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[Feature] Enhance build script, add pre_wheel logic (#4729)

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* Enhance build script, add pre_wheel logic

Updated copyright year and added precompiled wheel installation logic.

* update the nvidia_gpu.md, add pre_wheel description

* fix zh .md

* update the url, automatically detect CUDA and SM

* Fix GPU architecture string formatting in build.sh

* Change default for FD_USE_PRECOMPILED to 0

* fix build.sh

* add ./dist, pre-wheel path

* simplify the process,just save the whl

* del pre_wheel dir

* fix function name, extract_ops_from_precompiled_wheel

* fix docs

* add default commitID in docs

---------

Co-authored-by: plusNew001 <95567040+plusNew001@users.noreply.github.com>
This commit is contained in:
Echo-Nie
2025-11-13 19:03:52 +08:00
committed by GitHub
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docs/get_started/installation/nvidia_gpu.md
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@@ -80,6 +80,51 @@ bash build.sh 1 python false [80,90]
```
The built packages will be in the ```FastDeploy/dist``` directory.
## 5. Precompiled Operator Wheel Packages
FastDeploy provides precompiled GPU operator wheel packages for quick setup without building the entire source code.
This method currently supports **SM90 architecture (e.g., H20/H100)** and **CUDA 12.6** environments only.
> By default, `build.sh` compiles all custom operators from source.To use the precompiled package, enable it with the `FD_USE_PRECOMPILED` parameter.
> If the precompiled package cannot be downloaded or does not match the current environment, the system will automatically fall back to `4. Build Wheel from Source`.
First, install paddlepaddle-gpu.
For detailed instructions, please refer to the [PaddlePaddle Installation Guide](https://www.paddlepaddle.org.cn/).
```shell
python -m pip install paddlepaddle-gpu==3.2.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/
```
Then, clone the FastDeploy repository and build using the precompiled operator wheels:
```shell
git clone https://github.com/PaddlePaddle/FastDeploy
cd FastDeploy
# Argument 1: Whether to build wheel package (1 for yes)
# Argument 2: Python interpreter path
# Argument 3: Whether to compile CPU inference operators (false for GPU only)
# Argument 4: Target GPU architectures (currently supports [90])
# Argument 5: Whether to use precompiled operators (1 for enable)
# Argument 6 (optional): Specific commitID for precompiled operators(The default is the current commit ID.)
# Use precompiled operators for accelerated build
bash build.sh 1 python false [90] 1
# Use precompiled wheel from a specific commit
bash build.sh 1 python false [90] 1 7dbd9412b0de47aacad9011e8ace492af7247620
```
The downloaded wheel packages will be stored in the `FastDeploy/pre_wheel` directory.
After the build completes, the operator binaries can be found in `FastDeploy/fastdeploy/model_executor/ops/gpu`.
> **Notes:**
>
> - This mode prioritizes downloading precompiled GPU operator wheels to reduce build time.
> - Currently supports **GPU + SM90 + CUDA 12.6** only.
> - For custom architectures or modified operator logic, please use **source compilation (Section 4)**.
> - You can check whether the precompiled wheel for a specific commit has been successfully built on the [FastDeploy CI Build Status Page](https://github.com/PaddlePaddle/FastDeploy/actions/workflows/ci_image_update.yml).
## Environment Verification
After installation, verify the environment with this Python code: