Update docker images (#6955)

Author: tianshuo78520a

ci_scripts/Dockerfile

@@ -1,4 +1,4 @@
-ARG BASEIMAGE=registry.baidubce.com/paddleopen/paddle:build-gpu-cuda10.2-cudnn8-devel-ubuntu18.04-gcc8-py38
+ARG BASEIMAGE=ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddleopen/paddle:build-gpu-cuda10.2-cudnn8-devel-ubuntu18.04-gcc8-py38
 FROM ${BASEIMAGE}
 
 RUN git config --global user.name "PaddleCI" \

docs-build.sh

@@ -50,8 +50,8 @@ fi
 
 VERSIONSTR=${VERSIONSTR:=develop}
 
-SPHINX_DOCKERIMAGE=registry.baidubce.com/paddleopen/fluiddoc-sphinx:20210610-py38
-PADDLEDEV_DOCKERIMAGE=registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda10.1-cudnn7-gcc82
+SPHINX_DOCKERIMAGE=ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddleopen/fluiddoc-sphinx:20210610-py38
+PADDLEDEV_DOCKERIMAGE=ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev-cuda10.1-cudnn7-gcc82
 
 
 if [ "$PADDLE_WHL" = '' ] && [ "$PADDLE_DIR" = '' ] ; then

docs/guides/06_distributed_training/deployment_cn.rst

@@ -52,7 +52,7 @@ paddle 环境安装
 
 .. code-block::
 
-   $ docker run --name paddle -it --net=host -v $PWD:/paddle registry.baidubce.com/paddlepaddle/paddle:2.2.2-gpu-cuda11.2-cudnn8 /bin/bash
+   $ docker run --name paddle -it --net=host -v $PWD:/paddle ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:2.2.2-gpu-cuda11.2-cudnn8 /bin/bash
 
 * 当使用 gpu 时请配置 nvidia docker runtime 或使用 nvidia-docker 启动容器，进入容器后使用 nvidia-smi 命令确认环境正确
 * 使用分布式时需要添加 --net=host 参数让容器使用主机网络以实现跨机建立连接
@@ -230,14 +230,14 @@ paddlejob 任务提交
           spec:
             containers:
               - name: paddle
-                image: registry.baidubce.com/paddle-operator/demo-wide-and-deep:v1
+                image: ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddle-operator/demo-wide-and-deep:v1
       ps:
         replicas: 2
         template:
           spec:
             containers:
               - name: paddle
-                image: registry.baidubce.com/paddle-operator/demo-wide-and-deep:v1
+                image: ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddle-operator/demo-wide-and-deep:v1
 
 说明：
 
@@ -277,7 +277,7 @@ paddlejob 任务提交
           spec:
             containers:
               - name: paddle
-                image: registry.baidubce.com/paddle-operator/demo-resnet:v1
+                image: ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddle-operator/demo-resnet:v1
                 command:
                 - python
                 args:

docs/guides/hardware_support/dcu/install_cn.md

@@ -18,13 +18,13 @@
 
 ```bash
 # 拉取镜像
-docker pull registry.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310
+docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310
 
 # 参考如下命令，启动容器
 docker run -it --name paddle-dcu-dev -v `pwd`:/work \
   -w=/work --shm-size=128G --network=host --privileged  \
   --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
-  registry.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310 /bin/bash
+  ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-dcu:dtk23.10.1-kylinv10-gcc73-py310 /bin/bash
 
 # 检查容器内是否可以正常识别海光 DCU 设备
 rocm-smi

docs/guides/hardware_support/mlu/install_cn.md

@@ -18,14 +18,14 @@
 
 ```bash
 # 拉取镜像
-docker pull registry.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
+docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
 
 # 参考如下命令，启动容器
 docker run -it --name paddle-mlu-dev -v $(pwd):/work \
   -w=/work --shm-size=128G --network=host --privileged  \
   --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
   -v /usr/bin/cnmon:/usr/bin/cnmon \
-  registry.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310 /bin/bash
+  ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310 /bin/bash
 
