48,BatchNormalization_49,Add_50,Conv_51,BatchNormalization_52,Clip_53,Conv_54,BatchNormalization_55,Clip_56,Conv_57,BatchNormalization_58,Conv_59,BatchNormalization_60,Clip_61,Conv_62,BatchNormalization_63,Clip_64,Conv_65,BatchNormalization_66,Add_67,Conv_68,BatchNormalization_69,Clip_70,Conv_71,BatchNormalization_72,Clip_73,Conv_74,BatchNormalization_75,Add_76,Conv_77,BatchNormalization_78,Clip_79,Conv_80,BatchNormalization_81,Clip_82,Conv_83,BatchNormalization_84,Add_85,Conv_86,BatchNormalization_87,Clip_88,Conv_89,BatchNormalization_90,Clip_91,Conv_92,BatchNormalization_93,Conv_94,BatchNormalization_95,Clip_96,Conv_97,BatchNormalization_98,Clip_99,Conv_100,BatchNormalization_101,Add_102,Conv_103,BatchNormalization_104,Clip_105,Conv_106,BatchNormalization_107,Clip_108,Conv_109,BatchNormalization_110,Add_111,Conv_112,BatchNormalization_113,Clip_114,Conv_115,BatchNormalization_116,Clip_117,Conv_118,BatchNormalization_119,Conv_120,BatchNormalization_121,Clip_122} Weights: 0 HostPersistent: 888 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: input copy finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_123 input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 455 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_123 Weights: 17280 HostPersistent: 8 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} Weights: 0 HostPersistent: 912 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 452 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_132 input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 464 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_132 Weights: 17280 HostPersistent: 8 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} Weights: 0 HostPersistent: 888 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 461 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_141 input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 473 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: Conv_141 Weights: 17280 HostPersistent: 8 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} Weights: 0 HostPersistent: 864 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: ConvTranspose_149 Weights: 10485760 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: ConvTranspose_149 output reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_150,Relu_151} Weights: 0 HostPersistent: 864 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 482 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_150,Relu_151} output reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_150,Relu_151} output to be reformatted 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: ConvTranspose_152 Weights: 2097152 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_153,Relu_154} input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_153,Relu_154} Weights: 0 HostPersistent: 864 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_153,Relu_154} reformatted input 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: ConvTranspose_155 input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: 487 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: ConvTranspose_155 Weights: 1048576 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_156,Relu_157,Conv_158} input reformatter 0 Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_156,Relu_157,Conv_158} Weights: 0 HostPersistent: 864 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0 finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: output from nvm Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Layer: output copy finish Weights: 0 HostPersistent: 0 DevicePersistent: 0
[10/13/2020-20:19:43] [V] [TRT] Total Host Persistent Memory: 6168
[10/13/2020-20:19:43] [V] [TRT] Total Device Persistent Memory: 0
[10/13/2020-20:19:43] [V] [TRT] Total Weight Memory: 13683328
[10/13/2020-20:19:43] [V] [TRT] Builder timing cache: created 149 entries, 54 hit(s)
[10/13/2020-20:19:43] [V] [TRT] Engine generation completed in 56.3844 seconds.
