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Copy file name to clipboardExpand all lines: README.md
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version of the PyTorch C++ ABI. If your source of PyTorch is pytorch.org, likely this is the pre-cxx11-abi in which case you must modify `//docker/dist-build.sh` to not build the
Copy file name to clipboardExpand all lines: docker/Dockerfile
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# Base image starts with CUDA
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ARG BASE_IMG=nvidia/cuda:11.7.1-devel-ubuntu22.04
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FROM ${BASE_IMG} as base
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ENV BASE_IMG=nvidia/cuda:11.7.1-devel-ubuntu22.04
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ARG TENSORRT_VERSION
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ENV TENSORRT_VERSION=${TENSORRT_VERSION}
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RUN test -n "$TENSORRT_VERSION" || (echo "No tensorrt version specified, please use --build-arg TENSORRT_VERSION=x.y.z to specify a version." && exit 1)
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ARG CUDNN_VERSION
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ENV CUDNN_VERSION=${CUDNN_VERSION}
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RUN test -n "$CUDNN_VERSION" || (echo "No cudnn version specified, please use --build-arg CUDNN_VERSION=x.y.z to specify a version." && exit 1)
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ARG PYTHON_VERSION=3.10
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RUN add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /"
Copy file name to clipboardExpand all lines: docker/README.md
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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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* 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 CUDNN and TensorRT must be specified as build-args, with major, minor, and patch versions as in: `--build-arg TENSORRT_VERSION=a.b.c --build-arg CUDNN_VERSION=x.y.z`
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* The desired versions of CUDNN and TensorRT must be specified as build-args, with majorand minor versions as in: `--build-arg TENSORRT_VERSION=a.b --build-arg CUDNN_VERSION=x.y`
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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:11.7.1-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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### Instructions
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- The example below uses CUDNN 8.5.0 and TensorRT 8.5.1
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- The example below uses CUDNN 8.5 and TensorRT 8.5
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- See <ahref="https://github.com/pytorch/TensorRT#dependencies">dependencies</a> for a list of current default dependencies.
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