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Merge pull request #1137 from pytorch/circleci-editor/245/circleci-project-setup
CI/CD setup
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‎.circleci/config.yml‎

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# Use the latest 2.1 version of CircleCI pipeline process engine.
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# See: https://circleci.com/docs/2.0/configuration-reference
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version: 2.1
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# Define a job to be invoked later in a workflow.
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# See: https://circleci.com/docs/2.0/configuration-reference/#jobs
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jobs:
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build:
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machine:
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# Primary container image where all steps run.
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# image: nvcr.io/nvidia/tensorrt:22.01-py3 # does not work with customized image
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# https://circleci.com/docs/2.0/configuration-reference#available-linux-gpu-images
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image: ubuntu-2004-cuda-11.4:202110-01
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resource_class: gpu.nvidia.large
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steps:
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- checkout
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- run:
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name: install cudnn + tensorrt + bazel
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command: |
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cd ~
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OS=ubuntu2004
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CUDNN_VERSION=8.2.1.*-1+cuda11.3
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TRT_VERSION=8.2.4-1+cuda11.4
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BAZEL_VERSION=5.1.1
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wget https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/cuda-${OS}.pin
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sudo mv cuda-${OS}.pin /etc/apt/preferences.d/cuda-repository-pin-600
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sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/7fa2af80.pub
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sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys 536F8F1DE80F6A35
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sudo apt-key adv --keyserver keyserver.ubuntu.com --recv-keys A4B469963BF863CC
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sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/ /"
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sudo apt-get update
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sudo apt-get install libcudnn8=${CUDNN_VERSION}
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sudo apt-get install libcudnn8-dev=${CUDNN_VERSION}
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sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/{OS}/x86_64/3bf863cc.pub
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sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/${OS}/x86_64/ /"
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sudo apt-get update
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sudo apt-get install libnvinfer8=${TRT_VERSION} libnvonnxparsers8=${TRT_VERSION} libnvparsers8=${TRT_VERSION} libnvinfer-plugin8=${TRT_VERSION} libnvinfer-dev=${TRT_VERSION} libnvonnxparsers-dev=${TRT_VERSION} libnvparsers-dev=${TRT_VERSION} libnvinfer-plugin-dev=${TRT_VERSION} python3-libnvinfer=${TRT_VERSION}
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# check available version, apt list libnvinfer8 -a
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sudo wget -q https://github.com/bazelbuild/bazel/releases/download/${BAZEL_VERSION}/bazel-${BAZEL_VERSION}-linux-x86_64 -O /usr/bin/bazel
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sudo chmod a+x /usr/bin/bazel
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- run:
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name: set up python environment
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command: |
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pip3 install nvidia-pyindex
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pip3 install nvidia-tensorrt==8.2.4.2
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pip3 install --pre torch==1.13.0.dev20220618 torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cu113
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pip3 install pytest parameterized expecttest
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# install torch_tensorrt
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mv WORKSPACE.ci WORKSPACE
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cd py
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python3 setup.py install
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# install fx2trt
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# cd py/torch_tensorrt/fx/setup
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# python3 setup.py install
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- run:
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name: run fx2trt tests
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command: |
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# one fix pending to enable below
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# cd py/torch_tensorrt/fx/test
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# pytest $(find . -name '*.py' | grep -v test_dispatch* | grep -v test_setitem*)
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cd py/torch_tensorrt/fx/test
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pushd converters/acc_op
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pytest
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popd
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pushd passes
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list_passes=$(ls | grep -v test_setitem*)
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pytest $list_passes
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popd
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pushd core
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pytest
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popd
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# pushd quant
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# pytest
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# popd
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pushd tools
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pytest
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popd
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pushd trt_lower
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pytest
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popd
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pushd tracer
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list_tracer=$(ls | grep -v test_dispatch_*)
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pytest $list_tracer
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popd
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# Invoke jobs via workflows
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# See: https://circleci.com/docs/2.0/configuration-reference/#workflows
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workflows:
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build_run:
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jobs:
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- build

