Hi Dusty,
Did comment out the line you mentioned and rebuild and collected the logs. Logs shared below…
How to attach the log file here?
Regarding the accuracy of the model: I think accuracy will be very low since I run training for 5 epochs only. how to get the accuracy of the model?
The logs:-
jetbot@jetbot-desktop:~/jetson-inference/python/training/classification$ python3.6 imagenet-console.py --model=/home/jetbot/shankar/resnet18.onnx --input_blob=input_0 --output_blob=output_0 --labels=/home/jetbot/datasets/cat_dog_limited/labels.txt /home/jetbot/datasets/cat_dog_limited/test/02.jpg cat.jpg
jetson.inference.init.py
jetson.inference – initializing Python 3.6 bindings…
jetson.inference – registering module types…
jetson.inference – done registering module types
jetson.inference – done Python 3.6 binding initialization
jetson.utils.init.py
jetson.utils – initializing Python 3.6 bindings…
jetson.utils – registering module functions…
jetson.utils – done registering module functions
jetson.utils – registering module types…
jetson.utils – done registering module types
jetson.utils – done Python 3.6 binding initialization
[image] loaded ‘/home/jetbot/datasets/cat_dog_limited/test/02.jpg’ (620 x 410, 1 channels)
Image loaded is: 620 X 410
jetson.inference – PyTensorNet_New()
jetson.inference – PyImageNet_Init()
jetson.inference – imageNet loading network using argv command line params
jetson.inference – imageNet.init() argv[0] = ‘imagenet-console.py’
jetson.inference – imageNet.init() argv[1] = ‘–model=/home/jetbot/shankar/resnet18.onnx’
jetson.inference – imageNet.init() argv[2] = ‘–input_blob=input_0’
jetson.inference – imageNet.init() argv[3] = ‘–output_blob=output_0’
jetson.inference – imageNet.init() argv[4] = ‘–labels=/home/jetbot/datasets/cat_dog_limited/labels.txt’
jetson.inference – imageNet.init() argv[5] = ‘/home/jetbot/datasets/cat_dog_limited/test/02.jpg’
jetson.inference – imageNet.init() argv[6] = ‘cat.jpg’
imageNet – loading classification network model from:
– prototxt (null)
– model /home/jetbot/shankar/resnet18.onnx
– class_labels /home/jetbot/datasets/cat_dog_limited/labels.txt
– input_blob ‘input_0’
– output_blob ‘output_0’
– batch_size 1
[TRT] TensorRT version 6.0.1
[TRT] loading NVIDIA plugins…
[TRT] Plugin Creator registration succeeded - GridAnchor_TRT
[TRT] Plugin Creator registration succeeded - GridAnchorRect_TRT
[TRT] Plugin Creator registration succeeded - NMS_TRT
[TRT] Plugin Creator registration succeeded - Reorg_TRT
[TRT] Plugin Creator registration succeeded - Region_TRT
[TRT] Plugin Creator registration succeeded - Clip_TRT
[TRT] Plugin Creator registration succeeded - LReLU_TRT
[TRT] Plugin Creator registration succeeded - PriorBox_TRT
[TRT] Plugin Creator registration succeeded - Normalize_TRT
[TRT] Plugin Creator registration succeeded - RPROI_TRT
[TRT] Plugin Creator registration succeeded - BatchedNMS_TRT
[TRT] Could not register plugin creator: FlattenConcat_TRT in namespace:
[TRT] completed loading NVIDIA plugins.
[TRT] detected model format - ONNX (extension ‘.onnx’)
[TRT] desired precision specified for GPU: FASTEST
[TRT] requested fasted precision for device GPU without providing valid calibrator, disabling INT8
[TRT] native precisions detected for GPU: FP32, FP16
[TRT] selecting fastest native precision for GPU: FP16
[TRT] attempting to open engine cache file /home/jetbot/shankar/resnet18.onnx.1.1.GPU.FP16.engine
[TRT] cache file not found, profiling network model on device GPU
[TRT] device GPU, loading /usr/bin/ /home/jetbot/shankar/resnet18.onnx
Input filename: /home/jetbot/shankar/resnet18.onnx
ONNX IR version: 0.0.4
Opset version: 9
Producer name: pytorch
Producer version: 1.2
Domain:
Model version: 0
Doc string:
WARNING: ONNX model has a newer ir_version (0.0.4) than this parser was built against (0.0.3).
