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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
You can then build the container using the build command in the [docker README](docker/README.md#instructions)
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If you would like to build outside a docker container, please follow the section [Compiling Torch-TensorRT](#compiling-torch-tensorrt)
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These are the following dependencies used to verify the testcases. Torch-TensorRT can work with other versions, but the tests are not guaranteed to pass.
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- Bazel 5.2.0
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- Libtorch 2.1.0.dev20230314 (built with CUDA 11.7)
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- CUDA 11.7
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- cuDNN 8.5.0
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- TensorRT 8.5.1.7
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- Libtorch 2.1.0.dev20230419 (built with CUDA 11.8)
Copy file name to clipboardExpand all lines: docker/README.md
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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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*[**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**] 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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### 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 8.5.0 and TensorRT 8.6.0
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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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