Hello, I’m trying to optimize Resnet34 model, mentioned in NVIDIA/caffe/models/modelBuilder.
I’ve successfully generated .caffemodel and updated .ptototxt for deployment, and can use it via caffe.
However, when I try to load and optimize this model using TensorRT, I get crash with following logs:
TENSORRT INFO: Applying generic optimizations to the graph for inference.
TENSORRT INFO: Original: 124 layers
TENSORRT INFO: After dead-layer removal: 124 layers
TENSORRT INFO: Fusing convolution weights from conv1 with scale conv1/bn
TENSORRT INFO: Fusing convolution weights from res2.1.conv1 with scale res2.1.conv1/bn
TENSORRT INFO: Fusing convolution weights from res2.1.conv2 with scale res2.1.conv2/bn
TENSORRT INFO: Fusing convolution weights from res2.2.conv1 with scale res2.2.conv1/bn
TENSORRT INFO: Fusing convolution weights from res2.2.conv2 with scale res2.2.conv2/bn
TENSORRT INFO: Fusing convolution weights from res2.3.conv1 with scale res2.3.conv1/bn
TENSORRT INFO: Fusing convolution weights from res2.3.conv2 with scale res2.3.conv2/bn
TENSORRT INFO: Fusing convolution weights from res3.1.conv1 with scale res3.1.conv1/bn
TENSORRT INFO: Fusing convolution weights from res3.1.conv2 with scale res3.1.conv2/bn
TENSORRT INFO: Fusing convolution weights from res3.1.skipConv with scale res3.1.skipConv/bn
TENSORRT INFO: Fusing convolution weights from res3.2.conv1 with scale res3.2.conv1/bn
TENSORRT INFO: Fusing convolution weights from res3.2.conv2 with scale res3.2.conv2/bn
TENSORRT INFO: Fusing convolution weights from res3.3.conv1 with scale res3.3.conv1/bn
TENSORRT INFO: Fusing convolution weights from res3.3.conv2 with scale res3.3.conv2/bn
TENSORRT INFO: Fusing convolution weights from res3.4.conv1 with scale res3.4.conv1/bn
TENSORRT INFO: Fusing convolution weights from res3.4.conv2 with scale res3.4.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.1.conv1 with scale res4.1.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.1.conv2 with scale res4.1.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.1.skipConv with scale res4.1.skipConv/bn
TENSORRT INFO: Fusing convolution weights from res4.2.conv1 with scale res4.2.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.2.conv2 with scale res4.2.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.3.conv1 with scale res4.3.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.3.conv2 with scale res4.3.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.4.conv1 with scale res4.4.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.4.conv2 with scale res4.4.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.5.conv1 with scale res4.5.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.5.conv2 with scale res4.5.conv2/bn
TENSORRT INFO: Fusing convolution weights from res4.6.conv1 with scale res4.6.conv1/bn
TENSORRT INFO: Fusing convolution weights from res4.6.conv2 with scale res4.6.conv2/bn
TENSORRT INFO: Fusing convolution weights from res5.1.conv1 with scale res5.1.conv1/bn
TENSORRT INFO: Fusing convolution weights from res5.1.conv2 with scale res5.1.conv2/bn
My generated model files:
https://drive.google.com/open?id=1RmGk244vhz1lcLdXDlNMkSz24BdV_LJD