[10/13/2020-20:19:43] [V] [TRT] Engine Layer Information:
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): input to nvm, Tactic: 0, input[Float(3,480,640)] -> input copy[Half(3,480,640)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {Conv_0,BatchNormalization_1,Clip_2,Conv_3,BatchNormalization_4,Clip_5,Conv_6,BatchNormalization_7,Conv_8,BatchNormalization_9,Clip_10,Conv_11,BatchNormalization_12,Clip_13,Conv_14,BatchNormalization_15,Conv_16,BatchNormalization_17,Clip_18,Conv_19,BatchNormalization_20,Clip_21,Conv_22,BatchNormalization_23,Add_24,Conv_25,BatchNormalization_26,Clip_27,Conv_28,BatchNormalization_29,Clip_30,Conv_31,BatchNormalization_32,Conv_33,BatchNormalization_34,Clip_35,Conv_36,BatchNormalization_37,Clip_38,Conv_39,BatchNormalization_40,Add_41,Conv_42,BatchNormalization_43,Clip_44,Conv_45,BatchNormalization_46,Clip_47,Conv_48,BatchNormalization_49,Add_50,Conv_51,BatchNormalization_52,Clip_53,Conv_54,BatchNormalization_55,Clip_56,Conv_57,BatchNormalization_58,Conv_59,BatchNormalization_60,Clip_61,Conv_62,BatchNormalization_63,Clip_64,Conv_65,BatchNormalization_66,Add_67,Conv_68,BatchNormalization_69,Clip_70,Conv_71,BatchNormalization_72,Clip_73,Conv_74,BatchNormalization_75,Add_76,Conv_77,BatchNormalization_78,Clip_79,Conv_80,BatchNormalization_81,Clip_82,Conv_83,BatchNormalization_84,Add_85,Conv_86,BatchNormalization_87,Clip_88,Conv_89,BatchNormalization_90,Clip_91,Conv_92,BatchNormalization_93,Conv_94,BatchNormalization_95,Clip_96,Conv_97,BatchNormalization_98,Clip_99,Conv_100,BatchNormalization_101,Add_102,Conv_103,BatchNormalization_104,Clip_105,Conv_106,BatchNormalization_107,Clip_108,Conv_109,BatchNormalization_110,Add_111,Conv_112,BatchNormalization_113,Clip_114,Conv_115,BatchNormalization_116,Clip_117,Conv_118,BatchNormalization_119,Conv_120,BatchNormalization_121,Clip_122}, Tactic: 549229989443, input copy[Half(3,480,640)] -> 452[Half(160,15,20)], 455[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): input copy finish, Tactic: 0, input copy[Half(3,480,640)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): Conv_123 input reformatter 0, Tactic: 0, 455[Half(960,15,20)] -> Conv_123 reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 455 finish, Tactic: 0, 455[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Convolution): Conv_123, Tactic: 1, Conv_123 reformatted input 0[Half(960,15,20)] -> 456[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} input reformatter 0, Tactic: 1002, 456[Half(960,15,20)] -> {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131}, Tactic: 549229989443, {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0[Half(960,15,20)], 452[Half(160,15,20)] -> 461[Half(160,15,20)], 464[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0 finish, Tactic: 0, {BatchNormalization_124,Clip_125,Conv_126,BatchNormalization_127,Add_128,Conv_129,BatchNormalization_130,Clip_131} reformatted input 0[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 452 finish, Tactic: 0, 452[Half(160,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): Conv_132 input reformatter 0, Tactic: 0, 464[Half(960,15,20)] -> Conv_132 reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 464 finish, Tactic: 0, 464[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Convolution): Conv_132, Tactic: 1, Conv_132 reformatted input 0[Half(960,15,20)] -> 465[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} input reformatter 0, Tactic: 1002, 465[Half(960,15,20)] -> {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140}, Tactic: 549229989443, {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0[Half(960,15,20)], 461[Half(160,15,20)] -> 473[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0 finish, Tactic: 0, {BatchNormalization_133,Clip_134,Conv_135,BatchNormalization_136,Add_137,Conv_138,BatchNormalization_139,Clip_140} reformatted input 0[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 461 finish, Tactic: 0, 461[Half(160,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): Conv_141 input reformatter 0, Tactic: 0, 473[Half(960,15,20)] -> Conv_141 reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 473 finish, Tactic: 0, 473[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Convolution): Conv_141, Tactic: 1, Conv_141 reformatted input 0[Half(960,15,20)] -> 474[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} input reformatter 0, Tactic: 1002, 474[Half(960,15,20)] -> {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0[Half(960,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148}, Tactic: 549229989443, {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0[Half(960,15,20)] -> {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0[Half(1280,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0 finish, Tactic: 