 # 检查容器内是否可以正常识别寒武纪 MLU 设备
 cnmon

docs/guides/hardware_support/npu/install_cn.md

@@ -28,8 +28,8 @@ lspci | grep d802
 
 ```bash
 # 拉取镜像
-docker pull registry.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-x86_64-gcc84-py39 # X86 架构
-docker pull registry.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-aarch64-gcc84-py39 # ARM 架构
+docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-x86_64-gcc84-py39 # X86 架构
+docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-aarch64-gcc84-py39 # ARM 架构
 
 # 考如下命令启动容器，ASCEND_RT_VISIBLE_DEVICES 可指定可见的 NPU 卡号
 docker run -it --name paddle-npu-dev -v $(pwd):/work \
@@ -38,7 +38,7 @@ docker run -it --name paddle-npu-dev -v $(pwd):/work \
     -v /usr/local/bin/npu-smi:/usr/local/bin/npu-smi \
     -v /usr/local/dcmi:/usr/local/dcmi \
     -e ASCEND_RT_VISIBLE_DEVICES="0,1,2,3,4,5,6,7" \
-    registry.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-$(uname -m)-gcc84-py39 /bin/bash
+    ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80RC1-ubuntu20-$(uname -m)-gcc84-py39 /bin/bash
 
 # 检查容器内是否可以正常识别昇腾 NPU 设备
 npu-smi info

docs/guides/hardware_support/xpu/install_cn.md

@@ -18,13 +18,13 @@
 
 ```bash
 # 拉取镜像
-docker pull registry.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
+docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
 
 # 参考如下命令，启动容器
 docker run -it --name paddle-xpu-dev -v $(pwd):/work \
   -w=/work --shm-size=128G --network=host --privileged  \
   --cap-add=SYS_PTRACE --security-opt seccomp=unconfined \
-  registry.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310 /bin/bash
+  ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310 /bin/bash
 
 # 检查容器内是否可以正常识别昆仑芯 XPU 设备
 xpu_smi

docs/hardware_support/dcu/paddle_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接：registry.baidubce.com/paddlepaddle/paddle-dcu:dtk24.04.1-kylinv10-gcc82
+  * 镜像链接：ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle-dcu:dtk24.04.1-kylinv10-gcc82
 
 ### 环境安装
 

docs/hardware_support/dcu/paddlex_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接：registry.baidubce.com/paddlepaddle/paddle-dcu:dtk24.04.1-kylinv10-gcc82
+  * 镜像链接：ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle-dcu:dtk24.04.1-kylinv10-gcc82
 
 ### 环境安装
 

docs/hardware_support/mlu/paddle_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接： registry.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
+  * 镜像链接： ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
 
 ### 环境安装
 

docs/hardware_support/mlu/paddlex_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接： registry.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
+  * 镜像链接： ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-mlu:ubuntu20-x86_64-gcc84-py310
 
 ### 环境安装
 

docs/hardware_support/npu/paddle_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接：registry.baidubce.com/device/paddle-npu:cann80T13-ubuntu20-x86_64-gcc84-py39
+  * 镜像链接：ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80T13-ubuntu20-x86_64-gcc84-py39
 
   * 镜像中已经默认安装了昇腾算子库 CANN-8.0.T13
 

docs/hardware_support/npu/paddlex_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接：registry.baidubce.com/device/paddle-npu:cann80T13-ubuntu20-x86_64-gcc84-py39
+  * 镜像链接：ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-npu:cann80T13-ubuntu20-x86_64-gcc84-py39
 
   * 镜像中已经默认安装了昇腾算子库 CANN-8.0.T13
 

docs/hardware_support/xpu/paddle_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接： registry.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
+  * 镜像链接： ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
 
 ### 环境安装
 

docs/hardware_support/xpu/paddlex_tutorial_cn.md

@@ -8,7 +8,7 @@
 
 * 考虑到环境差异性，我们推荐使用教程提供的标准镜像完成环境准备：
 
-  * 镜像链接： registry.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
+  * 镜像链接： ccr-2vdh3abv-pub.cnc.bj.baidubce.com/device/paddle-xpu:ubuntu20-x86_64-gcc84-py310
 
