Plot the System Metrics and Framework Metrics Data - Amazon SageMaker

Plot the System Metrics and Framework Metrics Data

You can use the system and algorithm metrics objects for the following visualization classes to plot timeline graphs and histograms.

Note

To visualize the data with narrowed-down metrics in the following visualization object plot methods, specify select_dimensions and select_events parameters. For example, if you specify select_dimensions=["GPU"], the plot methods filter the metrics that include the "GPU" keyword. If you specify select_events=["total"], the plot methods filter the metrics that include the "total" event tags at the end of the metric names. If you enable these parameters and give the keyword strings, the visualization classes return the charts with filtered metrics.

  • The MetricsHistogram class

    from smdebug.profiler.analysis.notebook_utils.metrics_histogram import MetricsHistogram metrics_histogram = MetricsHistogram(system_metrics_reader) metrics_histogram.plot( starttime=0, endtime=system_metrics_reader.get_timestamp_of_latest_available_file(), select_dimensions=["CPU", "GPU", "I/O"], # optional select_events=["total"] # optional )
  • The StepTimelineChart class

    from smdebug.profiler.analysis.notebook_utils.step_timeline_chart import StepTimelineChart view_step_timeline_chart = StepTimelineChart(framework_metrics_reader)
  • The StepHistogram class

    from smdebug.profiler.analysis.notebook_utils.step_histogram import StepHistogram step_histogram = StepHistogram(framework_metrics_reader) step_histogram.plot( starttime=step_histogram.last_timestamp - 5 * 1000 * 1000, endtime=step_histogram.last_timestamp, show_workers=True )
  • The TimelineCharts class

    from smdebug.profiler.analysis.notebook_utils.timeline_charts import TimelineCharts view_timeline_charts = TimelineCharts( system_metrics_reader, framework_metrics_reader, select_dimensions=["CPU", "GPU", "I/O"], # optional select_events=["total"] # optional ) view_timeline_charts.plot_detailed_profiler_data([700,710])
  • The Heatmap class

    from smdebug.profiler.analysis.notebook_utils.heatmap import Heatmap view_heatmap = Heatmap( system_metrics_reader, framework_metrics_reader, select_dimensions=["CPU", "GPU", "I/O"], # optional select_events=["total"], # optional plot_height=450 )