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Copy file name to clipboardExpand all lines: docker/README.md
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# Building a Torch-TensorRT container
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* Use `Dockerfile` to build a container which provides the exact development environment that our master branch is usually tested against.
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* Use `Dockerfile` to build a container which provides the exact development environment that our main branch is usually tested against.
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* The `Dockerfile` currently uses <ahref="https://github.com/bazelbuild/bazelisk">Bazelisk</a> to select the Bazel version, and uses the exact library versions of Torch and CUDA listed in <ahref="https://github.com/pytorch/TensorRT#dependencies">dependencies</a>.
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* The desired versions of TensorRT must be specified as build-args, with major and minor versions as in: `--build-arg TENSORRT_VERSION=a.b`
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*[**Optional**] The desired base image be changed by explicitly setting a base image, as in `--build-arg BASE_IMG=nvidia/cuda:11.8.0-devel-ubuntu22.04`, though this is optional
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*[**Optional**] The desired base image be changed by explicitly setting a base image, as in `--build-arg BASE_IMG=nvidia/cuda:11.8.0-devel-ubuntu22.04`, though this is optional.
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*[**Optional**] Additionally, the desired Python version can be changed by explicitly setting a version, as in `--build-arg PYTHON_VERSION=3.10`, though this is optional as well.
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* This `Dockerfile` installs `pre-cxx11-abi` versions of Pytorch and builds Torch-TRT using `pre-cxx11-abi` libtorch as well.
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* This `Dockerfile` installs `cxx11-abi` versions of Pytorch and builds Torch-TRT using `cxx11-abi` libtorch as well. As of torch 2.7, torch requires `cxx11-abi` for all CUDA 11.8, 12.4, and 12.6.
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Note: By default the container uses the `pre-cxx11-abi` version of Torch + Torch-TRT. If you are using a workflow that requires a build of PyTorch on the CXX11 ABI (e.g. using the PyTorch NGC containers as a base image), add the Docker build argument: `--build-arg USE_CXX11_ABI=1`
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Note: By default the container uses the `cxx11-abi` version of Torch + Torch-TRT. If you are using a workflow that requires a build of PyTorch on the PRE CXX11 ABI, please add the Docker build argument: `--build-arg USE_PRE_CXX11_ABI=1`
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### Dependencies
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* Install nvidia-docker by following https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/install-guide.html#docker
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### Instructions
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- The example below uses TensorRT 10.6.0.26
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- The example below uses TensorRT 10.7.0.23
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- See <ahref="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
NOTE: For all of the above cases you must correctly declare the source of PyTorch you intend to use in your WORKSPACE file for both Python and C++ builds. See below for more information
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.. code-block:: shell
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python3 setup.py install --use-cxx11-abi
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python3 setup.py install
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If you have a build of PyTorch that uses Pre-CXX11 ABI drop the ``--use-cxx11-abi`` flag
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If you have a build of PyTorch that uses Pre-CXX11 ABI drop the ``--use-pre-cxx11-abi`` flag
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If you are building for Jetpack 4.5 add the ``--jetpack-version 5.0`` flag
For Linux x86_64 platform, Pytorch libraries default to pre cxx11 abi. So, please use `python3 setup.py install`.
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On Jetson platforms, NVIDIA hosts <a href="https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-10-now-available/72048">pre-built Pytorch wheel files</a>. These wheel files are built withCXX11ABI. So on jetson platforms, please use `python3 setup.py install --jetpack-version 4.6--use-cxx11-abi`
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On Jetson platforms, NVIDIA hosts <a href="https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-10-now-available/72048">pre-built Pytorch wheel files</a>. These wheel files are built withCXX11ABI. So on jetson platforms, please use `python3 setup.py install --jetpack-version 4.6`
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