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remove more cudnn dependencies
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‎cmake/Modules/FindcuDNN.cmake

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‎cmake/dependencies.cmake

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# If the custom finders are needed at this point, there are good chances that they will be needed when consuming the library as well
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install(FILES "${CMAKE_SOURCE_DIR}/cmake/Modules/FindTensorRT.cmake" DESTINATION "${CMAKE_INSTALL_LIBDIR}/cmake/torchtrt/Modules")
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install(FILES "${CMAKE_SOURCE_DIR}/cmake/Modules/FindcuDNN.cmake" DESTINATION "${CMAKE_INSTALL_LIBDIR}/cmake/torchtrt/Modules")
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# CUDA
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find_package(CUDAToolkit REQUIRED)
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find_package(cuDNN REQUIRED) # Headers are needed somewhere
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# libtorch
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find_package(Torch REQUIRED)

‎core/plugins/CMakeLists.txt

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@@ -23,7 +23,6 @@ target_link_libraries(${lib_name}
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TensorRT::nvinfer_plugin
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torch
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core_util
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cuDNN::cuDNN
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PRIVATE
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Threads::Threads
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)

‎examples/int8/ptq/README.md

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@@ -149,14 +149,13 @@ tar -xvzf libtorch_tensorrt.tar.gz
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unzip libtorch.zip
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```
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> If cuDNN and TensorRT are not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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> If TensorRT is not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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```sh
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cd deps
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mkdir cudnn && tar -xvzf <cuDNN TARBALL> --directory cudnn --strip-components=1
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mkdir tensorrt && tar -xvzf <TensorRT TARBALL> --directory tensorrt --strip-components=1
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cd ..
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:$(pwd)/deps/cudnn/lib64:/usr/local/cuda/lib
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:/usr/local/cuda/lib
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```
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2) Build and run `ptq`

‎examples/int8/qat/README.md

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@@ -43,14 +43,13 @@ tar -xvzf libtorch_tensorrt.tar.gz
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unzip libtorch.zip
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```
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> If cuDNN and TensorRT are not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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> If TensorRT is not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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```sh
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cd deps
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mkdir cudnn && tar -xvzf <cuDNN TARBALL> --directory cudnn --strip-components=1
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mkdir tensorrt && tar -xvzf <TensorRT TARBALL> --directory tensorrt --strip-components=1
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cd ..
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:$(pwd)/deps/cudnn/lib64:/usr/local/cuda/lib
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:/usr/local/cuda/lib
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```
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2) Build and run `qat`

‎examples/torchtrt_runtime_example/Makefile

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CXX=g++
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DEP_DIR=$(PWD)/deps
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INCLUDE_DIRS=-I$(DEP_DIR)/libtorch/include -I$(DEP_DIR)/torch_tensorrt/include
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LIB_DIRS=-L$(DEP_DIR)/torch_tensorrt/lib -L$(DEP_DIR)/libtorch/lib # -Wl,-rpath $(DEP_DIR)/tensorrt/lib -Wl,-rpath $(DEP_DIR)/cudnn/lib64
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LIB_DIRS=-L$(DEP_DIR)/torch_tensorrt/lib -L$(DEP_DIR)/libtorch/lib # -Wl,-rpath $(DEP_DIR)/tensorrt/lib
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LIBS=-Wl,--no-as-needed -ltorchtrt_runtime -Wl,--as-needed -ltorch -ltorch_cuda -ltorch_cpu -ltorch_global_deps -lbackend_with_compiler -lc10 -lc10_cuda
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SRCS=main.cpp
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‎examples/torchtrt_runtime_example/README.md