 ### 环境安装
 

docs/install/Tables.md

@@ -461,17 +461,17 @@ platform tag: 类似 'linux_x86_64', 'any'
 cd /home/work
 ```
 ```
-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle /work/train.py
+docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle /work/train.py
 ```
 
 上述命令中，`-it` 参数说明容器已交互式运行；`-v $PWD:/work`
 指定将当前路径（Linux 中 PWD 变量会展开为当前路径的绝对路径）挂载到容器内部的:`/work`
-目录: `registry.baidubce.com/paddlepaddle/paddle` 指定需要使用的容器； 最后`/work/train.py`为容器内执行的命令，即运行训练程序。
+目录: `ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle` 指定需要使用的容器； 最后`/work/train.py`为容器内执行的命令，即运行训练程序。
 
 当然，您也可以进入到 Docker 容器中，以交互式的方式执行或调试您的代码：
 
 ```
-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle /bin/bash
+docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle /bin/bash
 ```
 ```
 cd /work
@@ -495,13 +495,13 @@ PaddlePaddle Book 是为用户和开发者制作的一个交互式的 Jupyter No
 我们提供可以直接运行 PaddlePaddle Book 的 Docker 镜像，直接运行：
 
 ```
-docker run -p 8888:8888 registry.baidubce.com/paddlepaddle/book
+docker run -p 8888:8888 ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/book
 ```
 
 国内用户可以使用下面的镜像源来加速访问：
 
 ```
-docker run -p 8888:8888 registry.baidubce.com/paddlepaddle/book
+docker run -p 8888:8888 ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/book
 ```
 
 然后在浏览器中输入以下网址：
@@ -520,7 +520,7 @@ http://localhost:8888/
 请不要忘记提前在物理机上安装 GPU 最新驱动。
 
 ```
-nvidia-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle:latest-gpu /bin/bash
+nvidia-docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-gpu /bin/bash
 ```
 
 **注: 如果没有安装 nvidia-docker，可以尝试以下的方法，将 CUDA 库和 Linux 设备挂载到 Docker 容器内：**
@@ -530,5 +530,5 @@ export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') \
 $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
 export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
 docker run ${CUDA_SO} \
-${DEVICES} -it registry.baidubce.com/paddlepaddle/paddle:latest-gpu
+${DEVICES} -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-gpu
 ```

docs/install/Tables_en.md

@@ -456,16 +456,16 @@ Suppose you have written a PaddlePaddle program in the current directory (such a
 cd /home/work
 ```
 ```
-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle /work/train.py
+docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle /work/train.py
 ```
 
 
-In the above commands, the `-it` parameter indicates that the container has been run interactively; `-v $PWD:/work` specifies that the current path (the absolute path where the PWD variable in Linux will expand to the current path) is mounted to the `:/work` directory inside the container: `registry.baidubce.com/paddlepaddle/paddle` specifies the container to be used; finally `/work/train.py` is the command executed inside the container, ie. the training program.
+In the above commands, the `-it` parameter indicates that the container has been run interactively; `-v $PWD:/work` specifies that the current path (the absolute path where the PWD variable in Linux will expand to the current path) is mounted to the `:/work` directory inside the container: `ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle` specifies the container to be used; finally `/work/train.py` is the command executed inside the container, ie. the training program.
 
 Of course, you can also enter into the Docker container and execute or debug your code interactively:
 
 ```
-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle /bin/bash
+docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle /bin/bash
 ```
 ```
 cd /work
@@ -487,13 +487,13 @@ Use Docker to quickly launch a local Jupyter Notebook containing the PaddlePaddl
 We provide a Docker image that can run the PaddlePaddle Book directly, running directly:
 
 ```
-docker run -p 8888:8888 registry.baidubce.com/paddlepaddle/book
+docker run -p 8888:8888 ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/book
 ```
 
 Domestic users can use the following image source to speed up access:
 
 ```
-docker run -p 8888:8888 registry.baidubce.com/paddlepaddle/book
+docker run -p 8888:8888 ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/book
 ```
 
 Then enter the following URL in your browser:
@@ -511,7 +511,7 @@ http://localhost:8888/
 In order to ensure that the GPU driver works properly in the image, we recommend using [nvidia-docker](https://github.com/NVIDIA/nvidia-docker) to run the image. Don't forget to install the latest GPU drivers on your physical machine in advance.
 
