wehub-resource-sync
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Book-CI / test (macos-latest) (push) Waiting to run
Deploy / deploy (macos-latest) (push) Waiting to run
Deploy / deploy (ubuntu-latest) (push) Waiting to run
Deploy / deploy (windows-latest) (push) Waiting to run
Release to PyPI / Build & publish sglang-kt (push) Waiting to run
Release to PyPI / Build kt-kernel (Python 3.11) (push) Waiting to run
Release to PyPI / Build kt-kernel (Python 3.12) (push) Waiting to run
Release to PyPI / Publish kt-kernel to PyPI (push) Blocked by required conditions
Book-CI / test (ubuntu-latest) (push) Waiting to run
Book-CI / test (windows-latest) (push) Waiting to run
Release Fake Tag / publish (push) Waiting to run
284 lines
11 KiB
YAML
284 lines
11 KiB
YAML
name: Release to PyPI
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on:
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push:
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branches:
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- main
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paths:
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- "version.py"
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workflow_dispatch:
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inputs:
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test_pypi:
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description: 'Publish to TestPyPI instead of PyPI (for testing)'
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required: false
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default: 'false'
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type: choice
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options:
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- 'true'
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- 'false'
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permissions:
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contents: read
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jobs:
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# ── sglang-kt (must be on PyPI before users can pip install kt-kernel) ──
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build-and-publish-sglang-kt:
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name: Build & publish sglang-kt
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runs-on: [self-hosted, linux, x64]
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if: github.repository == 'kvcache-ai/ktransformers' && github.ref == 'refs/heads/main'
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environment: prod
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permissions:
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id-token: write
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contents: read
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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submodules: recursive
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.12'
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- name: Install build tools
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run: |
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python -m pip install --upgrade pip
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pip install build wheel setuptools twine
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- name: Build sglang-kt wheel
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working-directory: third_party/sglang/python
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run: |
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KT_VERSION=$(python3 -c "exec(open('${{ github.workspace }}/version.py').read()); print(__version__)")
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export SGLANG_KT_VERSION="$KT_VERSION"
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echo "Building sglang-kt v${KT_VERSION} wheel..."
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python -m build --wheel -v
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ls dist/ | grep -q "sglang_kt" || (echo "ERROR: Wheel name does not contain sglang_kt" && exit 1)
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- name: Publish sglang-kt to PyPI
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if: github.event.inputs.test_pypi != 'true'
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
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run: |
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python -m twine upload --skip-existing --verbose third_party/sglang/python/dist/*.whl
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- name: Publish sglang-kt to TestPyPI (if requested)
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if: github.event.inputs.test_pypi == 'true'
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.TEST_PYPI_API_TOKEN }}
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run: |
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python -m twine upload --repository testpypi --skip-existing --verbose third_party/sglang/python/dist/*.whl
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# ── kt-kernel ──
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build-kt-kernel:
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name: Build kt-kernel (Python ${{ matrix.python-version }})
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runs-on: [self-hosted, linux, x64, gpu]
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strategy:
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fail-fast: false
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matrix:
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python-version: ['3.11', '3.12']
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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with:
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submodules: recursive
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v4
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with:
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python-version: ${{ matrix.python-version }}
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- name: Verify CUDA availability
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run: |
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nvidia-smi || (echo "ERROR: GPU not available" && exit 1)
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nvcc --version || (echo "ERROR: CUDA toolkit not found" && exit 1)
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- name: Install dependencies
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run: |
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# System packages (cmake/libhwloc-dev/pkg-config/libnuma-dev) are expected to be
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# preinstalled on self-hosted runners. Skip apt-get to avoid sudo dependency.
