AI开发平台MODELARTS-ma-cli ma-job训练作业支持的命令:示例：基于ModelArts预置镜像提交训练作业

时间：2024-08-16 20:39:17

AI开发平台MODELARTS

示例：基于ModelArts预置镜像提交训练作业

指定命令行options参数提交训练作业

ma-cli ma-job submit --code-dir obs://your-bucket/mnist/code/ \
                  --boot-file main.py \
                  --framework-type PyTorch \
                  --working-dir /home/ma-user/modelarts/user-job-dir/code \
                  --framework-version pytorch_1.8.0-cuda_10.2-py_3.7-ubuntu_18.04-x86_64 \
                  --data-url obs://your-bucket/mnist/dataset/MNIST/ \
                  --log-url obs://your-bucket/mnist/logs/ \
                  --train-instance-type modelarts.vm.cpu.8u \
                  --train-instance-count 1  \
                  -q

使用预置镜像的train.yaml样例：

# .ma/train.yaml样例（预置镜像）
# pool_id: pool_xxxx
train-instance-type: modelarts.vm.cpu.8u
train-instance-count: 1
data-url: obs://your-bucket/mnist/dataset/MNIST/
code-dir: obs://your-bucket/mnist/code/
working-dir: /home/ma-user/modelarts/user-job-dir/code
framework-type: PyTorch
framework-version: pytorch_1.8.0-cuda_10.2-py_3.7-ubuntu_18.04-x86_64
boot-file: main.py
log-url: obs://your-bucket/mnist/logs/

##[Optional] Uncomment to set uid when use custom image mode
uid: 1000

##[Optional] Uncomment to upload output file/dir to OBS from training platform
output:
    - name: output_dir
      obs_path: obs://your-bucket/mnist/output1/

##[Optional] Uncomment to download input file/dir from OBS to training platform
input:
    - name: data_url
      obs_path: obs://your-bucket/mnist/dataset/MNIST/

##[Optional] Uncomment pass hyperparameters
parameters:
    - epoch: 10
    - learning_rate: 0.01
    - pretrained:

##[Optional] Uncomment to use dedicated pool
pool_id: pool_xxxx

##[Optional] Uncomment to use volumes attached to the training job
volumes:
  - efs:
      local_path: /xx/yy/zz
      read_only: false
      nfs_server_path: xxx.xxx.xxx.xxx:/

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