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https://github.com/saymrwulf/onnxruntime.git
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### Description <!-- Describe your changes. --> Old pool | New pool | Notes -- | -- | -- onnxruntime-Win-CPU-2019 | onnxruntime-Win-CPU-2022 | onnxruntime-Win2019-CPU-training | onnxruntime-Win2022-CPU-training-AMD | onnxruntime-Win2019-CPU-training-AMD | onnxruntime-Win2022-CPU-training-AMD | Same as the above onnxruntime-Win2019-GPU-dml-A10 | Need be created | You need to create a new image for it first onnxruntime-Win2019-GPU-T4 | onnxruntime-Win2022-GPU-T4 | onnxruntime-Win2019-GPU-training-T4 | onnxruntime-Win2022-GPU-T4 | Same as the above because we do not have many T4 GPUs onnxruntime-tensorrt8-winbuild-T4| TBD|TBD Win-CPU-2021|onnxruntime-Win-CPU-2022| will do it in next PR Win-CPU-2019|onnxruntime-Win2022-Intel-CPU'| Intel CPU needed for win-ci-pipeline.yml -> `stage: x64_release_dnnl` <br class="Apple-interchange-newline"> ### Motivation and Context With vs2022 we can take the advantage of 64bit compiler. It also with better c++20 support
37 lines
1.1 KiB
YAML
37 lines
1.1 KiB
YAML
name: Windows_CI
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on:
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push:
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branches:
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- master
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- main
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pull_request:
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jobs:
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Onnxruntime-TVM:
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runs-on: windows-latest
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steps:
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- uses: actions/checkout@v3
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with:
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submodules: true
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- uses: actions/setup-python@v3
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with:
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python-version: '3.8.x'
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architecture: 'x64'
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- uses: conda-incubator/setup-miniconda@v2
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with:
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activate-environment: ""
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- name: 'Install LLVM-Dev'
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shell: pwsh
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run: |
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conda install llvmdev=12.0.0
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conda info
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conda list
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- name: 'Add LLVM-Dev binaries to the PATH'
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run: |
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echo "C:/Miniconda/Library/bin" >> $GITHUB_PATH
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- name: 'Setup TVM EP Python requirements'
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run: |
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python3 -m pip install -r ${{ github.workspace }}/tools/ci_build/github/linux/tvm/requirements.txt
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- name: 'Build and Test'
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run: |
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python3 ${{ github.workspace }}/tools/ci_build/build.py --build_dir build --config Release --skip_submodule_sync --parallel --enable_pybind --disable_contrib_ops --disable_ml_ops --skip_onnx_tests --use_tvm
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