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (3, 224, 224)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (7, 7), strides: (2, 2), padding: (3, 3), dilations: (1, 1), numOutputs: 64
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (64, 112, 112)
[TRT] 123:Conv → (64, 112, 112)
[TRT] 124:BatchNormalization → (64, 112, 112)
[TRT] 125:Relu → (64, 112, 112)
[TRT] 126:MaxPool → (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 64
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (64, 56, 56)
[TRT] 127:Conv → (64, 56, 56)
[TRT] 128:BatchNormalization → (64, 56, 56)
[TRT] 129:Relu → (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 64
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (64, 56, 56)
[TRT] 130:Conv → (64, 56, 56)
[TRT] 131:BatchNormalization → (64, 56, 56)
[TRT] 132:Add → (64, 56, 56)
[TRT] 133:Relu → (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 64
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (64, 56, 56)
[TRT] 134:Conv → (64, 56, 56)
[TRT] 135:BatchNormalization → (64, 56, 56)
[TRT] 136:Relu → (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 64
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (64, 56, 56)
[TRT] 137:Conv → (64, 56, 56)
[TRT] 138:BatchNormalization → (64, 56, 56)
[TRT] 139:Add → (64, 56, 56)
[TRT] 140:Relu → (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (2, 2), padding: (1, 1), dilations: (1, 1), numOutputs: 128
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (128, 28, 28)
[TRT] 141:Conv → (128, 28, 28)
[TRT] 142:BatchNormalization → (128, 28, 28)
[TRT] 143:Relu → (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 128
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (128, 28, 28)
[TRT] 144:Conv → (128, 28, 28)
[TRT] 145:BatchNormalization → (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (64, 56, 56)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (1, 1), strides: (2, 2), padding: (0, 0), dilations: (1, 1), numOutputs: 128
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (128, 28, 28)
[TRT] 146:Conv → (128, 28, 28)
[TRT] 147:BatchNormalization → (128, 28, 28)
[TRT] 148:Add → (128, 28, 28)
[TRT] 149:Relu → (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 128
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (128, 28, 28)
[TRT] 150:Conv → (128, 28, 28)
[TRT] 151:BatchNormalization → (128, 28, 28)
[TRT] 152:Relu → (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 128
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (128, 28, 28)
[TRT] 153:Conv → (128, 28, 28)
[TRT] 154:BatchNormalization → (128, 28, 28)
[TRT] 155:Add → (128, 28, 28)
[TRT] 156:Relu → (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (2, 2), padding: (1, 1), dilations: (1, 1), numOutputs: 256
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (256, 14, 14)
[TRT] 157:Conv → (256, 14, 14)
[TRT] 158:BatchNormalization → (256, 14, 14)
[TRT] 159:Relu → (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 256
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (256, 14, 14)
[TRT] 160:Conv → (256, 14, 14)
[TRT] 161:BatchNormalization → (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (128, 28, 28)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (1, 1), strides: (2, 2), padding: (0, 0), dilations: (1, 1), numOutputs: 256
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (256, 14, 14)
[TRT] 162:Conv → (256, 14, 14)
[TRT] 163:BatchNormalization → (256, 14, 14)
[TRT] 164:Add → (256, 14, 14)
[TRT] 165:Relu → (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 256
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (256, 14, 14)
[TRT] 166:Conv → (256, 14, 14)
[TRT] 167:BatchNormalization → (256, 14, 14)
[TRT] 168:Relu → (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 256
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (256, 14, 14)
[TRT] 169:Conv → (256, 14, 14)
[TRT] 170:BatchNormalization → (256, 14, 14)
[TRT] 171:Add → (256, 14, 14)
[TRT] 172:Relu → (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (2, 2), padding: (1, 1), dilations: (1, 1), numOutputs: 512
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (512, 7, 7)
[TRT] 173:Conv → (512, 7, 7)
[TRT] 174:BatchNormalization → (512, 7, 7)
[TRT] 175:Relu → (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 512
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (512, 7, 7)
[TRT] 176:Conv → (512, 7, 7)
[TRT] 177:BatchNormalization → (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (256, 14, 14)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (1, 1), strides: (2, 2), padding: (0, 0), dilations: (1, 1), numOutputs: 512
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (512, 7, 7)
[TRT] 178:Conv → (512, 7, 7)
[TRT] 179:BatchNormalization → (512, 7, 7)
[TRT] 180:Add → (512, 7, 7)
[TRT] 181:Relu → (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 512
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (512, 7, 7)
[TRT] 182:Conv → (512, 7, 7)
[TRT] 183:BatchNormalization → (512, 7, 7)
[TRT] 184:Relu → (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:773: Convolution input dimensions: (512, 7, 7)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:840: Using kernel: (3, 3), strides: (1, 1), padding: (1, 1), dilations: (1, 1), numOutputs: 512
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:841: Convolution output dimensions: (512, 7, 7)
[TRT] 185:Conv → (512, 7, 7)
[TRT] 186:BatchNormalization → (512, 7, 7)
[TRT] 187:Add → (512, 7, 7)
[TRT] 188:Relu → (512, 7, 7)
[TRT] 189:GlobalAveragePool → (512, 1, 1)
[TRT] 190:Flatten → (512)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:1094: GEMM: A: (512), B: (512, 2), C: (2)
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:1131: Using opA: 2 opB: 0
[TRT] /home/jenkins/workspace/TensorRT/helpers/rel-6.0/L1_Nightly/build/source/parsers/onnxOpenSource/builtin_op_importers.cpp:1132: GEMM: A, after squeezing: (512)
[TRT] 191:Gemm → (2)
[TRT] output_0:Softmax → (2)
[TRT] retrieved Input tensor “input_0”: 3x224x224
[TRT] device GPU, configuring CUDA engine
[TRT] device GPU, building FP16: ON
[TRT] device GPU, building INT8: OFF
[TRT] device GPU, building CUDA engine (this may take a few minutes the first time a network is loaded)
[TRT] Applying generic optimizations to the graph for inference.
