apps/FastDeploy
1
0
Fork 0
mirror of https://github.com/PaddlePaddle/FastDeploy.git synced 2026-04-23 00:17:25 +08:00
Code Issues Actions 19 Packages Projects Releases Wiki Activity

[Cherry-Pick][Docs] Update Release Note(#7302) (#7336)

Browse Source
This commit is contained in:
YuBaoku
2026-04-11 16:47:33 +08:00
committed by GitHub
parent 9985b192b4
commit d9d5740c4d
4 changed files with 49 additions and 35 deletions
Download Patch File Download Diff File Expand all files Collapse all files
dockerfiles/Dockerfile.gpu
+4 -4
View File
@@ -1,6 +1,6 @@
FROM ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:tag-base
ARG PADDLE_VERSION=3.3.0
ARG FD_VERSION=2.4.0
ARG PADDLE_VERSION=3.3.1
ARG FD_VERSION=2.5.0
ENV DEBIAN_FRONTEND=noninteractive
@@ -16,8 +16,8 @@ RUN python -m pip uninstall paddlepaddle-gpu fastdeploy-gpu -y
RUN python -m pip install --no-cache-dir paddlepaddle-gpu==${PADDLE_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/cu126/
# build and install FastDeploy
RUN python -m pip install --no-cache-dir fastdeploy-gpu==${FD_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-gpu-80_90/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
RUN python -m pip install --no-cache-dir fastdeploy-gpu==${FD_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/cu126/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
ENV http_proxy=""
ENV https_proxy=""
ENV no_proxy=""
ENV no_proxy=""
dockerfiles/Dockerfile.xpu
+26 -15
View File
@@ -1,11 +1,7 @@
FROM ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddlenlp:llm-base-gcc12.3-xpu-xft20250402-v1.1
ARG PADDLE_VERSION=3.1.0
ARG FD_VERSION=2.0.0
FROM ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddleqa:xpu-ubuntu2204-x86_64-gcc123-py310
WORKDIR /workspace
ENV http_proxy=http://agent.baidu.com:8891
ENV https_proxy=http://agent.baidu.com:8891
COPY requirements.txt .
RUN echo "\
deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy main restricted universe multiverse \n\
@@ -15,18 +11,33 @@ deb https://mirrors.tuna.tsinghua.edu.cn/ubuntu/ jammy-backports main restricted
RUN apt-get update && apt-get install -y libibverbs-dev librdmacm-dev cmake pybind11-dev
# uninstall existing package
RUN python -m pip uninstall paddlepaddle-gpu paddlepaddle-xpu -y
# install paddlepaddle-xpu
RUN python -m pip install --no-cache-dir --progress-bar off paddlepaddle-xpu==${PADDLE_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/xpu-p800/
RUN python -m pip uninstall paddlepaddle-gpu paddlepaddle-xpu fastdeploy-xpu -y
RUN python -m pip uninstall -y Pillow && rm -rf /usr/local/lib/python3.10/dist-packages/Pillow* && rm -rf /usr/local/lib/python3.10/dist-packages/pillow* && python -m pip install Pillow==11.3.0
RUN python -m pip install --no-cache-dir fastdeploy-xpu==${FD_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple
# install paddlepaddle-xpu
ARG PADDLE_VERSION=3.3.1
RUN if [ "$PADDLE_VERSION" = "nightly" ]; then \
python -m pip install --no-cache-dir --progress-bar off paddlepaddle-xpu -i https://www.paddlepaddle.org.cn/packages/nightly/xpu-p800/; \
else \
python -m pip install --no-cache-dir --progress-bar off paddlepaddle-xpu==${PADDLE_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/xpu-p800/; \
fi
# install fastdeploy-xpu
ARG INSTALL_REQUIREMENTS=true
ARG INSTALL_FASTDEPLOY=true
ARG FASTDEPLOY_VERSION=2.5.0
RUN if [ "$INSTALL_FASTDEPLOY" = "true" ]; then \
python -m pip install --no-cache-dir fastdeploy-xpu==${FASTDEPLOY_VERSION} -i https://www.paddlepaddle.org.cn/packages/stable/fastdeploy-xpu-p800/ --extra-index-url https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple; \
fi
RUN if [ "$INSTALL_REQUIREMENTS" = "true" ]; then \
python -m pip install -r requirements.txt; \
fi
RUN mkdir -p /workspace/deps && cd /workspace/deps && \
wget https://klx-sdk-release-public.su.bcebos.com/xre/kl3-release/5.0.21.21/xre-Linux-x86_64-5.0.21.21.tar.gz && \
tar -zxf xre-Linux-x86_64-5.0.21.21.tar.gz && mv xre-Linux-x86_64-5.0.21.21 xre
ENV PATH=/workspace/deps/xre/bin:$PATH
ENV http_proxy=""
ENV https_proxy=""
ENV no_proxy=""
ENV PATH=/workspace/deps/xre/bin:$PATH
docs/get_started/installation/nvidia_gpu.md
+10 -10
View File
@@ -12,10 +12,13 @@ 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
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.5.0
# CUDA 12.9
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.9:2.5.0
```
## 2. Pre-built Pip Installation
@@ -38,7 +41,7 @@ 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 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
@@ -54,7 +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``` by default supports SM 80/90 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
@@ -69,8 +72,6 @@ First install paddlepaddle-gpu. For detailed instructions, refer to [PaddlePaddl
```shell
python -m pip install paddlepaddle-gpu==3.3.1 -i https://www.paddlepaddle.org.cn/packages/stable/cu126/
```
Then clone the source code and build:
```shell
git clone https://github.com/PaddlePaddle/FastDeploy
cd FastDeploy
@@ -85,8 +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`.
@@ -115,7 +115,7 @@ cd FastDeploy
bash build.sh 1 python false [90] 1
# Use precompiled wheel from a specific commit
bash build.sh 1 python false [90] 1 8a9e7b53af4a98583cab65e4b44e3265a93e56d2
bash build.sh 1 python false [90] 1 d693d4be1448d414097882386fdc24c8bec2a63a
```
The downloaded wheel packages will be stored in the `FastDeploy/pre_wheel` directory.
@@ -124,9 +124,9 @@ 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.
> - Currently supports **GPU, SM80/90, CUDA 12.6** only.
> - 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/ci_image_update.yml).
> - 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).
## Environment Verification
docs/zh/get_started/installation/nvidia_gpu.md
+9 -6
View File
@@ -14,10 +14,13 @@
## 1. 预编译Docker安装(推荐)
**注意**： 预编译镜像支持 80/86/89/90 架构的GPU硬件 (如 A800/H800/L20/L40/4090)。
**注意**： 预编译镜像支持 80/86/89/90 架构的GPU硬件 (如 A800/H800/L20/L40/4090) 且仅支持 Python 3.10。
``` shell
# CUDA 12.6
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.6:2.5.0
# CUDA 12.9
docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/fastdeploy-cuda-12.9:2.5.0
```
## 2. 预编译Pip安装
@@ -41,7 +44,7 @@ python -m pip install --pre paddlepaddle-gpu -i https://www.paddlepaddle.org.cn/
再安装 fastdeploy，**注意不要通过pypi源安装**，需要通过如下方式安装(目前支持80/86/89/90四个架构GPU）
**注意**: 稳定版本的FastDeploy搭配稳定版本的PaddlePaddle; 而Nightly Build的FastDeploy则对应Nightly Build的PaddlePaddle。其中 `--extra-index-url` 仅用于安装 fastdeploy-gpu 所需的依赖包，fastdeploy-gpu 本身必须从 `-i` 指定的 Paddle 源安装。
```
```shell
# 安装稳定版本FastDeploy
# 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
@@ -57,7 +60,7 @@ python -m pip install fastdeploy-gpu -i https://www.paddlepaddle.org.cn/packages
## 3. 镜像自行构建
> 注意 ```dockerfiles/Dockerfile.gpu``` 默认编译的架构支持SM 80/90，如若需要支持其它架构，需自行修改Dockerfile中的 ```bash build.sh 1 python false [80,90]```，建议不超过2个架构。
> 注意 ```dockerfiles/Dockerfile.gpu``` 默认编译产物仅支持 SM 80/86/89/90 架构，基于 CUDA 12.6 环境构建，且仅支持 Python 3.10，如若需要支持其它架构，需自行修改Dockerfile中的 ```bash build.sh 1 python false [80,90]```，建议不超过2个架构。
```
git clone https://github.com/PaddlePaddle/FastDeploy
@@ -91,7 +94,7 @@ bash build.sh 1 python false [80,90]
## 5. 算子预编译 Wheel 包
FastDeploy 提供了 GPU 算子预编译版 Wheel 包，可在无需完整源码编译的情况下快速构建。该方式当前仅支持 **SM80/90 架构（A100/H100等）** 和 **CUDA 12.6** 环境。
FastDeploy 提供了 GPU 算子预编译版 Wheel 包，可在无需完整源码编译的情况下快速构建。该方式当前仅支持 **SM80/90 架构（A100/H100等）** **CUDA 12.6** 和 **Python 3.10** 环境。
>默认情况下，`build.sh` 会从源码编译；若希望使用预编译包，可使用`FD_USE_PRECOMPILED` 参数；
>若预编译包下载失败或与环境不匹配，系统会自动回退至 `4. wheel 包源码编译` 模式。
@@ -119,7 +122,7 @@ cd FastDeploy
bash build.sh 1 python false [90] 1
# 从指定 commitID 获取对应预编译算子
bash build.sh 1 python false [90] 1 8a9e7b53af4a98583cab65e4b44e3265a93e56d2
bash build.sh 1 python false [90] 1 d693d4be1448d414097882386fdc24c8bec2a63a
```
下载的 whl 包在 `FastDeploy/pre_wheel`目录下。
@@ -128,7 +131,7 @@ bash build.sh 1 python false [90] 1 8a9e7b53af4a98583cab65e4b44e3265a93e56d2
> **说明：**
> - 该模式会优先下载预编译的 GPU 算子 whl 包，减少编译时间；
> - 目前仅支持 **GPU， SM80/90 架构， CUDA 12.6**；
> - 目前仅支持 **GPU， SM80/90 架构， CUDA 12.6， Python3.10**；
> - 若希望自定义架构或修改算子逻辑，请使用 **源码编译方式（第4节）**。
> - 您可以在 FastDeploy CI 构建状态页面查看对应 commit 的预编译 whl 是否已构建成功。