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@@ -26,17 +26,16 @@ tar -xvzf libtorch_tensorrt.tar.gz
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unzip libtorch-cxx11-abi-shared-with-deps-[PYTORCH_VERSION].zip
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```
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> If cuDNN and TensorRT are not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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> If TensorRT is not installed on your system / in your LD_LIBRARY_PATH then do the following as well
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```sh
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cd deps
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mkdir cudnn && tar -xvzf <cuDNN TARBALL> --directory cudnn --strip-components=1
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mkdir tensorrt && tar -xvzf <TensorRT TARBALL> --directory tensorrt --strip-components=1
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cd ..
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:$(pwd)/deps/cudnn/lib64:/usr/local/cuda/lib
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:/usr/local/cuda/lib
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```
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This gives maximum compatibility with system configurations for running this example but in general you are better off adding `-Wl,-rpath $(DEP_DIR)/tensorrt/lib -Wl,-rpath $(DEP_DIR)/cudnn/lib64` to your linking command for actual applications
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This gives maximum compatibility with system configurations for running this example but in general you are better off adding `-Wl,-rpath $(DEP_DIR)/tensorrt/lib` to your linking command for actual applications
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2) Build and run `torchtrt_runtime_example`
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cd examples/torchtrt_runtime_example
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make
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# If paths are different than the ones below, change as necessary
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:$(pwd)/deps/cudnn/lib64:/usr/local/cuda/lib
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export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:$(pwd)/deps/torch_tensorrt/lib:$(pwd)/deps/libtorch/lib:$(pwd)/deps/tensorrt/lib:/usr/local/cuda/lib
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./torchtrt_runtime_example $PWD/examples/torchtrt_runtime_example/norm.jit
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```

‎notebooks/Resnet50-CPP.ipynb

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"unzip libtorch-cxx11-abi-shared-with-deps-1.11.0+cu113.zip"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "198553b7",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%bash\n",
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"cd deps\n",
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"wget https://github.com/pytorch/TensorRT/releases/download/v1.1.0/libtorchtrt-v1.1.0-cudnn8.2-tensorrt8.2-cuda11.3-libtorch1.11.0.tar.gz\n",
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"tar -xvzf libtorchtrt-v1.1.0-cudnn8.2-tensorrt8.2-cuda11.3-libtorch1.11.0.tar.gz"
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]
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},
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{
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"cell_type": "markdown",
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"id": "309696b6",

‎py/ci/build_whl.sh

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TORCHTRT_VERSION=$(cd ${PROJECT_DIR} && ${PY_DIR}/bin/python3 -c "import versions; versions.torch_tensorrt_version_release()")
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TRT_VERSION=$(cd ${PROJECT_DIR} && ${PY_DIR}/bin/python3 -c "import versions; versions.tensorrt_version()")
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TORCH_VERSION=$(${PY_DIR}/bin/python -c "from torch import __version__;print(__version__.split('+')[0])")
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cp ${PROJECT_DIR}/bazel-bin/libtorchtrt.tar.gz ${PROJECT_DIR}/py/wheelhouse/libtorchtrt-${TORCHTRT_VERSION}-cudnn${CUDNN_VERSION}-tensorrt${TRT_VERSION}-cuda${CUDA_VERSION}-libtorch${TORCH_VERSION}-x86_64-linux.tar.gz
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cp ${PROJECT_DIR}/bazel-bin/libtorchtrt.tar.gz ${PROJECT_DIR}/py/wheelhouse/libtorchtrt-${TORCHTRT_VERSION}-tensorrt${TRT_VERSION}-cuda${CUDA_VERSION}-libtorch${TORCH_VERSION}-x86_64-linux.tar.gz
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}
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libtorchtrt_pre_cxx11_abi() {

‎py/ci/soname_excludes.params

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--exclude libcuda.so.515
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--exclude libcublasLt.so.11
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--exclude libnvinfer.so.8
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--exclude libcudnn.so.8
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--exclude libcublas.so.12
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--exclude libcublasLt.so.12
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--exclude libcublas.so.12.1.3.1

‎toolchains/ci_workspaces/WORKSPACE.win.release.tmpl

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# Locally installed dependencies (use in cases of custom dependencies or aarch64)
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####################################################################################
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new_local_repository(
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name = "cudnn",
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path = "C:/",
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build_file = "@//third_party/cudnn/local:BUILD"
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)
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new_local_repository(
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name = "tensorrt",
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path = "C:/",

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