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Analyze data using the Debugger Python client library - Amazon SageMaker AI

Analyze data using the Debugger Python client library

Note

On 6/30/27, AWS will discontinue support for Amazon SageMaker Profiler. After 6/30/27, you will no longer be able to access the Profiler console or Profiler resources. For more information, see Profiler availability change.

While your training job is running or after it has completed, you can access the training data collected by Debugger using the Amazon SageMaker Python SDK and the SMDebug client library. The Debugger Python client library provides analysis and visualization tools that enable you to drill down into your training job data.

To install the library and use its analysis tools (in a JupyterLab notebook or an iPython kernel)

! pip install -U smdebug

The following topics walk you through how to use the Debugger Python tools to visualize and analyze the training data collected by Debugger.

Analyze system and framework metrics