You can create a PaddlePaddle task.

Prerequisites

• You already install the CCE AI Job Scheduler and CCE Deep Learning Frameworks Operator components successfully. Otherwise, the cloud native AI feature is unavailable.
• If you are a sub-user, you can only use the queue to create a task if you are among the users associated with the queue.
• During the installation of the CCE Deep Learning Frameworks Operator component, the system is installed with the PaddlePaddle deep learning framework.

Restriction Description

• At present, the PaddlePaddle task does not support GPU graphic memory sharing.

Operation Steps

1. Log in to Baidu AI Cloud Official Website, and then enter the management console.
2. Select “Product Service > Cloud Native > CCE”, and click CCE to enter the container engine management console.
3. Click Cluster Management > Cluster List in the navbar on the left side.
4. On the cluster list page, click the target cluster name to enter the cluster management page.
5. On the cluster management page, click Cloud Native AI > Task Management.
6. On the task management page, click Create Task.
7. On the basic information, complete the configuration of the task.

• Task name: Customize the task name, which supports uppercase and lowercase letters, numbers, -, _, /, ., and other special characters, must start with a Chinese character or letter and have a length of 1-65 characters.
• Queue: Select the queue associated with the new task.
• Framework: Select the deep learning framework "PaddlePaddle" corresponding to the task.

8. Complete the configuration by referring to the yaml template:

apiVersion: batch.paddlepaddle.org/v1
kind: PaddleJob
metadata:
  name: resnet
spec:
  cleanPodPolicy: Never
  worker:
    replicas: 2
    template:
      spec:
        schedulerName: volcano
        containers:
          - name: resnet
            image: registry.baidubce.com/paddle-operator/demo-resnet:v1
            command:
            - python
            args:
            - "-m"
            - "paddle.distributed.launch"
            - "train_fleet.py"
            volumeMounts:
            - mountPath: /dev/shm
              name: dshm
            resources:
              requests:
                cpu: 1
                memory: 2Gi
              limits:
                baidu.com/v100_16g_cgpu: "1"
        volumes:
        - name: dshm
          emptyDir:
            medium: Memory

9. Click the “OK” button to complete the task creation.