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Update on "Make test_export training IR compatible"
 In this PR, I make test_export to be compatible with training IR. The idea is that when we flip the IR to non-functional training IR, all these tests should be green. The changes involve reading through the test case, and add necessary decomposition etc to make sure the tests pass. For example, if the tests expect to see mutated buffers returned, we need to get them via running run_decomp. Differential Revision: [D64732360](https://our.internmc.facebook.com/intern/diff/D64732360) [ghstack-poisoned]
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‎.ci/docker/ci_commit_pins/executorch.txt‎

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ca4783992ed7602a39528ba304d61f00396b2a5a
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export-D64151426

‎.ci/docker/libtorch/Dockerfile‎

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@@ -66,6 +66,11 @@ RUN bash ./install_cuda.sh 12.4
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RUN bash ./install_magma.sh 12.4
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RUN ln -sf /usr/local/cuda-12.4 /usr/local/cuda
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FROM cuda as cuda12.6
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RUN bash ./install_cuda.sh 12.6
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RUN bash ./install_magma.sh 12.6
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RUN ln -sf /usr/local/cuda-12.6 /usr/local/cuda
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FROM cpu as rocm
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ARG PYTORCH_ROCM_ARCH
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ENV PYTORCH_ROCM_ARCH ${PYTORCH_ROCM_ARCH}

‎.ci/docker/requirements-ci.txt‎

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#test that import:
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# needed by torchgen utils
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typing-extensions
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typing-extensions>=4.10.0
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#Description: type hints for python
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#Pinned versions:
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#test that import:
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#Pinned versions:
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#test that import:
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onnx==1.16.1
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onnx==1.17.0
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#Description: Required by mypy and test_public_bindings.py when checking torch.onnx._internal
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#Pinned versions:
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#test that import:

‎.ci/pytorch/test.sh‎

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#
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# int main(int argv) {
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# Tensor b = empty({3, 4});
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# auto z = call(b, b.sym_sizes(), b.sym_strides(), c10::nullopt);
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# auto z = call(b, b.sym_sizes(), b.sym_strides(), std::nullopt);
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# }
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export VALGRIND=OFF
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fi

‎.github/scripts/generate_ci_workflows.py‎

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isolated_workflow=True,
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),
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),
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BinaryBuildWorkflow(
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os=OperatingSystem.LINUX,
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package_type="manywheel",
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build_configs=generate_binary_build_matrix.generate_wheels_matrix(
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OperatingSystem.LINUX,
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use_split_build=True,
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arches=["11.8", "12.1", "12.4", "cpu"],
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),
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ciflow_config=CIFlowConfig(
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labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_WHEEL},
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isolated_workflow=True,
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),
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use_split_build=True,
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),
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# See https://github.com/pytorch/pytorch/issues/138750
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# BinaryBuildWorkflow(
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# os=OperatingSystem.LINUX,
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# package_type="manywheel",
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# build_configs=generate_binary_build_matrix.generate_wheels_matrix(
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# OperatingSystem.LINUX,
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# use_split_build=True,
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# arches=["11.8", "12.1", "12.4", "cpu"],
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# ),
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# ciflow_config=CIFlowConfig(
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# labels={LABEL_CIFLOW_BINARIES, LABEL_CIFLOW_BINARIES_WHEEL},
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# isolated_workflow=True,
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# ),
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# use_split_build=True,
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# ),
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BinaryBuildWorkflow(
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os=OperatingSystem.LINUX,
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package_type="conda",
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branches="main",
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),
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BinaryBuildWorkflow(
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os=OperatingSystem.LINUX,
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package_type="manywheel",
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build_configs=generate_binary_build_matrix.generate_wheels_matrix(
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OperatingSystem.LINUX,
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arches=["11.8", "12.1", "12.4"],
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python_versions=["3.9"],
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use_split_build=True,
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),
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ciflow_config=CIFlowConfig(
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labels={LABEL_CIFLOW_PERIODIC},
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),
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branches="main",
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use_split_build=True,
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),
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# See https://github.com/pytorch/pytorch/issues/138750
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# BinaryBuildWorkflow(
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# os=OperatingSystem.LINUX,
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# package_type="manywheel",
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# build_configs=generate_binary_build_matrix.generate_wheels_matrix(
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# OperatingSystem.LINUX,
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# arches=["11.8", "12.1", "12.4"],
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# python_versions=["3.9"],
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# use_split_build=True,
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# ),
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# ciflow_config=CIFlowConfig(
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# labels={LABEL_CIFLOW_PERIODIC},
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# ),
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# branches="main",
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# use_split_build=True,
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# ),
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BinaryBuildWorkflow(
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os=OperatingSystem.LINUX,
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package_type="libtorch",

‎.github/workflows/_runner-determinator.yml‎

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jobs:
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runner-determinator:
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# Don't run on forked repos
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if: github.repository_owner == 'pytorch'
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runs-on: ubuntu-latest
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outputs:
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label-type: ${{ steps.set-condition.outputs.label-type }}

‎.github/workflows/build-libtorch-images.yml‎

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runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
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strategy:
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matrix:
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cuda_version: ["12.4", "12.1", "11.8"]
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cuda_version: ["12.6", "12.4", "12.1", "11.8"]
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env:
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GPU_ARCH_TYPE: cuda
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GPU_ARCH_VERSION: ${{ matrix.cuda_version }}

‎.github/workflows/build-manywheel-images.yml‎

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runs-on: "${{ needs.get-label-type.outputs.label-type }}linux.9xlarge.ephemeral"
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strategy:
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cuda_version: ["12.4", "12.1", "11.8"]
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cuda_version: ["12.6", "12.4", "12.1", "11.8"]
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env:
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GPU_ARCH_TYPE: cuda
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GPU_ARCH_VERSION: ${{ matrix.cuda_version }}

‎.github/workflows/generated-linux-binary-manywheel-split-main.yml‎

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