[TRT] Original: 73 layers
[TRT] After dead-layer removal: 73 layers
[TRT] Fusing convolution weights from (Unnamed Layer* 0) [Convolution] with scale (Unnamed Layer* 1) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 4) [Convolution] with scale (Unnamed Layer* 5) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 7) [Convolution] with scale (Unnamed Layer* 8) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 11) [Convolution] with scale (Unnamed Layer* 12) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 14) [Convolution] with scale (Unnamed Layer* 15) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 18) [Convolution] with scale (Unnamed Layer* 19) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 21) [Convolution] with scale (Unnamed Layer* 22) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 23) [Convolution] with scale (Unnamed Layer* 24) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 27) [Convolution] with scale (Unnamed Layer* 28) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 30) [Convolution] with scale (Unnamed Layer* 31) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 34) [Convolution] with scale (Unnamed Layer* 35) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 37) [Convolution] with scale (Unnamed Layer* 38) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 39) [Convolution] with scale (Unnamed Layer* 40) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 43) [Convolution] with scale (Unnamed Layer* 44) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 46) [Convolution] with scale (Unnamed Layer* 47) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 50) [Convolution] with scale (Unnamed Layer* 51) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 53) [Convolution] with scale (Unnamed Layer* 54) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 55) [Convolution] with scale (Unnamed Layer* 56) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 59) [Convolution] with scale (Unnamed Layer* 60) [Scale]
[TRT] Fusing convolution weights from (Unnamed Layer* 62) [Convolution] with scale (Unnamed Layer* 63) [Scale]
[TRT] After scale fusion: 53 layers
[TRT] Fusing (Unnamed Layer* 0) [Convolution] with (Unnamed Layer* 2) [Activation]
[TRT] Fusing (Unnamed Layer* 4) [Convolution] with (Unnamed Layer* 6) [Activation]
[TRT] Fusing (Unnamed Layer* 7) [Convolution] with (Unnamed Layer* 9) [ElementWise]
[TRT] Fusing (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] with (Unnamed Layer* 10) [Activation]
[TRT] Fusing (Unnamed Layer* 11) [Convolution] with (Unnamed Layer* 13) [Activation]
[TRT] Fusing (Unnamed Layer* 14) [Convolution] with (Unnamed Layer* 16) [ElementWise]
[TRT] Fusing (Unnamed Layer* 14) [Convolution] + (Unnamed Layer* 16) [ElementWise] with (Unnamed Layer* 17) [Activation]
[TRT] Fusing (Unnamed Layer* 18) [Convolution] with (Unnamed Layer* 20) [Activation]
[TRT] Fusing (Unnamed Layer* 21) [Convolution] with (Unnamed Layer* 25) [ElementWise]
[TRT] Fusing (Unnamed Layer* 21) [Convolution] + (Unnamed Layer* 25) [ElementWise] with (Unnamed Layer* 26) [Activation]
[TRT] Fusing (Unnamed Layer* 27) [Convolution] with (Unnamed Layer* 29) [Activation]
[TRT] Fusing (Unnamed Layer* 30) [Convolution] with (Unnamed Layer* 32) [ElementWise]
[TRT] Fusing (Unnamed Layer* 30) [Convolution] + (Unnamed Layer* 32) [ElementWise] with (Unnamed Layer* 33) [Activation]
[TRT] Fusing (Unnamed Layer* 34) [Convolution] with (Unnamed Layer* 36) [Activation]
[TRT] Fusing (Unnamed Layer* 37) [Convolution] with (Unnamed Layer* 41) [ElementWise]
[TRT] Fusing (Unnamed Layer* 37) [Convolution] + (Unnamed Layer* 41) [ElementWise] with (Unnamed Layer* 42) [Activation]
[TRT] Fusing (Unnamed Layer* 43) [Convolution] with (Unnamed Layer* 45) [Activation]
[TRT] Fusing (Unnamed Layer* 46) [Convolution] with (Unnamed Layer* 48) [ElementWise]
[TRT] Fusing (Unnamed Layer* 46) [Convolution] + (Unnamed Layer* 48) [ElementWise] with (Unnamed Layer* 49) [Activation]
[TRT] Fusing (Unnamed Layer* 50) [Convolution] with (Unnamed Layer* 52) [Activation]
[TRT] Fusing (Unnamed Layer* 53) [Convolution] with (Unnamed Layer* 57) [ElementWise]
[TRT] Fusing (Unnamed Layer* 53) [Convolution] + (Unnamed Layer* 57) [ElementWise] with (Unnamed Layer* 58) [Activation]
[TRT] Fusing (Unnamed Layer* 59) [Convolution] with (Unnamed Layer* 61) [Activation]
[TRT] Fusing (Unnamed Layer* 62) [Convolution] with (Unnamed Layer* 64) [ElementWise]
[TRT] Fusing (Unnamed Layer* 62) [Convolution] + (Unnamed Layer* 64) [ElementWise] with (Unnamed Layer* 65) [Activation]
[TRT] After vertical fusions: 28 layers
[TRT] After final dead-layer removal: 28 layers
[TRT] After tensor merging: 28 layers
[TRT] After concat removal: 28 layers
[TRT] Graph construction and optimization completed in 1.03877 seconds.
