@@ -37,17 +37,16 @@ In addition, for some C++ secondary development scenarios, we also provide OPENC
Docker compilation is recommended. We have prepared the Paddle Serving compilation environment for you and configured the above compilation dependencies. For details, please refer to [this document](DOCKER_IMAGES_CN.md).
We provide five environment development images, namely CPU, CUDA10.1 + CUDNN7, CUDA10.2 + CUDNN7, CUDA10.2 + CUDNN8, CUDA11.2 + CUDNN8. We provide a Serving development image to cover the above environment. At the same time, we also support Paddle development mirroring.
We provide 4 environment development images, namely CPU, CUDA10.2 + CUDNN7, CUDA10.2 + CUDNN8, CUDA11.2 + CUDNN8. We provide a Serving development image to cover the above environment. At the same time, we also support Paddle development mirroring.
Serving development mirror is the mirror used to compile and debug prediction services provided by Serving suite in order to support various prediction environments. Paddle development mirror is the mirror used for compilation, development, and training models released by Paddle on the official website. In order to allow Paddle developers to use Serving directly in the same container. For developers who have already used Serving users in the previous version, Serving development image should not be unfamiliar. But for developers who are familiar with the Paddle training framework ecology, they should be more familiar with the existing Paddle development mirrors. In order to adapt to the different habits of all users, we have fully supported both sets of mirrors.
| Environment | Serving Dev Image Tag | OS | Paddle Dev Image Tag | OS |
We first need to pull related images for the environment we need. Under the **Environment** column in the above table, except for the CPU, the rest (Cuda**+Cudnn**) belong to the GPU environment.
@@ -28,10 +28,8 @@ You can get images in two ways:
If you want to customize your Serving based on source code, use the version with the suffix - devel.
**cuda10.1-cudnn7-gcc54 image is not ready, you should run from dockerfile if you need it.**
If you need to develop and compile based on the source code, please use the version with the suffix -devel.
**In the TAG column, 0.8.0 can also be replaced with the corresponding version number, such as 0.5.0/0.4.1, etc., but it should be noted that some development environments only increase with a certain version iteration, so not all environments All have the corresponding version number can be used.**
**In the TAG column, 0.9.0 can also be replaced with the corresponding version number, such as 0.5.0/0.4.1, etc., but it should be noted that some development environments only increase with a certain version iteration, so not all environments All have the corresponding version number can be used.**
**Development Docker Images:**
...
...
@@ -39,12 +37,10 @@ A variety of development tools are installed in the development image, which can
**Tip-1**: This project only supports <mark>**Python3.6/3.7/3.8/3.9**</mark>, all subsequent operations related to Python/Pip need to select the correct Python version.
**Tip-2**: The GPU environments in the following examples are all cuda10.2-cudnn7. If you use Python Pipeline to deploy and need Nvidia TensorRT to optimize prediction performance, please refer to [Supported Mirroring Environment and Instructions](#4.-Supported-Docker-Images-and-Instruction) to choose other versions.
**Tip-2**: The GPU environments in the following examples are all cuda11.2-cudnn8. If you use Python Pipeline to deploy and need Nvidia TensorRT to optimize prediction performance, please refer to [Supported Mirroring Environment and Instructions](#4.-Supported-Docker-Images-and-Instruction) to choose other versions.
## 1. Start the Docker Container
<mark>**Both Serving Dev Image and Paddle Dev Image are supported at the same time. You can choose 1 from the operation 2 in chapters 1.1 and 1.2.**</mark>Deploying the Serving service on the Paddle docker image requires the installation of additional dependency libraries. Therefore, we directly use the Serving development image.
Install the service whl package. There are three types of client, app and server. The server is divided into CPU and GPU. Choose one installation according to the environment.
By default, the domestic Tsinghua mirror source is turned on to speed up the download. If you use a proxy, you can turn it off（`-i https://pypi.tuna.tsinghua.edu.cn/simple`).
...
...
@@ -86,31 +87,35 @@ The paddle-serving-server and paddle-serving-server-gpu installation packages su
The paddle-serving-client and paddle-serving-app installation packages support Linux and Windows, and paddle-serving-client only supports python3.6/3.7/3.8/3.9.
**If you used the CUDA10.2 environment of paddle serving 0.5.X 0.6.X before, you need to pay attention to version 0.8.0, paddle-serving-server-gpu==0.8.0.post102 uses Cudnn7 and TensorRT6, and 0.6.0.post102 uses cudnn8 and TensorRT7. If 0.6.0 cuda10.2 users need to upgrade, please use paddle-serving-server-gpu==0.8.0.post1028**
## 3. Install Paddle related Python libraries
**You only need to install it when you use the `paddle_serving_client.convert` command or the `Python Pipeline framework`. **
**Note**: If your CUDA version is not 10.2 or if you want to use TensorRT(CUDA10.2 included), please do not execute the above commands directly, you need to refer to [Paddle-Inference official document-download and install the Linux prediction library](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python) Select the URL link of the corresponding GPU environment and install it. Assuming that you use Python3.6, please follow the codeblock.
**Note**: If you want to use other versions, please do not execute the above commands directly, you need to refer to [Paddle-Inference official document-download and install the Linux prediction library](https://paddleinference.paddlepaddle.org.cn/master/user_guides/download_lib.html#python) Select the URL link of the corresponding GPU environment and install it. Assuming that you use Python3.6, please follow the codeblock.
for most users, we do not need to read this section. But if you deploy your Paddle Serving on a machine without network, you will encounter a problem that the binary executable tar file cannot be downloaded. Therefore, here we give you all the download links for various environment.
...
...
@@ -29,15 +29,15 @@ for most users, we do not need to read this section. But if you deploy your Padd