‎WORKSPACE.ci‎

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workspace(name = "Torch-TensorRT")
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load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")
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load("@bazel_tools//tools/build_defs/repo:git.bzl", "git_repository")
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http_archive(
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name = "rules_python",
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sha256 = "778197e26c5fbeb07ac2a2c5ae405b30f6cb7ad1f5510ea6fdac03bded96cc6f",
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url = "https://github.com/bazelbuild/rules_python/releases/download/0.2.0/rules_python-0.2.0.tar.gz",
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)
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load("@rules_python//python:pip.bzl", "pip_install")
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http_archive(
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name = "rules_pkg",
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sha256 = "038f1caa773a7e35b3663865ffb003169c6a71dc995e39bf4815792f385d837d",
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urls = [
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"https://mirror.bazel.build/github.com/bazelbuild/rules_pkg/releases/download/0.4.0/rules_pkg-0.4.0.tar.gz",
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"https://github.com/bazelbuild/rules_pkg/releases/download/0.4.0/rules_pkg-0.4.0.tar.gz",
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],
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)
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load("@rules_pkg//:deps.bzl", "rules_pkg_dependencies")
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rules_pkg_dependencies()
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git_repository(
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name = "googletest",
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commit = "703bd9caab50b139428cea1aaff9974ebee5742e",
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remote = "https://github.com/google/googletest",
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shallow_since = "1570114335 -0400",
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)
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# External dependency for torch_tensorrt if you already have precompiled binaries.
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local_repository(
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name = "torch_tensorrt",
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path = "/opt/conda/lib/python3.8/site-packages/torch_tensorrt"
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)
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# CUDA should be installed on the system locally
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new_local_repository(
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name = "cuda",
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build_file = "@//third_party/cuda:BUILD",
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path = "/usr/local/cuda/",
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)
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new_local_repository(
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name = "cublas",
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build_file = "@//third_party/cublas:BUILD",
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path = "/usr",
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)
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#############################################################################################################
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# Tarballs and fetched dependencies (default - use in cases when building from precompiled bin and tarballs)
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#############################################################################################################
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#http_archive(
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# name = "libtorch",
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# build_file = "@//third_party/libtorch:BUILD",
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# sha256 = "8d9e829ce9478db4f35bdb7943308cf02e8a2f58cf9bb10f742462c1d57bf287",
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# strip_prefix = "libtorch",
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# urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-cxx11-abi-shared-with-deps-1.11.0%2Bcu113.zip"],
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#)
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#
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#http_archive(
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# name = "libtorch_pre_cxx11_abi",
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# build_file = "@//third_party/libtorch:BUILD",
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# sha256 = "90159ecce3ff451f3ef3f657493b6c7c96759c3b74bbd70c1695f2ea2f81e1ad",
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# strip_prefix = "libtorch",
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# urls = ["https://download.pytorch.org/libtorch/cu113/libtorch-shared-with-deps-1.11.0%2Bcu113.zip"],
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#)
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# Download these tarballs manually from the NVIDIA website
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# Either place them in the distdir directory in third_party and use the --distdir flag
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# or modify the urls to "file:///<PATH TO TARBALL>/<TARBALL NAME>.tar.gz
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#http_archive(
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# name = "cudnn",
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# build_file = "@//third_party/cudnn/archive:BUILD",
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# sha256 = "0e5d2df890b9967efa6619da421310d97323565a79f05a1a8cb9b7165baad0d7",
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# strip_prefix = "cuda",
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# urls = [
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# "https://developer.nvidia.com/compute/machine-learning/cudnn/secure/8.2.4/11.4_20210831/cudnn-11.4-linux-x64-v8.2.4.15.tgz",
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# ],
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#)
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#
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#http_archive(
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# name = "tensorrt",
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# build_file = "@//third_party/tensorrt/archive:BUILD",
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# sha256 = "826180eaaecdf9a7e76116855b9f1f3400ea9b06e66b06a3f6a0747ba6f863ad",
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# strip_prefix = "TensorRT-8.2.4.2",
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# urls = [
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# "https://developer.nvidia.com/compute/machine-learning/tensorrt/secure/8.2.4/tars/tensorrt-8.2.4.2.linux.x86_64-gnu.cuda-11.4.cudnn8.2.tar.gz",
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# ],
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#)
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####################################################################################
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# Locally installed dependencies (use in cases of custom dependencies or aarch64)
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####################################################################################
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# NOTE: In the case you are using just the pre-cxx11-abi path or just the cxx11 abi path
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# with your local libtorch, just point deps at the same path to satisfy bazel.
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# NOTE: NVIDIA's aarch64 PyTorch (python) wheel file uses the CXX11 ABI unlike PyTorch's standard
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# x86_64 python distribution. If using NVIDIA's version just point to the root of the package
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# for both versions here and do not use --config=pre-cxx11-abi
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new_local_repository(
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name = "libtorch",
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path = "/opt/circleci/.pyenv/versions/3.9.4/lib/python3.9/site-packages/torch",
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build_file = "third_party/libtorch/BUILD"
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)
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new_local_repository(
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name = "libtorch_pre_cxx11_abi",
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path = "/opt/circleci/.pyenv/versions/3.9.4/lib/python3.9/site-packages/torch",
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build_file = "third_party/libtorch/BUILD"
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)
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new_local_repository(
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name = "cudnn",
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path = "/usr/",
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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 = "/usr/",
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build_file = "@//third_party/tensorrt/local:BUILD"
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)
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# #########################################################################
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# # Testing Dependencies (optional - comment out on aarch64)
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# #########################################################################
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# pip_install(
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# name = "torch_tensorrt_py_deps",
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# requirements = "//py:requirements.txt",
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# )
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# pip_install(
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# name = "py_test_deps",
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# requirements = "//tests/py:requirements.txt",
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# )
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pip_install(
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name = "pylinter_deps",
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requirements = "//tools/linter:requirements.txt",
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)

