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This workflow: 1. Clones PyTorch main repository 2. Clones kerer-ai/pytorch repository 3. Builds PyTorch from source 4. Builds torch_npu extension 5. Tests the installation 6. Uploads build artifacts The workflow supports multiple Python versions (3.9, 3.10, 3.11) and can be triggered on push to master, pull requests, or manually. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Changes: 1. Remove torch installation from requirements.txt to avoid conflict with compiled PyTorch 2. Add Huawei Cloud mirror for faster package installation in China 3. Add warning about missing CANN environment 4. Adjust Python versions to match existing CI (3.8, 3.9, 3.10) The build may still fail due to missing CANN drivers for Ascend NPU support. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This workflow only checks: 1. Build script syntax 2. setup.py syntax 3. Project structure It does not attempt full build, which requires CANN environment. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
1. build-pytorch.yml: Builds PyTorch from source - Supports multiple Python versions (3.9, 3.10, 3.11) - Two build modes: develop (editable) and install - Weekly scheduled builds 2. build-torch-npu-simple.yml: Simplified torch_npu build - Installs pre-built PyTorch - Checks environment and dependencies - Creates build report with next steps - Acknowledges CANN dependency requirement These workflows separate the complex build process and provide better debugging information. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This workflow: 1. Installs the exact PyTorch version required (2.11.0.dev20251215) 2. Includes numpy to avoid warnings 3. Provides detailed analysis of build requirements 4. Documents CANN dependency clearly The build still requires CANN environment for Ascend NPU support. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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