export Module
Exports experiment run history data to Tensorboard logs suitable for viewing in a Tensorboard instance.
Functions
export_to_tensorboard
Export experiment run history to Tensorboard logs ready for Tensorboard visualization.
export_to_tensorboard(run_data, logsdir, logger=None, recursive=True)
Parameters
- recursive
- bool
Specifies whether to recursively retrieve all child runs for specified runs.
Remarks
This function enables you to view experiment run history in a Tensorboard instance. Use it for Azure Machine learning experiments and other machine learning frameworks that don't natively output log files consumable in Tensorboard. For more information about using Tensorboard, see Visualize experiment runs and metrics with Tensorboard.
The following example shows how to use the export_to_tensorboard
function to export
machine learning logs for viewing in TensorBoard. In this example, experiment has completed
and the run history is stored in Tensorboard logs.
# Export Run History to Tensorboard logs
from azureml.tensorboard.export import export_to_tensorboard
import os
logdir = 'exportedTBlogs'
log_path = os.path.join(os.getcwd(), logdir)
try:
os.stat(log_path)
except os.error:
os.mkdir(log_path)
print(logdir)
# export run history for the project
export_to_tensorboard(root_run, logdir)
# or export a particular run
# export_to_tensorboard(run, logdir)
Full sample is available from https://github.com/Azure/MachineLearningNotebooks/blob/master/how-to-use-azureml/track-and-monitor-experiments/tensorboard/export-run-history-to-tensorboard/export-run-history-to-tensorboard.ipynb
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