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migrate to linux_job_v2 and manylinux 2_28 (#1302)
* Update float8_test.yml to use linux_job_v2 * Update nightly_smoke_test.yml * Update float8_test.yml no binutils * Update post_build_script.sh * Update post_build_script.sh * Update regression_test.yml * Update regression_test.yml
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.github/workflows/float8_test.yml

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@@ -29,7 +29,7 @@ jobs:
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gpu-arch-type: "cuda"
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gpu-arch-version: "12.1"
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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with:
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timeout: 60
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runner: ${{ matrix.runs-on }}
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script: |
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conda create -n venv python=3.9 -y
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conda activate venv
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echo "::group::Install newer objcopy that supports --set-section-alignment"
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yum install -y devtoolset-10-binutils
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export PATH=/opt/rh/devtoolset-10/root/usr/bin/:$PATH
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python -m pip install --upgrade pip
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pip install ${{ matrix.torch-spec }}

.github/workflows/nightly_smoke_test.yml

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@@ -26,7 +26,7 @@ jobs:
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gpu-arch-version: "12.1"
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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with:
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runner: ${{ matrix.runs-on }}
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gpu-arch-type: ${{ matrix.gpu-arch-type }}

.github/workflows/regression_test.yml

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@@ -18,6 +18,38 @@ env:
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HF_TOKEN: ${{ secrets.HF_TOKEN }}
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jobs:
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test-nightly:
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strategy:
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fail-fast: false
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matrix:
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include:
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- name: CUDA Nightly
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runs-on: linux.g5.12xlarge.nvidia.gpu
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torch-spec: '--pre torch==2.6.0.dev20241101 --index-url https://download.pytorch.org/whl/nightly/cu121'
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gpu-arch-type: "cuda"
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gpu-arch-version: "12.1"
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- name: CPU Nightly
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runs-on: linux.4xlarge
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torch-spec: '--pre torch==2.6.0.dev20241101 --index-url https://download.pytorch.org/whl/nightly/cpu'
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gpu-arch-type: "cpu"
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gpu-arch-version: ""
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uses: pytorch/test-infra/.github/workflows/linux_job_v2.yml@main
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with:
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timeout: 120
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runner: ${{ matrix.runs-on }}
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gpu-arch-type: ${{ matrix.gpu-arch-type }}
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gpu-arch-version: ${{ matrix.gpu-arch-version }}
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script: |
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conda create -n venv python=3.9 -y
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conda activate venv
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python -m pip install --upgrade pip
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pip install ${{ matrix.torch-spec }}
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pip install -r dev-requirements.txt
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pip install .
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export CONDA=$(dirname $(dirname $(which conda)))
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export LD_LIBRARY_PATH=$CONDA/lib/:$LD_LIBRARY_PATH
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pytest test --verbose -s
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test:
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strategy:
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fail-fast: false
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torch-spec: 'torch==2.5.1 --index-url https://download.pytorch.org/whl/cu121'
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gpu-arch-type: "cuda"
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gpu-arch-version: "12.1"
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- name: CUDA Nightly
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runs-on: linux.g5.12xlarge.nvidia.gpu
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torch-spec: '--pre torch==2.6.0.dev20241101 --index-url https://download.pytorch.org/whl/nightly/cu121'
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gpu-arch-type: "cuda"
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gpu-arch-version: "12.1"
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- name: CPU 2.3
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runs-on: linux.4xlarge
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torch-spec: 'torch==2.3.0 --index-url https://download.pytorch.org/whl/cpu'
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torch-spec: 'torch==2.5.1 --index-url https://download.pytorch.org/whl/cpu'
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gpu-arch-type: "cpu"
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gpu-arch-version: ""
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- name: CPU Nightly
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runs-on: linux.4xlarge
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torch-spec: '--pre torch==2.6.0.dev20241101 --index-url https://download.pytorch.org/whl/nightly/cpu'
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gpu-arch-type: "cpu"
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gpu-arch-version: ""
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uses: pytorch/test-infra/.github/workflows/linux_job.yml@main
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with:

packaging/post_build_script.sh

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@@ -13,7 +13,7 @@ if [[ "$CU_VERSION" == cu* ]]; then
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WHEEL_NAME=$(ls dist/)
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pushd dist
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manylinux_plat=manylinux2014_x86_64
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manylinux_plat=manylinux_2_28_x86_64
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auditwheel repair --plat "$manylinux_plat" -w . \
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--exclude libtorch.so \
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--exclude libtorch_python.so \

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