【Hackathon 10th Spring No.45】FastDeploy 支持在 T4/V100 硬件的编译

[playaswd]

Motivation

Support FastDeploy compilation on NVIDIA T4/V100 (SM75/SM70) and fix CI startup compatibility when Paddle does not expose paddle.compat.

Modifications

• Update custom_ops/setup_ops.py to gate architecture-specific CUDA sources/macros and deduplicate source entries.
• Update custom_ops/gpu_ops/cpp_extensions.cc to register/export SM-specific ops with compile-time guards.
• Update fastdeploy/__init__.py to enable torch-proxy compatibility in a version-safe way:
  • prefer paddle.enable_compat(scope={"triton"})
  • fallback to paddle.compat.enable_torch_proxy(scope={"triton"})
  • otherwise skip with warning.

Usage or Command

# Build
python -m pip install -U pybind11 pybind11-global
MAX_JOBS=8 python setup.py bdist_wheel

# Install
python -m pip install -U dist/fastdeploy_gpu-*.whl

# Verify
python -c "import fastdeploy; print(fastdeploy.__file__)"
python -m pip show fastdeploy-gpu

Accuracy Tests

• This PR does not change model forward numerical logic.
• It changes build/source selection and import-time compatibility guards only.
• Build and install were verified on SM86/SM75/SM70 environments; the HPU CI error path (paddle.compat missing) is addressed by compatibility fallback.

Checklist

• PR description sections are complete and non-empty.
• Formatting checks (pre-commit) passed for modified files.
• A new commit has been pushed and CI can be re-run on the latest head.

[paddle-bot]

Thanks for your contribution!

[codecov-commenter]

Codecov Report

✅ All modified and coverable lines are covered by tests.
⚠️ Please upload report for BASE (develop@ddb06ff). Learn more about missing BASE report.

Additional details and impacted files

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  Files              ?      394           
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  Misses             ?    12456           
  Partials           ?     2786           

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