[TRT] Constructing optimization profile number 0 out of 1
--------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.36263
[TRT] Tactic: 0 time 0.614843
[TRT] Fastest Tactic: 1002 Time: 0.36263
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 7.5544
[TRT] Tactic: 0 time 0.286016
[TRT] Fastest Tactic: 0 Time: 0.286016
[TRT] *************** Autotuning format combination: Float(1,224,50176,150528) → Float(1,112,12544,802816) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 3.01174
[TRT] Fastest Tactic: 0 Time: 3.01174
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (FusedConvActConvolution)
[TRT] Tactic: 1 time 4.9762
[TRT] Tactic: 49 time 4.65906
[TRT] Tactic: 128 time 4.255
[TRT] Fastest Tactic: 128 Time: 4.255
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1
[TRT] Tactic: 1062367460111450758 time 2.82388
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1
[TRT] Tactic: 4337000649858996379 time 2.63484
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1
[TRT] Tactic: 4501471010995462441 time 4.88021
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1
[TRT] Tactic: 6645123197870846056 time 2.24
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1
[TRT] Tactic: -9137461792520977713 time 4.88344
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1
[TRT] Tactic: -6092040395344634144 time 2.8737
[TRT] Fastest Tactic: 6645123197870846056 Time: 2.24
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 5.6726
[TRT] Tactic: 1 time 3.05862
[TRT] Tactic: 2 time 5.14909
[TRT] Fastest Tactic: 1 Time: 3.05862
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 6645123197870846056
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,224,50176,150528) → Half(1,112,12544,802816) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (FusedConvActConvolution)
[TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CaskConvolution)
[TRT] CaskConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 6.07667
[TRT] Tactic: 1 time 2.94841
[TRT] Tactic: 2 time 4.56203
[TRT] Fastest Tactic: 1 Time: 2.94841
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaConvolution Tactic: 1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,224,50176:2,100352) → Half(1,112,12544:2,401408) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 1.52648
[TRT] Fastest Tactic: 0 Time: 1.52648
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (FusedConvActConvolution)
[TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1
[TRT] Tactic: 3564772625446233998 time 2.44872
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_large_nn_v1
[TRT] Tactic: 3650389455493082349 time 2.02521
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1
[TRT] Tactic: 7205456024582378848 time 1.54763
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_large_nn_v1
[TRT] Tactic: -6490690591794140522 time 1.55997
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_large_nn_v1
[TRT] Tactic: -4686027666808657977 time 3.47766
[TRT] (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1
[TRT] Tactic: -3898373634979201110 time 3.43685
[TRT] Fastest Tactic: 7205456024582378848 Time: 1.54763
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaConvolution)
[TRT] CudaConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 0) [Convolution] + (Unnamed Layer* 2) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: LegacySASSConvolution Tactic: 0
[TRT]
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.731562
[TRT] Tactic: 0 time 1.21159
[TRT] Fastest Tactic: 1002 Time: 0.731562
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 2.4274
[TRT] Tactic: 0 time 0.974584
[TRT] Fastest Tactic: 0 Time: 0.974584
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.72789
[TRT] Tactic: 0 time 1.0319
[TRT] Fastest Tactic: 1002 Time: 0.72789
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 2.86172
[TRT] Tactic: 0 time 0.955443
[TRT] Fastest Tactic: 0 Time: 0.955443
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 3.55315
[TRT] Tactic: 0 time 0.880911
[TRT] Fastest Tactic: 0 Time: 0.880911
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 3.75583
[TRT] Tactic: 0 time 0.870026
[TRT] Fastest Tactic: 0 Time: 0.870026
[TRT] *************** Autotuning format combination: Float(1,112,12544,802816) → Float(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (Pooling)
[TRT] Tactic: -1 time 0.887812
[TRT] Fastest Tactic: -1 Time: 0.887812
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (TiledPooling)
[TRT] Tactic: 257 time 1.37336
[TRT] Tactic: 65793 time 1.40943
[TRT] Tactic: 131329 time 1.72
[TRT] Tactic: 196865 time 2.15417
[TRT] Tactic: 262401 time 1.35432
[TRT] Tactic: 327937 time 1.34724
[TRT] Tactic: 393473 time 1.90399
[TRT] Tactic: 459009 time 0.849896
[TRT] Tactic: 524545 time 0.691823
[TRT] Tactic: 590081 time 1.01815
[TRT] Tactic: 655617 time 1.08013
[TRT] Tactic: 721153 time 1.09807
[TRT] Tactic: 786689 time 0.898567
[TRT] Tactic: 852225 time 0.971614
[TRT] Tactic: 917761 time 0.678907
[TRT] Tactic: 983297 time 0.575833
[TRT] Tactic: 1048833 time 0.852318
[TRT] Tactic: 1114369 time 0.863777
[TRT] Tactic: 1179905 time 0.975521
[TRT] Tactic: 1245441 time 0.69948
[TRT] Tactic: 1310977 time 0.805339
[TRT] Tactic: 1376513 time 0.616848
[TRT] Tactic: 1442049 time 0.492318
[TRT] Tactic: 1507585 time 0.725312
[TRT] Tactic: 1573121 time 0.692604
