SageMaker Debugger Interactive Reports - Amazon SageMaker

SageMaker Debugger Interactive Reports

Receive training and profiling reports autogenerated by Debugger. The Debugger reports provide insights into your training jobs and suggest recommendations to improve your model performance. The following screenshot shows a collage of the Debugger profiling report. To learn more, see SageMaker Debugger Profiling Report.


You can download a Debugger reports while your training job is running or after the job has finished. During training, Debugger concurrently updates the report reflecting the current rules' evaluation status. You can download a complete Debugger report only after the training job has completed.


To use the new Debugger features, you need to upgrade the SageMaker Python SDK and the SMDebug client library. In your iPython kernel, Jupyter notebook, or JupyterLab environment, run the following code to install the latest versions of the libraries and restart the kernel.

import sys import IPython !{sys.executable} -m pip install -U sagemaker smdebug IPython.Application.instance().kernel.do_shutdown(True)

            An example of a Debugger training job summary report