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for pkg in cmake pkg-config; do command -v $pkg >/dev/null || { echo "ERROR: $pkg missing on runner"; exit 1; }; done
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python -m pip install --upgrade pip
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pip install build wheel setuptools
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pip install torch --index-url https://download.pytorch.org/whl/cu128
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- name: Build kt-kernel wheel
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working-directory: kt-kernel
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env:
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CPUINFER_BUILD_ALL_VARIANTS: '1'
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CPUINFER_ENABLE_CPPTRACE: '0'
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CPUINFER_USE_CUDA: '1'
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CPUINFER_CUDA_ARCHS: '80;86;89;90;120'
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CPUINFER_CUDA_STATIC_RUNTIME: '1'
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CPUINFER_BUILD_TYPE: 'Release'
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CPUINFER_PARALLEL: '4'
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CPUINFER_FORCE_REBUILD: '1'
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CUDA_HOME: '/usr/local/cuda-12.8'
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run: |
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echo "Building kt-kernel with:"
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echo " - CUDA support (SM 80, 86, 89, 90, 120)"
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echo " - CPU multi-variant (AMX, AVX512, AVX2)"
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python -m build --wheel -v
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- name: Verify wheel
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working-directory: kt-kernel
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run: |
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echo "Generated wheel:"
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ls -lh dist/
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# Install and test
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pip install dist/*.whl
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python -c "import kt_kernel; print(f'✓ Version: {kt_kernel.__version__}')"
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python -c "import kt_kernel; print(f'✓ CPU variant: {kt_kernel.__cpu_variant__}')"
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# Verify CUDA support
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python -c "
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from kt_kernel import kt_kernel_ext
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cpu_infer = kt_kernel_ext.CPUInfer(4)
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methods = dir(cpu_infer)
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has_cuda = 'submit_with_cuda_stream' in methods
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print(f'✓ CUDA support: {has_cuda}')
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"
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# Verify CPU multi-variant support
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echo "Checking CPU variants in wheel..."
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python -m zipfile -l dist/*.whl | grep "_kt_kernel_ext_" || echo "Warning: No variant .so files found"
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python -m zipfile -l dist/*.whl | grep "_kt_kernel_ext_amx.cpython" && echo "✓ AMX variant found" || echo "Note: AMX variant missing"
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python -m zipfile -l dist/*.whl | grep "_kt_kernel_ext_avx512" && echo "✓ AVX512 variants found" || echo "Note: AVX512 variants missing"
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python -m zipfile -l dist/*.whl | grep "_kt_kernel_ext_avx2.cpython" && echo "✓ AVX2 variant found" || echo "Note: AVX2 variant missing"
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# Verify static linking (should NOT depend on libcudart.so).
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# Use $RUNNER_TEMP (honors TMPDIR redirect to /mnt) — /tmp is the
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# system disk on self-hosted runners and can be tight.
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CHECK_DIR="${RUNNER_TEMP:-/tmp}/check"
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rm -rf "$CHECK_DIR"
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unzip -q dist/*.whl -d "$CHECK_DIR"
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if ldd "$CHECK_DIR"/kt_kernel/*.so 2>/dev/null | grep -q "libcudart.so"; then
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echo "ERROR: Dynamic cudart found, should be statically linked"
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exit 1
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else
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echo "✓ CUDA runtime statically linked"
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fi
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- name: Repair wheel for manylinux
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working-directory: kt-kernel
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run: |
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pip install auditwheel patchelf
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mkdir -p wheelhouse
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for wheel in dist/*.whl; do
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auditwheel repair "$wheel" --plat manylinux_2_35_x86_64 --exclude libcuda.so.1 -w wheelhouse/
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done
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rm -f dist/*.whl && cp wheelhouse/*.whl dist/
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- name: Upload artifact
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uses: actions/upload-artifact@v4
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with:
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name: kt-kernel-wheels-py${{ matrix.python-version }}
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path: kt-kernel/dist/*.whl
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retention-days: 7
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publish-pypi:
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name: Publish kt-kernel to PyPI
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needs: [build-and-publish-sglang-kt, build-kt-kernel]
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runs-on: [self-hosted, linux, x64]
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if: github.repository == 'kvcache-ai/ktransformers' && github.ref == 'refs/heads/main'
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environment: prod
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permissions:
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id-token: write # For trusted publishing (OIDC)
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contents: read
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steps:
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- name: Download all wheel artifacts
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uses: actions/download-artifact@v4
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with:
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path: artifacts/
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- name: Set up Python
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uses: actions/setup-python@v4
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with:
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python-version: '3.12'
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- name: Organize wheels into dist/
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run: |
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mkdir -p dist/
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find artifacts/ -name "*.whl" -exec cp {} dist/ \;
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echo "Wheels to publish:"
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ls -lh dist/
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- name: Get version from wheel
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id: get_version
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run: |
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# Extract version from first wheel filename
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wheel_name=$(ls dist/*.whl | head -1 | xargs basename)
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# Extract version (format: kt_kernel-X.Y.Z-...)
