8cfc8ee03f
* add tensorrt temporal shift module and related pytorch implementations * add .gitignore and getn weights script. * rename get_wts.py script * Add tsm-r50 demo. * update readme * remove useless codes * update readme * update readme * remote video and .gitignore, update tutorial * update readme and tutorial * fix a few bugs and test on tensorrt 5.1 * update readme |
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| .. | ||
| CMakeLists.txt | ||
| lenet.cpp | ||
| lenet.py | ||
| logging.h | ||
| README.md | ||
lenet5
lenet5 is the simplest net in this tensorrtx project. You can learn the basic procedures of building tensorrt app from API. Including define network, build engine, set output, do inference, serialize model to file, deserialize model from file, etc.
TensorRT C++ API
// 1. generate lenet5.wts from https://github.com/wang-xinyu/pytorchx/tree/master/lenet
// 2. put lenet5.wts into tensorrtx/lenet
// 3. build and run
cd tensorrtx/lenet
mkdir build
cd build
cmake ..
make
sudo ./lenet -s // serialize model to plan file i.e. 'lenet5.engine'
sudo ./lenet -d // deserialize plan file and run inference
// 4. see if the output is same as pytorchx/lenet
TensorRT Python API
# 1. generate lenet5.wts from https://github.com/wang-xinyu/pytorchx/tree/master/lenet
# 2. put lenet5.wts into tensorrtx/lenet
# 3. install Python dependencies (tensorrt/pycuda/numpy)
cd tensorrtx/lenet
python lenet.py -s # serialize model to plan file, i.e. 'lenet5.engine'
python lenet.py -d # deserialize plan file and run inference
# 4. see if the output is same as pytorchx/lenet