Browse checkpoint files - Amazon SageMaker AI
Services or capabilities described in Amazon Web Services documentation might vary by Region. To see the differences applicable to the China Regions, see Getting Started with Amazon Web Services in China (PDF).

Browse checkpoint files

Locate checkpoint files using the SageMaker Python SDK and the Amazon S3 console.

To find the checkpoint files programmatically

To retrieve the S3 bucket URI where the checkpoints are saved, check the following estimator attribute:

estimator.checkpoint_s3_uri

This returns the S3 output path for checkpoints configured while requesting the CreateTrainingJob request. To find the saved checkpoint files using the S3 console, use the following procedure.

To find the checkpoint files from the S3 console

  1. Sign in to the Amazon Web Services Management Console and open the SageMaker AI console at https://console.amazonaws.cn/sagemaker/.

  2. In the left navigation pane, choose Training jobs.

  3. Choose the link to the training job with checkpointing enabled to open Job settings.

  4. On the Job settings page of the training job, locate the Checkpoint configuration section.

    Checkpoint configuration section in the Job settings page of a training job.

  5. Use the link to the S3 bucket to access the checkpoint files.