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wanchaolwanchaol
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Update on "[jit] register __getitem__ builtin"
[jit] register __getitem__ builtin Summary: Follow up of #21990, I am switching index select operations to a standard __getitem__ builtin, rather than bunch of different builtins according to the type, such as prim::DictIndex, prim::ListIndex, etc. This will also aligned with the some other magic methods that we already use gh-metadata: pytorch pytorch 22276 gh/wanchaol/28/head
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‎.circleci/scripts/binary_populate_env.sh‎

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@@ -75,7 +75,7 @@ export OVERRIDE_PACKAGE_VERSION="$PYTORCH_BUILD_VERSION"
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export TORCH_PACKAGE_NAME='torch-nightly'
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export TORCH_CONDA_BUILD_FOLDER='pytorch-nightly'
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export NO_FBGEMM=1
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export USE_FBGEMM=0
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export PIP_UPLOAD_FOLDER="$PIP_UPLOAD_FOLDER"
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export DOCKER_IMAGE="$DOCKER_IMAGE"
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‎.jenkins/pytorch/build-asan.sh‎

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@@ -33,7 +33,7 @@ export ASAN_OPTIONS=detect_leaks=0:symbolize=1
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CC="clang" CXX="clang++" LDSHARED="clang --shared" \
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CFLAGS="-fsanitize=address -fsanitize=undefined -fno-sanitize-recover=all -shared-libasan -pthread" \
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CXX_FLAGS="-pthread" \
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USE_ASAN=1 NO_CUDA=1 USE_MKLDNN=0 \
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USE_ASAN=1 USE_CUDA=0 USE_MKLDNN=0 \
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python setup.py install
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assert_git_not_dirty

‎.jenkins/pytorch/macos-build.sh‎

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@@ -30,7 +30,7 @@ if [[ "${BUILD_ENVIRONMENT}" == *cuda9.2* ]]; then
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export PATH=/Developer/NVIDIA/CUDA-${CUDA_VERSION}/bin${PATH:+:${PATH}}
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export DYLD_LIBRARY_PATH=/Developer/NVIDIA/CUDA-${CUDA_VERSION}/lib${DYLD_LIBRARY_PATH:+:${DYLD_LIBRARY_PATH}}
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export CUDA_HOME=/Developer/NVIDIA/CUDA-${CUDA_VERSION}
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export NO_CUDA=0
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export USE_CUDA=1
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if [ -z "${IN_CIRCLECI}" ]; then
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# Eigen gives "explicit specialization of class must precede its first use" error

‎.jenkins/pytorch/test.sh‎

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}
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test_torchvision() {
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pip_install git+https://github.com/pytorch/vision.git@2f64dd90e14fe5463b4e5bd152d56e4a6f0419de
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pip_install git+https://github.com/pytorch/vision.git@487c9bf4b7750e779fac31c35d930381baa60a4a
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}
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test_libtorch() {

‎.jenkins/pytorch/win-test-helpers/build_pytorch.bat‎

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if not "%USE_CUDA%"=="1" (
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if "%REBUILD%"=="" (
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set NO_CUDA=1
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:: Must save and restore the original value of USE_CUDA, otherwise the
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:: `if not "%USE_CUDA%"=="0"` line can be messed up.
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set OLD_USE_CUDA=%USE_CUDA%
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set USE_CUDA=0
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python setup.py install
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set USE_CUDA=%OLD_USE_CUDA%
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)
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if errorlevel 1 exit /b 1
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if not errorlevel 0 exit /b 1
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set CUDA_NVCC_EXECUTABLE=%TMP_DIR_WIN%\bin\nvcc
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if "%REBUILD%"=="" set NO_CUDA=0
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if "%REBUILD%"=="" set USE_CUDA=1
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python setup.py install --cmake && sccache --show-stats && (
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if "%BUILD_ENVIRONMENT%"=="" (

‎CMakeLists.txt‎

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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DBUILD_NAMEDTENSOR")
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endif()
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if(USE_QNNPACK)
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set(CMAKE_CXX_FLAGS "${CMAKE_CXX_FLAGS} -DUSE_QNNPACK")
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endif()
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# ---[ Whitelist file if whitelist is specified
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include(cmake/Whitelist.cmake)
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‎CONTRIBUTING.md‎

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Caffe2 operators.
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On the initial build, you can also speed things up with the environment
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variables `DEBUG` and `NO_CUDA`.
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variables `DEBUG` and `USE_CUDA`.
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- `DEBUG=1` will enable debug builds (-g -O0)
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- `REL_WITH_DEB_INFO=1` will enable debug symbols with optimizations (-g -O3)
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- `NO_CUDA=1` will disable compiling CUDA (in case you are developing on something not CUDA related), to save compile time.
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- `USE_CUDA=0` will disable compiling CUDA (in case you are developing on something not CUDA related), to save compile time.
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For example:
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```bash
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NO_CUDA=1 DEBUG=1 python setup.py develop
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USE_CUDA=0 DEBUG=1 python setup.py develop
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```
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Make sure you continue to pass these flags on subsequent builds.

‎README.md‎

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- [NVIDIA CUDA](https://developer.nvidia.com/cuda-downloads) 9 or above
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- [NVIDIA cuDNN](https://developer.nvidia.com/cudnn) v7 or above
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If you want to disable CUDA support, export environment variable `NO_CUDA=1`.
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If you want to disable CUDA support, export environment variable `USE_CUDA=0`.
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Other potentially useful environment variables may be found in `setup.py`.
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If you are building for NVIDIA's Jetson platforms (Jetson Nano, TX1, TX2, AGX Xavier), Instructions to [are available here](https://devtalk.nvidia.com/default/topic/1049071/jetson-nano/pytorch-for-jetson-nano/)

‎aten/CMakeLists.txt‎

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set(ATen_CUDA_SRCS)
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set(ATen_CUDA_TEST_SRCS)
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set(ATen_CUDA_INCLUDE)
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set(ATen_NVRTC_STUB_SRCS)
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set(ATen_HIP_SRCS)
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set(ATen_HIP_TEST_SRCS)
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set(ATen_HIP_INCLUDE)
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set(ATen_CPU_SRCS ${ATen_CPU_SRCS} PARENT_SCOPE)
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set(ATen_CUDA_SRCS ${ATen_CUDA_SRCS} PARENT_SCOPE)
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set(ATen_HIP_SRCS ${ATen_HIP_SRCS} PARENT_SCOPE)
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set(ATen_NVRTC_STUB_SRCS ${ATen_NVRTC_STUB_SRCS} PARENT_SCOPE)
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set(ATen_CPU_TEST_SRCS ${ATen_CPU_TEST_SRCS} PARENT_SCOPE)
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set(ATen_CUDA_TEST_SRCS ${ATen_CUDA_TEST_SRCS} PARENT_SCOPE)
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set(ATen_HIP_TEST_SRCS ${ATen_HIP_TEST_SRCS} PARENT_SCOPE)

‎aten/re_worker_requirements‎

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"ATen-cu#compile-pic-Unique.cu.o199e1a23,platform007-clang": {
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"workerSize": "MEDIUM",
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"platformType": "LINUX"
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},
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"ATen-cu#platform007-clang,shared": {
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"workerSize": "MEDIUM",
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"platformType": "LINUX"
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}
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}

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