0, {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} reformatted input 0[Half(960,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output reformatter 0, Tactic: 0, {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0[Half(1280,15,20)] -> 481[Half(1280,15,20)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0 finish, Tactic: 0, {BatchNormalization_142,Clip_143,Conv_144,BatchNormalization_145,Conv_146,BatchNormalization_147,Clip_148} output to be reformatted 0[Half(1280,15,20)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(gemmDeconvolution): ConvTranspose_149, Tactic: 0, 481[Half(1280,15,20)] -> ConvTranspose_149 output to be reformatted 0[Half(256,30,40)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): ConvTranspose_149 output reformatter 0, Tactic: 1002, ConvTranspose_149 output to be reformatted 0[Half(256,30,40)] -> 482[Half(256,30,40)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_150,Relu_151}, Tactic: 549229989443, 482[Half(256,30,40)] -> {BatchNormalization_150,Relu_151} output to be reformatted 0[Half(256,30,40)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 482 finish, Tactic: 0, 482[Half(256,30,40)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_150,Relu_151} output reformatter 0, Tactic: 0, {BatchNormalization_150,Relu_151} output to be reformatted 0[Half(256,30,40)] -> 484[Half(256,30,40)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_150,Relu_151} output to be reformatted 0 finish, Tactic: 0, {BatchNormalization_150,Relu_151} output to be reformatted 0[Half(256,30,40)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(gemmDeconvolution): ConvTranspose_152, Tactic: 0, 484[Half(256,30,40)] -> 485[Half(256,60,80)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_153,Relu_154} input reformatter 0, Tactic: 1002, 485[Half(256,60,80)] -> {BatchNormalization_153,Relu_154} reformatted input 0[Half(256,60,80)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_153,Relu_154}, Tactic: 549229989443, {BatchNormalization_153,Relu_154} reformatted input 0[Half(256,60,80)] -> 487[Half(256,60,80)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_153,Relu_154} reformatted input 0 finish, Tactic: 0, {BatchNormalization_153,Relu_154} reformatted input 0[Half(256,60,80)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): ConvTranspose_155 input reformatter 0, Tactic: 0, 487[Half(256,60,80)] -> ConvTranspose_155 reformatted input 0[Half(256,60,80)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): 487 finish, Tactic: 0, 487[Half(256,60,80)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(gemmDeconvolution): ConvTranspose_155, Tactic: 0, ConvTranspose_155 reformatted input 0[Half(256,60,80)] -> 488[Half(128,120,160)]
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): {BatchNormalization_156,Relu_157,Conv_158} input reformatter 0, Tactic: 1002, 488[Half(128,120,160)] -> {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0[Half(128,120,160)]
[10/13/2020-20:19:43] [V] [TRT] Layer(DLANative): {BatchNormalization_156,Relu_157,Conv_158}, Tactic: 549229989443, {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0[Half(128,120,160)] -> output copy[Half(21,120,160)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0 finish, Tactic: 0, {BatchNormalization_156,Relu_157,Conv_158} reformatted input 0[Half(128,120,160)] -> 
[10/13/2020-20:19:43] [V] [TRT] Layer(Reformat): output from nvm, Tactic: 1002, output copy[Half(21,120,160)] -> output[Float(21,120,160)]
[10/13/2020-20:19:43] [V] [TRT] Layer(FinishNvmRegion): output copy finish, Tactic: 0, output copy[Half(21,120,160)] -> 
[10/13/2020-20:19:44] [I] Starting inference threads
[10/13/2020-20:19:47] [I] Warmup completed 0 queries over 200 ms
[10/13/2020-20:19:47] [I] Timing trace has 0 queries over 3.12065 s
[10/13/2020-20:19:47] [I] Trace averages of 25000 runs:
[10/13/2020-20:19:47] [I] Host Latency
[10/13/2020-20:19:47] [I] min: 45.1609 ms (end to end 45.1703 ms)
[10/13/2020-20:19:47] [I] max: 50.1166 ms (end to end 50.4858 ms)
[10/13/2020-20:19:47] [I] mean: 45.7969 ms (end to end 45.8902 ms)
[10/13/2020-20:19:47] [I] median: 45.3002 ms (end to end 45.3124 ms)
[10/13/2020-20:19:47] [I] percentile: 50.1166 ms at 99% (end to end 50.4858 ms at 99%)
[10/13/2020-20:19:47] [I] throughput: 0 qps
[10/13/2020-20:19:47] [I] walltime: 3.12065 s
[10/13/2020-20:19:47] [I] Enqueue Time
[10/13/2020-20:19:47] [I] min: 3.87842 ms
[10/13/2020-20:19:47] [I] max: 11.6349 ms
[10/13/2020-20:19:47] [I] median: 5.198 ms
[10/13/2020-20:19:47] [I] GPU Compute
[10/13/2020-20:19:47] [I] min: 44.6669 ms
[10/13/2020-20:19:47] [I] max: 49.6149 ms
[10/13/2020-20:19:47] [I] mean: 45.2998 ms
[10/13/2020-20:19:47] [I] median: 44.8051 ms
[10/13/2020-20:19:47] [I] percentile: 49.6149 ms at 99%
[10/13/2020-20:19:47] [I] total compute time: 3.08039 s