SMDebug Trial

An SMDebug trial is an object which lets you query for tensors for a given training job, specified by the path where SMDebug’s artifacts are saved. Trial is capable of loading new tensors as soon as they become available from the given path, allowing you to do both offline as well as real-time analysis.

Create an SMDebug trial object

Depending on the output path, there are two types of trials you can create: LocalTrial or S3Trial. The SMDebug library provides the following wrapper method that automatically creates the right trial.

class smdebug.trials.create_trial(path, name=None, profiler=False, output_dir='/opt/ml/processing/outputs/', **kwargs)
Parameters

  • path (str) – A local path or an S3 path of the form s3://bucket/prefix. You should see directories such as collections, events and index at this path once the training job starts.

  • name (str) – A name for a trial. It is to help you manage different trials. This is an optional parameter, which defaults to the basename of the path if not passed. Make sure to give it a unique name to prevent duplication.

Returns

An SMDebug trial instance

Return type

Trial

The following examples show how to create an SMDebug trial object.

Example: Creating an S3 trial

from smdebug.trials import create_trial
trial = create_trial(
    path='s3://smdebug-testing-bucket/outputs/resnet',
    name='resnet_training_run'
)

Example: Creating a local trial

from smdebug.trials import create_trial
trial = create_trial(
    path='/home/ubuntu/smdebug_outputs/resnet',
    name='resnet_training_run'
)

Example: Restricting analysis to a range of steps

You can optionally pass range_steps to restrict your analysis to a certain range of steps. Note that if you do so, Trial will not load data from other steps.

  • range_steps=(100, None): This will load all steps after 100

  • range_steps=(None, 100): This will load all steps before 100

  • range_steps=(100, 200) : This will load steps between 100 and 200

  • range_steps=None: This will load all steps

from smdebug.trials import create_trial
trial = create_trial(
    path='s3://smdebug-testing-bucket/outputs/resnet',
    name='resnet_training',
    range_steps=(100, 200)
)