modify multy devices docs (#2186)

docs/installation/installation.md

@@ -148,4 +148,4 @@ paddlex --install --platform gitee.com
 ```
 All packages are installed.
 ```
-更多硬件环境的PaddleX安装请参考[PaddleX多硬件使用指南](installation_other_devices.md)
+更多硬件环境的PaddleX安装请参考[PaddleX多硬件使用指南](../other_devices_support/multy_devices_use_guide.md)

docs/installation/installation_en.md

@@ -147,4 +147,4 @@ After installation, you will see the following prompt:
 All packages are installed.
 ```
 
-For PaddleX installation on more hardware environments, please refer to the [PaddleX Multi-hardware Usage Guide](installation_other_devices_en.md)
+For PaddleX installation on more hardware environments, please refer to the [PaddleX Multi-hardware Usage Guide](../other_devices_support/multy_devices_use_guide_en.md)

docs/installation/paddlepaddle_install.md

@@ -34,7 +34,7 @@ python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.
 ```
 > ❗ **注**：更多飞桨 Wheel 版本请参考[飞桨官网](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/zh/install/pip/linux-pip.html)。
 
-**关于其他硬件安装飞桨，请参考**[多硬件安装飞桨](https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/tutorials/INSTALL_OTHER_DEVICES.md)**。**
+**关于其他硬件安装飞桨，请参考**[PaddleX多硬件使用指南](../other_devices_support/multy_devices_use_guide.md)**。**
 
 安装完成后，使用以下命令可以验证 PaddlePaddle 是否安装成功：
 
@@ -47,4 +47,4 @@ python -c "import paddle; print(paddle.__version__)"
 3.0.0-beta1
 ```
 
-> ❗ **注**：如果在安装的过程中，出现任何问题，欢迎在Paddle仓库中[提Issue](https://github.com/PaddlePaddle/Paddle/issues)。
+> ❗ **注**：如果在安装的过程中，出现任何问题，欢迎在Paddle仓库中[提Issue](https://github.com/PaddlePaddle/Paddle/issues)。

docs/installation/paddlepaddle_install_en.md

@@ -32,7 +32,7 @@ python -m pip install paddlepaddle-gpu==3.0.0b1 -i https://www.paddlepaddle.org.
 ```
 Note: For more PaddlePaddle Wheel versions, please refer to the [PaddlePaddle official website](https://www.paddlepaddle.org.cn/install/quick?docurl=/documentation/docs/en/install/pip/linux-pip.html).
 
-**For installing PaddlePaddle on other hardware, please refer to** [Installing PaddlePaddle on Other Devices](https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/tutorials/INSTALL_OTHER_DEVICES.md).
+**For installing PaddlePaddle on other hardware, please refer to** [PaddleX Multi-hardware Usage Guide](../other_devices_support/multy_devices_use_guide_en.md).
 
 After installation, you can verify if PaddlePaddle is successfully installed using the following command:
 

docs/other_devices_support/installation_other_devices.md → docs/other_devices_support/multy_devices_use_guide.md

@@ -64,6 +64,8 @@ PaddleX支持的插件如下，请您根据开发需求，确定所需的一个
 若您需要安装的插件为PaddleXXX（可以有多个），在安装飞桨后，您可以直接执行如下指令快速安装PaddleX的对应插件：
 
 ```
+# 下载 PaddleX 源码
+git clone https://github.com/PaddlePaddle/PaddleX.git
 cd PaddleX
 
 # 安装 PaddleX whl
@@ -100,12 +102,3 @@ All packages are installed.
 ```
 ## 2、使用
 基于昇腾 NPU、寒武纪 MLU、昆仑 XPU、海光DCU 硬件平台的 PaddleX 模型产线开发工具使用方法与 GPU 相同，只需根据所属硬件平台，修改配置设备的参数，详细的使用教程可以查阅[PaddleX产线开发工具本地使用教程](../pipeline_usage/pipeline_develop_guide.md)
-
-需要注意的是，这些硬件平台暂不支持 PaddleX 的边训练边导出静态图的功能，在您训练完之后，体验模块和产线的能力或准备部署时，需要先手动导出静态图。例如，在昇腾 NPU 平台下，导出训练好的 PP-YOLOE_plus-S 模型，可以运行如下命令：
-
-```
-python main.py -c paddlex/configs/object_detection/PP-YOLOE_plus-S.yaml \
-    -o Global.mode=export \
-    -o Global.device=npu \
-    -o Export.weight_path=output/best_model/best_model.pdparams
-```

docs/other_devices_support/installation_other_devices_en.md → docs/other_devices_support/multy_devices_use_guide_en.md

@@ -62,6 +62,8 @@ The plugins supported by PaddleX are as follows. Please determine the name(s) of
 If the plugin(s) you need to install is/are PaddleXXX (can be multiple), after installing PaddlePaddle, you can directly execute the following commands to quickly install the corresponding PaddleX plugin(s):
 
 ```bash
+# obtain PaddleX source code
+git clone https://github.com/PaddlePaddle/PaddleX.git
 cd PaddleX
 
 # Install PaddleX whl
@@ -103,12 +105,3 @@ All packages are installed.
 ## 2. Usage
 
 The usage of PaddleX model pipeline development tool on hardware platforms such as Ascend NPU, Cambricon MLU, Kunlun XPU, and Hygon DCU is identical to that on GPU. You only need to modify the device configuration parameters according to your hardware platform. For detailed usage tutorials, please refer to [PaddleX Pipeline Development Tool Local Usage Guide](../pipeline_usage/pipeline_develop_guide_en.md).
-
-It is important to note that these hardware platforms currently do not support PaddleX’s simultaneous training and static graph export feature. After completing your training, when you are ready to test the capabilities in a module or prepare for deployment on the production line, you will need to manually export the static graph. For example, to export the trained PP-YOLOE_plus-S model on the Ascend NPU platform, you can run the following command:
-
-```
-python main.py -c paddlex/configs/object_detection/PP-YOLOE_plus-S.yaml \
-    -o Global.mode=export \
-    -o Global.device=npu \
-    -o Export.weight_path=output/best_model/best_model.pdparams
-```