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.github/scripts/generate_binary_build_matrix.py

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@@ -150,7 +150,7 @@ def initialize_globals(channel: str, build_python_only: bool) -> None:
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},
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CPU: "pytorch/manylinux2_28-builder:cpu",
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XPU: "pytorch/manylinux2_28-builder:xpu",
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# TODO: Migrate CUDA_AARCH64 image to manylinux2_28_aarch64-builder:cuda12.4
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# TODO: Migrate CUDA_AARCH64 image to manylinux2_28_aarch64-builder:cuda12.6
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CPU_AARCH64: "pytorch/manylinux2_28_aarch64-builder:cpu-aarch64",
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CUDA_AARCH64: "pytorch/manylinuxaarch64-builder:cuda12.6",
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}

.github/workflows/release-linux.yml

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@@ -96,8 +96,8 @@ jobs:
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echo "${MATRIX_BLOB}"
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echo "matrix=${MATRIX_BLOB}" >> "${GITHUB_OUTPUT}"
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release-other-artifacts:
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name: Release torch-tensorrt wheel and cxx11 tarball artifacts
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release-wheel-artifacts:
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name: Release torch-tensorrt wheel artifacts
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needs: [generate-release-wheel-matrix]
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strategy:
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fail-fast: false

.github/workflows/release-wheel-linux.yml

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@@ -204,10 +204,6 @@ jobs:
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release/tarball/libtorchtrt-${BUILD_VERSION}-tensorrt${TRT_VERSION}-cuda${CU_VERSION:2}-libtorch${PYTORCH_VERSION}-x86_64-linux.tar.gz
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else
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${CONDA_RUN} python setup.py bdist_wheel --release
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cp bazel-bin/libtorchtrt.tar.gz \
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release/tarball/libtorchtrt-${BUILD_VERSION}-tensorrt${TRT_VERSION}-cuda${CU_VERSION:2}-libtorch${PYTORCH_VERSION}-x86_64-linux.tar.gz
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${CONDA_RUN} python -m pip install auditwheel
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${CONDA_RUN} python -m auditwheel repair \
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$(cat py/ci/soname_excludes.params) \

py/README.md

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@@ -31,7 +31,7 @@ torch.jit.save(trt_ts_module, "trt_torchscript_module.ts") # save the TRT embedd
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| ABI / Platform | Installation command |
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| --------------------------------------- | ----------------------------------------------------------------- |
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| CXX ABI (Linux x86_64) | python3 setup.py install |
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| CXX11 ABI (Linux x86_64) | python3 setup.py install |
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| CXX11 ABI (Jetson platform aarch64) | python3 setup.py install --jetpack-version 4.6 |
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