 ```
-Nvidia-docker run -it -v $PWD:/work registry.baidubce.com/paddlepaddle/paddle:latest-gpu /bin/bash
+Nvidia-docker run -it -v $PWD:/work ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-gpu /bin/bash
 ```
 
 **Note: If you don't have nvidia-docker installed, you can try the following to mount the CUDA library and Linux devices into the Docker container:**
@@ -521,5 +521,5 @@ export CUDA_SO="$(\ls /usr/lib64/libcuda* | xargs -I{} echo '-v {}:{}') \
 $(\ls /usr/lib64/libnvidia* | xargs -I{} echo '-v {}:{}')"
 export DEVICES=$(\ls /dev/nvidia* | xargs -I{} echo '--device {}:{}')
 docker run ${CUDA_SO} \
-${DEVICES} -it registry.baidubce.com/paddlepaddle/paddle:latest-gpu
+${DEVICES} -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-gpu
 ```

docs/install/compile/linux-compile-by-make.md

@@ -60,12 +60,12 @@ cd Paddle
 
 * CPU 版的 PaddlePaddle：
     ```
-    docker pull registry.baidubce.com/paddlepaddle/paddle:latest-dev
+    docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev
     ```
 
 * GPU 版的 PaddlePaddle：
     ```
-    docker pull registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2
+    docker pull ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2
     ```
 
 如果您的机器不在中国大陆地区，可以直接从 [DockerHub 中的 paddle 镜像仓库](https://hub.docker.com/r/paddlepaddle/paddle/tags) 拉取镜像：
@@ -90,7 +90,7 @@ cd Paddle
 
     用从百度拉取的镜像创建容器：
     ```
-    docker run --name paddle-test -v $PWD:/paddle --network=host -it registry.baidubce.com/paddlepaddle/paddle:latest-dev /bin/bash
+    docker run --name paddle-test -v $PWD:/paddle --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev /bin/bash
     ```
 
     - `--name paddle-test`：为您创建的 Docker 容器命名为 paddle-test;
@@ -99,7 +99,7 @@ cd Paddle
 
     - `-it`： 与宿主机保持交互状态;
 
-    - `registry.baidubce.com/paddlepaddle/paddle:latest-dev`：使用名为`registry.baidubce.com/paddlepaddle/paddle:latest-dev`的镜像创建 Docker 容器，/bin/bash 进入容器后启动/bin/bash 命令。
+    - `ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev`：使用名为`ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev`的镜像创建 Docker 容器，/bin/bash 进入容器后启动/bin/bash 命令。
 
     若使用的是从 DockerHub 拉取的镜像创建容器，则修改镜像名即可：
     ```
@@ -110,7 +110,7 @@ cd Paddle
 
     用从百度拉取的镜像创建容器
     ```
-    docker run --gpus all --name paddle-test -v $PWD:/paddle --network=host -it registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2 /bin/bash
+    docker run --gpus all --name paddle-test -v $PWD:/paddle --network=host -it ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2 /bin/bash
     ```
 
     - `--gpus all`: 在 Docker 容器中允许使用 gpu;
@@ -121,7 +121,7 @@ cd Paddle
 
     - `-it`： 与宿主机保持交互状态;
 
-    - `registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2`：使用名为`registry.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2`的镜像创建 Docker 容器，/bin/bash 进入容器后启动/bin/bash 命令。
+    - `ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2`：使用名为`ccr-2vdh3abv-pub.cnc.bj.baidubce.com/paddlepaddle/paddle:latest-dev-cuda12.0-cudnn8.9-trt8.6-gcc12.2`的镜像创建 Docker 容器，/bin/bash 进入容器后启动/bin/bash 命令。
 
     若使用的是从 DockerHub 拉取的镜像创建容器，则修改镜像名即可：
     ```