‎py/setup.py‎

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JETPACK_VERSION = None
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__version__ = '1.2.0a0'
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FX_ONLY = False
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def get_git_revision_short_hash() -> str:
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return subprocess.check_output(['git', 'rev-parse', '--short', 'HEAD']).decode('ascii').strip()
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if "--fx-only" in sys.argv:
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FX_ONLY = True
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sys.argv.remove("--fx-only")
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if "--release" not in sys.argv:
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__version__ = __version__ + "+" + get_git_revision_short_hash()
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develop.finalize_options(self)
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def run(self):
141-
global CXX11_ABI
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build_libtorchtrt_pre_cxx11_abi(develop=True, cxx11_abi=CXX11_ABI)
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gen_version_file()
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copy_libtorchtrt()
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develop.run(self)
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if FX_ONLY:
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develop.run(self)
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else:
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global CXX11_ABI
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build_libtorchtrt_pre_cxx11_abi(develop=True, cxx11_abi=CXX11_ABI)
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gen_version_file()
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copy_libtorchtrt()
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develop.run(self)
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class InstallCommand(install):
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install.finalize_options(self)
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157163
def run(self):
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global CXX11_ABI
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build_libtorchtrt_pre_cxx11_abi(develop=False, cxx11_abi=CXX11_ABI)
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gen_version_file()
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copy_libtorchtrt()
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install.run(self)
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if FX_ONLY:
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install.run(self)
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else:
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global CXX11_ABI
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build_libtorchtrt_pre_cxx11_abi(develop=False, cxx11_abi=CXX11_ABI)
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gen_version_file()
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copy_libtorchtrt()
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install.run(self)
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165174
class BdistCommand(bdist_wheel):
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] + (["-D_GLIBCXX_USE_CXX11_ABI=1"] if CXX11_ABI else ["-D_GLIBCXX_USE_CXX11_ABI=0"]),
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undef_macros=["NDEBUG"])
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]
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if FX_ONLY:
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ext_modules=None
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packages=[
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"torch_tensorrt.fx",
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"torch_tensorrt.fx.converters",
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"torch_tensorrt.fx.passes",
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"torch_tensorrt.fx.tools",
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"torch_tensorrt.fx.tracer.acc_tracer",
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]
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package_dir={
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"torch_tensorrt.fx": "torch_tensorrt/fx",
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"torch_tensorrt.fx.converters": "torch_tensorrt/fx/converters",
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"torch_tensorrt.fx.passes": "torch_tensorrt/fx/passes",
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"torch_tensorrt.fx.tools": "torch_tensorrt/fx/tools",
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"torch_tensorrt.fx.tracer.acc_tracer": "torch_tensorrt/fx/tracer/acc_tracer",
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}
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258284
with open("README.md", "r", encoding="utf-8") as fh:
259285
long_description = fh.read()
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282308
},
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zip_safe=False,
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license="BSD",
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packages=find_packages(),
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packages=packages if FX_ONLY else find_packages(),
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package_dir=package_dir if FX_ONLY else {},
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classifiers=[
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"Development Status :: 5 - Stable", "Environment :: GPU :: NVIDIA CUDA",
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"License :: OSI Approved :: BSD License", "Intended Audience :: Developers",

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