[TRT] Tactic: 1638657 time 0.633984
[TRT] Tactic: 1704193 time 0.564349
[TRT] Tactic: 1769729 time 0.652604
[TRT] Tactic: 1835265 time 0.603359
[TRT] Tactic: 1900801 time 0.462708
[TRT] Tactic: 1966337 time 0.625755
[TRT] Tactic: 2031873 time 0.603619
[TRT] Tactic: 2097409 time 0.594349
[TRT] Tactic: 2162945 time 0.514531
[TRT] Tactic: 2228481 time 0.556823
[TRT] Tactic: 2294017 time 0.618724
[TRT] Tactic: 2359553 time 0.46375
[TRT] Tactic: 2425089 time 0.597317
[TRT] Tactic: 2490625 time 0.591432
[TRT] Tactic: 2556161 time 0.557943
[TRT] Tactic: 2621697 time 0.493464
[TRT] Tactic: 2687233 time 0.539714
[TRT] Tactic: 6947073 time 0.533126
[TRT] Fastest Tactic: 1900801 Time: 0.462708
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: TiledPooling Tactic: 1900801
[TRT]
[TRT] *************** Autotuning format combination: Half(1,112,12544,802816) → Half(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (Pooling)
[TRT] Tactic: -1 time 0.969557
[TRT] Fastest Tactic: -1 Time: 0.969557
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (TiledPooling)
[TRT] TiledPooling has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: Pooling Tactic: -1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,112,12544:2,401408) → Half(1,56,3136:2,100352) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (Pooling)
[TRT] Tactic: -3 time 0.527031
[TRT] Fastest Tactic: -3 Time: 0.527031
[TRT] --------------- Timing Runner: (Unnamed Layer* 3) [Pooling] (TiledPooling)
[TRT] Tactic: 257 time 0.690339
[TRT] Tactic: 65793 time 0.583542
[TRT] Tactic: 131329 time 1.18289
[TRT] Tactic: 196865 time 0.927135
[TRT] Tactic: 262401 time 0.748204
[TRT] Tactic: 327937 time 0.766355
[TRT] Tactic: 393473 time 0.810964
[TRT] Tactic: 459009 time 0.44987
[TRT] Tactic: 524545 time 0.387448
[TRT] Tactic: 590081 time 0.531667
[TRT] Tactic: 655617 time 0.578593
[TRT] Tactic: 721153 time 0.482682
[TRT] Tactic: 786689 time 0.450286
[TRT] Tactic: 852225 time 0.503489
[TRT] Tactic: 917761 time 0.385312
[TRT] Tactic: 983297 time 0.331927
[TRT] Tactic: 1048833 time 0.424739
[TRT] Tactic: 1114369 time 0.458881
[TRT] Tactic: 1179905 time 0.40987
[TRT] Tactic: 1245441 time 0.372891
[TRT] Tactic: 1310977 time 0.410052
[TRT] Tactic: 1376513 time 0.341328
[TRT] Tactic: 1442049 time 0.290547
[TRT] Tactic: 1507585 time 0.359193
[TRT] Tactic: 1573121 time 0.407344
[TRT] Tactic: 1638657 time 0.352343
[TRT] Tactic: 1704193 time 0.321797
[TRT] Tactic: 1769729 time 0.359114
[TRT] Tactic: 1835265 time 0.345156
[TRT] Tactic: 1900801 time 0.294635
[TRT] Tactic: 1966337 time 0.36276
[TRT] Tactic: 2031873 time 0.373073
[TRT] Tactic: 2097409 time 0.358204
[TRT] Tactic: 2162945 time 0.323619
[TRT] Tactic: 2228481 time 0.355287
[TRT] Tactic: 2294017 time 0.332397
[TRT] Tactic: 2359553 time 0.294609
[TRT] Tactic: 2425089 time 0.365573
[TRT] Tactic: 2490625 time 0.372187
[TRT] Tactic: 2556161 time 0.349948
[TRT] Tactic: 2621697 time 0.313151
[TRT] Tactic: 2687233 time 0.353281
[TRT] Tactic: 6947073 time 0.311875
[TRT] Fastest Tactic: 1442049 Time: 0.290547
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: TiledPooling Tactic: 1442049
[TRT]
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.190859
[TRT] Tactic: 0 time 0.309687
[TRT] Fastest Tactic: 1002 Time: 0.190859
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.622084
[TRT] Tactic: 0 time 0.248933
[TRT] Fastest Tactic: 0 Time: 0.248933
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.192683
[TRT] Tactic: 0 time 0.261953
[TRT] Fastest Tactic: 1002 Time: 0.192683
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.630183
[TRT] Tactic: 0 time 0.244011
[TRT] Fastest Tactic: 0 Time: 0.244011
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.915026
[TRT] Tactic: 0 time 0.22565
[TRT] Fastest Tactic: 0 Time: 0.22565
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.909636
[TRT] Tactic: 0 time 0.222058
[TRT] Fastest Tactic: 0 Time: 0.222058
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.191328
[TRT] Tactic: 0 time 0.309896
[TRT] Fastest Tactic: 1002 Time: 0.191328
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.617787
[TRT] Tactic: 0 time 0.248802
[TRT] Fastest Tactic: 0 Time: 0.248802
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.188151
[TRT] Tactic: 0 time 0.263568
[TRT] Fastest Tactic: 1002 Time: 0.188151
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.630261
[TRT] Tactic: 0 time 0.244323
[TRT] Fastest Tactic: 0 Time: 0.244323
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.909869
[TRT] Tactic: 0 time 0.226589
[TRT] Fastest Tactic: 0 Time: 0.226589
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.91224
[TRT] Tactic: 0 time 0.223047
[TRT] Fastest Tactic: 0 Time: 0.223047
[TRT] *************** Autotuning format combination: Float(1,56,3136,200704) → Float(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 1.94354
[TRT] Tactic: 1 time 1.29154
[TRT] Fastest Tactic: 1 Time: 1.29154
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (FusedConvActConvolution)
[TRT] Tactic: 7 time 2.06359
[TRT] Tactic: 10 time 2.34182
[TRT] Tactic: 14 time 2.03648
[TRT] Tactic: 15 time 2.27479
[TRT] Tactic: 25 time 2.24036
[TRT] Tactic: 26 time 2.69646
[TRT] Tactic: 29 time 2.33823
[TRT] Tactic: 30 time 2.28675
[TRT] Tactic: 33 time 2.32479
[TRT] Tactic: 36 time 2.90206