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version=$(echo "$wheel_name" | sed 's/kt_kernel-\([0-9.]*\)-.*/\1/')
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echo "VERSION=$version" >> $GITHUB_OUTPUT
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echo "Publishing version: $version"
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- name: Install twine
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run: |
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python -m pip install --upgrade pip
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pip install twine
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- name: Publish to TestPyPI (if requested)
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if: github.event.inputs.test_pypi == 'true'
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.TEST_PYPI_API_TOKEN }}
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run: |
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python -m twine upload \
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--repository testpypi \
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--skip-existing \
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--verbose \
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dist/*.whl
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- name: Publish to PyPI
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if: github.event.inputs.test_pypi != 'true'
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env:
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TWINE_USERNAME: __token__
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TWINE_PASSWORD: ${{ secrets.PYPI_API_TOKEN }}
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run: |
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python -m twine upload \
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--skip-existing \
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--verbose \
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dist/*.whl
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- name: Create release summary
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run: |
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echo "## 🎉 kt-kernel v${{ steps.get_version.outputs.VERSION }} Published to PyPI" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Installation" >> $GITHUB_STEP_SUMMARY
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echo '```bash' >> $GITHUB_STEP_SUMMARY
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echo "pip install kt-kernel==${{ steps.get_version.outputs.VERSION }}" >> $GITHUB_STEP_SUMMARY
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echo '```' >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Published Wheels" >> $GITHUB_STEP_SUMMARY
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echo "Total: $(ls -1 dist/*.whl | wc -l) wheels (Python 3.10, 3.11, 3.12)" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "### Features" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "**CPU Multi-Variant Support:**" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ AMX (Intel Sapphire Rapids+, 2023)" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ AVX512 Base/VNNI/VBMI/BF16 (Intel Skylake-X/Ice Lake/Cascade Lake, 2017+)" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ AVX2 (Maximum compatibility, 2013+)" >> $GITHUB_STEP_SUMMARY
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echo "- 🔧 Runtime CPU detection: Automatically selects optimal variant" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "**CUDA Support:**" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ SM 80 (Ampere: A100, RTX 3000 series)" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ SM 86 (Ampere: RTX 3060-3090)" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ SM 89 (Ada Lovelace: RTX 4000 series)" >> $GITHUB_STEP_SUMMARY
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echo "- ✅ SM 90 (Hopper: H100)" >> $GITHUB_STEP_SUMMARY
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echo "- 🔧 Static CUDA runtime: Compatible with CUDA 11.8+ and 12.x drivers" >> $GITHUB_STEP_SUMMARY
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echo "- 🔧 Works on CPU-only systems (CUDA features disabled gracefully)" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "**Requirements:**" >> $GITHUB_STEP_SUMMARY
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echo "- Python 3.10, 3.11, or 3.12" >> $GITHUB_STEP_SUMMARY
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echo "- Linux x86-64 (manylinux_2_17 compatible)" >> $GITHUB_STEP_SUMMARY
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echo "- For CUDA features: NVIDIA driver with CUDA 11.8+ or 12.x support" >> $GITHUB_STEP_SUMMARY
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echo "" >> $GITHUB_STEP_SUMMARY
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echo "PyPI link: https://pypi.org/project/kt-kernel/${{ steps.get_version.outputs.VERSION }}/" >> $GITHUB_STEP_SUMMARY
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