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[Docs] Update Release Note (#7302)

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YuBaoku
2026-04-10 15:26:53 +08:00
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docs/get_started/installation/nvidia_gpu.md
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@@ -12,7 +12,7 @@ The following installation methods are available when your environment meets the
## 1. Pre-built Docker Installation (Recommended)
**Notice**: The pre-built image supports SM 80/86/89/90 architecture GPUs (e.g. A800/H800/L20/L40/4090).
**Notice**: The pre-built image supports SM 80/86/89/90 architecture GPUs (e.g. A800/H800/L20/L40/4090), and requires Python 3.10.
```shell
# CUDA 12.6
@@ -26,13 +26,13 @@ docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12
First install paddlepaddle-gpu. For detailed instructions, refer to [PaddlePaddle Installation](https://www.paddlepaddle.org.cn/en/install/quick?docurl=/documentation/docs/en/develop/install/pip/linux-pip_en.html)
```shell
# Install stable release
# CUDA
# CUDA 12.6
python -m pip install paddlepaddle-gpu==3.3.1 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/
# CUDA 12.9
python -m pip install paddlepaddle-gpu==3.3.1 -i https://www.paddlepaddle.org.cn/packages/stable/cu129/
# Install latest Nightly build
# CUDA
# CUDA 12.6
python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/
# CUDA 12.9
python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu129/
@@ -41,15 +41,15 @@ python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/
Then install fastdeploy. **Do not install from PyPI**. Use the following methods instead (supports SM80/86/89/90 GPU architectures).
**Note**: Stable FastDeploy release pairs with stable PaddlePaddle; Nightly Build FastDeploy pairs with Nightly Build PaddlePaddle. The `--extra-index-url` is only used for downloading fastdeploy-gpu's dependencies; fastdeploy-gpu itself must be installed from the Paddle source specified by `-i`.
```
```shell
# Install stable release FastDeploy
# CUDA
# CUDA 12.6
python -m pip install fastdeploy-gpu==2.5.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
# CUDA 12.9
python -m pip install fastdeploy-gpu==2.5.0 -i https://www.paddlepaddle.org.cn/packages/stable/cu129/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
# Install Nightly Build FastDeploy
# CUDA
# CUDA 12.6
python -m pip install fastdeploy-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu126/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
# CUDA 12.9
python -m pip install fastdeploy-gpu -i https://www.paddlepaddle.org.cn/packages/nightly/cu129/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
@@ -57,7 +57,7 @@ python -m pip install fastdeploy-gpu -i https://www.paddlepaddle.org.cn/packages
## 3. Build from Source Using Docker
> Note: `dockerfiles/Dockerfile.gpu` currently supports CUDA 12.6 only, targeting SM 80/86/89/90 architectures. To support other architectures, modify ```bash build.sh 1 python false [80,90]``` in the Dockerfile. It's recommended to specify no more than 2 architectures.
> Note: `dockerfiles/Dockerfile.gpu` currently supports CUDA 12.6 only, targeting SM 80/86/89/90 architectures, and requires Python 3.10. To support other architectures, modify ```bash build.sh 1 python false [80,90]``` in the Dockerfile. It's recommended to specify no more than 2 architectures.
```shell
git clone https://github.com/PaddlePaddle/FastDeploy
@@ -86,7 +86,7 @@ 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 SM80/90 architecture (e.g., A100/H100) and CUDA 12.6 environments only.
FastDeploy provides precompiled GPU operator wheel packages for quick setup without building the entire source code. This method currently supports **SM80/90 architecture (e.g., A100/H100)** **CUDA 12.6** and **Python 3.10** 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`.
@@ -124,7 +124,7 @@ After the build completes, the operator binaries can be found in `FastDeploy/fas
> **Notes:**
>
> - This mode prioritizes downloading precompiled GPU operator wheels to reduce build time.
> - Supports **GPU, SM80/86/89/90.
> - Currently supports **GPU, SM80/90, CUDA 12.6, Python3.10** 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/ce_job.yml).