[TRT] Tactic: 39 time 2.82047
[TRT] Tactic: 41 time 2.37052
[TRT] Tactic: 42 time 5.76255
[TRT] Tactic: 43 time 4.22417
[TRT] Tactic: 45 time 2.13344
[TRT] Tactic: 47 time 2.31451
[TRT] Tactic: 52 time 4.14367
[TRT] Tactic: 54 time 2.09365
[TRT] Tactic: 56 time 4.31859
[TRT] Tactic: 66 time 2.19521
[TRT] Tactic: 76 time 2.06203
[TRT] Tactic: 90 time 1.9668
[TRT] Tactic: 93 time 2.01875
[TRT] Tactic: 98 time 2.30417
[TRT] Tactic: 104 time 2.05341
[TRT] Tactic: 110 time 3.08216
[TRT] Tactic: 119 time 3.09065
[TRT] Tactic: 121 time 2.0118
[TRT] Tactic: 130 time 2.14607
[TRT] Tactic: 134 time 2.50138
[TRT] Tactic: 136 time 2.00005
[TRT] Tactic: 137 time 2.20221
[TRT] Tactic: 139 time 2.08115
[TRT] Tactic: 144 time 2.32385
[TRT] Tactic: 149 time 3.61987
[TRT] Tactic: 151 time 2.48042
[TRT] Tactic: 152 time 2.21216
[TRT] Tactic: 153 time 2.20128
[TRT] Tactic: 156 time 1.95091
[TRT] Tactic: 159 time 2.17299
[TRT] Tactic: 162 time 2.72753
[TRT] Tactic: 164 time 2.19536
[TRT] Fastest Tactic: 156 Time: 1.95091
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1
[TRT] Tactic: 1062367460111450758 time 2.72703
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1
[TRT] Tactic: 3827454225649558724 time 1.77786
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1
[TRT] Tactic: 4337000649858996379 time 1.93479
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1
[TRT] Tactic: 4501471010995462441 time 3.67549
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1
[TRT] Tactic: 5137655947464784826 time 2.20482
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT] Tactic: 5921334924264294896 time 1.35542
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1
[TRT] Tactic: 6645123197870846056 time 1.88128
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1
[TRT] Tactic: 7852627285308570038 time 1.8168
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1
[TRT] Tactic: -9137461792520977713 time 4.15448
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1
[TRT] Tactic: -6092040395344634144 time 2.70086
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1
[TRT] Tactic: -3456450830548107839 time 2.55117
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1
[TRT] Tactic: -410470605513481746 time 3.63945
[TRT] Fastest Tactic: 5921334924264294896 Time: 1.35542
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 4.6731
[TRT] Tactic: 1 time 2.17698
[TRT] Tactic: 2 time 4.16143
[TRT] Tactic: 6 time 1.60896
[TRT] Fastest Tactic: 6 Time: 1.60896
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: LegacySASSConvolution Tactic: 1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,56,3136,200704) → Half(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (FusedConvActConvolution)
[TRT] FusedConvActConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CaskConvolution)
[TRT] CaskConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 5.00344
[TRT] Tactic: 1 time 2.19349
[TRT] Tactic: 2 time 4.76542
[TRT] Tactic: 6 time 1.93888
[TRT] Fastest Tactic: 6 Time: 1.93888
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaConvolution Tactic: 6
[TRT]
[TRT] *************** Autotuning format combination: Half(1,56,3136:2,100352) → Half(1,56,3136:2,100352) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 0.936588
[TRT] Fastest Tactic: 0 Time: 0.936588
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (FusedConvActConvolution)
[TRT] Tactic: 7 time 1.14964
[TRT] Tactic: 10 time 1.3106
[TRT] Tactic: 14 time 1.10474
[TRT] Tactic: 15 time 1.30534
[TRT] Tactic: 25 time 1.29576
[TRT] Tactic: 26 time 6.60273
[TRT] Tactic: 29 time 1.11602
[TRT] Tactic: 30 time 1.20156
[TRT] Tactic: 33 time 1.3074
[TRT] Tactic: 36 time 2.46427
[TRT] Tactic: 39 time 1.59729
[TRT] Tactic: 41 time 1.23677
[TRT] Tactic: 42 time 3.05763
[TRT] Tactic: 43 time 2.74849
[TRT] Tactic: 45 time 1.23508
[TRT] Tactic: 47 time 1.26102
[TRT] Tactic: 52 time 2.75089
[TRT] Tactic: 54 time 1.19901
[TRT] Tactic: 56 time 2.47055
[TRT] Tactic: 66 time 1.21518
[TRT] Tactic: 76 time 1.15654
[TRT] Tactic: 90 time 1.06784
[TRT] Tactic: 93 time 1.17716
[TRT] Tactic: 98 time 1.19901
[TRT] Tactic: 104 time 1.08661
[TRT] Tactic: 110 time 1.41979
[TRT] Tactic: 119 time 1.56526
[TRT] Tactic: 121 time 1.18414
[TRT] Tactic: 130 time 1.25044
[TRT] Tactic: 134 time 2.16703
[TRT] Tactic: 136 time 1.14539
[TRT] Tactic: 137 time 1.23469
[TRT] Tactic: 139 time 1.19724
[TRT] Tactic: 144 time 1.19109
[TRT] Tactic: 149 time 2.15273
[TRT] Tactic: 151 time 1.36023
[TRT] Tactic: 152 time 1.24284
[TRT] Tactic: 153 time 1.21286
[TRT] Tactic: 156 time 1.14242
[TRT] Tactic: 159 time 1.26349
[TRT] Tactic: 162 time 1.46276
[TRT] Tactic: 164 time 1.17411
[TRT] Fastest Tactic: 90 Time: 1.06784
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1
[TRT] Tactic: 3564772625446233998 time 1.2245
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_large_nn_v1
[TRT] Tactic: 3650389455493082349 time 1.26852
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn_winograd) Set Tactic Name: maxwell_fp16x2_hcudnn_winograd_fp16x2_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT] Tactic: 4772821744921268633 time 0.750756
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1
[TRT] Tactic: 5319956359050645452 time 1.11195
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1
[TRT] Tactic: 7205456024582378848 time 0.972708
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_large_nn_v1
[TRT] Tactic: -6490690591794140522 time 1.00065
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_large_nn_v1
[TRT] Tactic: -4686027666808657977 time 1.92273
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1
[TRT] Tactic: -4212163711445252890 time 1.81034
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1
[TRT] Tactic: -3898373634979201110 time 1.85625
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1
[TRT] Tactic: -2409163523992614473 time 0.952942
[TRT] Fastest Tactic: 4772821744921268633 Time: 0.750756
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaConvolution)
[TRT] CudaConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (CudaDepthwiseConvolution)
[TRT] CudaDepthwiseConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 4772821744921268633
[TRT] (Unnamed Layer* 4) [Convolution] + (Unnamed Layer* 6) [Activation] (hcudnn_winograd) Set Tactic Name: maxwell_fp16x2_hcudnn_winograd_fp16x2_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT]
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.19151
[TRT] Tactic: 0 time 0.310338
[TRT] Fastest Tactic: 1002 Time: 0.19151
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.619219
[TRT] Tactic: 0 time 0.249427
[TRT] Fastest Tactic: 0 Time: 0.249427
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.192708
[TRT] Tactic: 0 time 0.263593
[TRT] Fastest Tactic: 1002 Time: 0.192708
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.620234
[TRT] Tactic: 0 time 0.244792
[TRT] Fastest Tactic: 0 Time: 0.244792
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.909869
[TRT] Tactic: 0 time 0.225911
[TRT] Fastest Tactic: 0 Time: 0.225911
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.910833
[TRT] Tactic: 0 time 0.222708
[TRT] Fastest Tactic: 0 Time: 0.222708
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.191849
[TRT] Tactic: 0 time 0.310313
[TRT] Fastest Tactic: 1002 Time: 0.191849
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.616172
[TRT] Tactic: 0 time 0.248697
[TRT] Fastest Tactic: 0 Time: 0.248697
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.189401
[TRT] Tactic: 0 time 0.262838
[TRT] Fastest Tactic: 1002 Time: 0.189401
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.623334
[TRT] Tactic: 0 time 0.244088
[TRT] Fastest Tactic: 0 Time: 0.244088
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.905495
[TRT] Tactic: 0 time 0.22651
[TRT] Fastest Tactic: 0 Time: 0.22651
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.910182
[TRT] Tactic: 0 time 0.222864
[TRT] Fastest Tactic: 0 Time: 0.222864
[TRT] *************** Autotuning format combination: Float(1,56,3136,200704), Float(1,56,3136,200704) → Float(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 2.01615
[TRT] Tactic: 1 time 1.33135
[TRT] Fastest Tactic: 1 Time: 1.33135
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_medium_nn_v1
[TRT] Tactic: 1062367460111450758 time 2.363
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148n_nt_v1
[TRT] Tactic: 3827454225649558724 time 1.84039
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_large_nn_v1
[TRT] Tactic: 4337000649858996379 time 1.9426
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_medium_nn_v1
[TRT] Tactic: 4501471010995462441 time 4.27633
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_small_nn_v1
[TRT] Tactic: 5137655947464784826 time 1.8501
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT] Tactic: 5921334924264294896 time 1.38654
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x64_relu_medium_nn_v1
[TRT] Tactic: 6645123197870846056 time 2.31081
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn_winograd) Set Tactic Name: maxwell_scudnn_winograd_128x128_ldg1_ldg4_relu_tile148t_nt_v1
[TRT] Tactic: 7852627285308570038 time 2.72331
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_large_nn_v1
[TRT] Tactic: -9137461792520977713 time 4.35734
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_large_nn_v1
[TRT] Tactic: -6092040395344634144 time 2.45872
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x32_relu_small_nn_v1
[TRT] Tactic: -3456450830548107839 time 2.63297
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (scudnn) Set Tactic Name: maxwell_scudnn_128x128_relu_small_nn_v1
[TRT] Tactic: -410470605513481746 time 4.07891
[TRT] Fastest Tactic: 5921334924264294896 Time: 1.38654
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 4.85464
[TRT] Tactic: 1 time 2.33365
[TRT] Tactic: 2 time 4.62102
[TRT] Tactic: 6 time 2.35203
[TRT] Fastest Tactic: 1 Time: 2.33365
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: LegacySASSConvolution Tactic: 1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,56,3136,200704), Half(1,56,3136,200704) → Half(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CaskConvolution)
[TRT] CaskConvolution has no valid tactics for this config, skipping
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CudaConvolution)
[TRT] Tactic: 0 time 5.12518
[TRT] Tactic: 1 time 2.31391
[TRT] Tactic: 2 time 4.10901
[TRT] Tactic: 6 time 2.55773
[TRT] Fastest Tactic: 1 Time: 2.31391
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CudaConvolution Tactic: 1
[TRT]
[TRT] *************** Autotuning format combination: Half(1,56,3136:2,100352), Half(1,56,3136:2,100352) → Half(1,56,3136:2,100352) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 0.947344
[TRT] Fastest Tactic: 0 Time: 0.947344
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CaskConvolution)
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_medium_nn_v1
[TRT] Tactic: 3564772625446233998 time 1.23398
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_large_nn_v1
[TRT] Tactic: 3650389455493082349 time 1.29594
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn_winograd) Set Tactic Name: maxwell_fp16x2_hcudnn_winograd_fp16x2_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT] Tactic: 4772821744921268633 time 0.764844
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x32_relu_small_nn_v1
[TRT] Tactic: 5319956359050645452 time 1.12466
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_medium_nn_v1
[TRT] Tactic: 7205456024582378848 time 0.9825
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_large_nn_v1
[TRT] Tactic: -6490690591794140522 time 0.993281
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_large_nn_v1
[TRT] Tactic: -4686027666808657977 time 1.90479
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_small_nn_v1
[TRT] Tactic: -4212163711445252890 time 2.10896
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x128_relu_medium_nn_v1
[TRT] Tactic: -3898373634979201110 time 1.87378
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn) Set Tactic Name: maxwell_fp16x2_hcudnn_fp16x2_128x64_relu_small_nn_v1
[TRT] Tactic: -2409163523992614473 time 0.950469
[TRT] Fastest Tactic: 4772821744921268633 Time: 0.764844
[TRT] --------------- Timing Runner: (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (CudaConvolution)
[TRT] CudaConvolution has no valid tactics for this config, skipping
[TRT] >>>>>>>>>>>>>>> Chose Runner Type: CaskConvolution Tactic: 4772821744921268633
[TRT] (Unnamed Layer* 7) [Convolution] + (Unnamed Layer* 9) [ElementWise] + (Unnamed Layer* 10) [Activation] (hcudnn_winograd) Set Tactic Name: maxwell_fp16x2_hcudnn_winograd_fp16x2_128x128_ldg1_ldg4_relu_tile148m_nt_v1
[TRT]
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.192109
[TRT] Tactic: 0 time 0.309349
[TRT] Fastest Tactic: 1002 Time: 0.192109
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.615156
[TRT] Tactic: 0 time 0.248673
[TRT] Fastest Tactic: 0 Time: 0.248673
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.190781
[TRT] Tactic: 0 time 0.264089
[TRT] Fastest Tactic: 1002 Time: 0.190781
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.649166
[TRT] Tactic: 0 time 0.24461
[TRT] Fastest Tactic: 0 Time: 0.24461
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.907865
[TRT] Tactic: 0 time 0.225625
[TRT] Fastest Tactic: 0 Time: 0.225625
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.911433
[TRT] Tactic: 0 time 0.223672
[TRT] Fastest Tactic: 0 Time: 0.223672
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.19388
[TRT] Tactic: 0 time 0.309792
[TRT] Fastest Tactic: 1002 Time: 0.19388
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.619609
[TRT] Tactic: 0 time 0.248203
[TRT] Fastest Tactic: 0 Time: 0.248203
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.196016
[TRT] Tactic: 0 time 0.262161
[TRT] Fastest Tactic: 1002 Time: 0.196016
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.641641
[TRT] Tactic: 0 time 0.243854
[TRT] Fastest Tactic: 0 Time: 0.243854
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.908542
[TRT] Tactic: 0 time 0.226146
[TRT] Fastest Tactic: 0 Time: 0.226146
[TRT] --------------- Timing Runner: (Reformat)
[TRT] Tactic: 1002 time 0.908985
[TRT] Tactic: 0 time 0.222135
[TRT] Fastest Tactic: 0 Time: 0.222135
[TRT] *************** Autotuning format combination: Float(1,56,3136,200704) → Float(1,56,3136,200704) ***************
[TRT] --------------- Timing Runner: (Unnamed Layer* 11) [Convolution] + (Unnamed Layer* 13) [Activation] (LegacySASSConvolution)
[TRT] Tactic: 0 time 2.34878
[TRT] Tactic: 1 time 1.29951
[TRT] Fastest Tactic: 1 Time: 1.29951
[TRT] --------------- Timing Runner: (Unnamed Layer* 11) [Convolution] + (Unnamed Layer* 13) [Activation] (FusedConvActConvolution)
[TRT] Tactic: 7 time 2.06341
[TRT] Tactic: 10 time 2.34875
[TRT] Tactic: 14 time 2.03273
[TRT] Tactic: 15 time 2.67888
[TRT] Tactic: 25 time 2.25081
[TRT] Tactic: 26 time 2.76031
[TRT] Tactic: 29 time 1.93945
[TRT] Tactic: 30 time 2.26245
[TRT] Tactic: 33 time 2.69802
[TRT] Tactic: 36 time 2.89164
[TRT] Tactic: 39 time 2.83456
[TRT] Tactic: 41 time 2.30802
[TRT] Tactic: 42 time 5.74539
[TRT] Tactic: 43 time 4.22385
[TRT] Tactic: 45 time 2.41937
[TRT] Tactic: 47 time 2.3131
[TRT] Tactic: 52 time 4.15846
[TRT] Tactic: 54 time 2.10625
[TRT] Tactic: 56 time 4.1531
[TRT] Tactic: 66 time 2.20508
[TRT] Tactic: 76 time 2.05971
[TRT] Tactic: 90 time 2.03971
[TRT] Tactic: 93 time 2.05716
[TRT] Tactic: 98 time 2.27562
[TRT] Tactic: 104 time 2.0668
[TRT] Tactic: 110 time 2.67742
[TRT] Tactic: 119 time 3.08185
[TRT] Tactic: 121 time 2.02573
[TRT] Tactic: 130 time 2.14586
[TRT] Tactic: 134 time 2.5637
[TRT] Tactic: 136 time 2.43234
[TRT] Tactic: 137 time 2.20964
[TRT] Tactic: 139 time 2.11221
[TRT] Tactic: 144 time 2.33901
[TRT] Tactic: 149 time 3.62807
[TRT] Tactic: 151 time 2.44422
[TRT] Tactic: 152 time 2.14505
[TRT] Tactic: 153 time 2.18659
[TRT] Tactic: 156 time