Analytics¶

class sagemaker.analytics.AnalyticsMetricsBase¶

Bases: object

Base class for tuning job or training job analytics classes. Understands common functionality like persistence and caching.

export_csv(filename)¶

Persists the analytics dataframe to a file.

Parameters:	filename (str) – The name of the file to save to.

dataframe(force_refresh=False)¶

A pandas dataframe with lots of interesting results about this object. Created by calling SageMaker List and Describe APIs and converting them into a convenient tabular summary.

Parameters:	force_refresh (bool) – Set to True to fetch the latest data from SageMaker API.

clear_cache()¶: Clear the object of all local caches of API methods, so that the next time any properties are accessed they will be refreshed from the service.

class sagemaker.analytics.HyperparameterTuningJobAnalytics(hyperparameter_tuning_job_name, sagemaker_session=None)¶

Bases: sagemaker.analytics.AnalyticsMetricsBase

Fetch results about a hyperparameter tuning job and make them accessible for analytics.

Initialize a HyperparameterTuningJobAnalytics instance.

Parameters:	hyperparameter_tuning_job_name (str) – name of the HyperparameterTuningJob to analyze. sagemaker_session (sagemaker.session.Session) – Session object which manages interactions with Amazon SageMaker APIs and any other AWS services needed. If not specified, one is created using the default AWS configuration chain.

name¶: Name of the HyperparameterTuningJob being analyzed

clear_cache()¶: Clear the object of all local caches of API methods.

tuning_ranges¶: A dictionary describing the ranges of all tuned hyperparameters. The keys are the names of the hyperparameter, and the values are the ranges.

description(force_refresh=False)¶

Call DescribeHyperParameterTuningJob for the hyperparameter tuning job.

Parameters:	force_refresh (bool) – Set to True to fetch the latest data from SageMaker API.
Returns:	The Amazon SageMaker response for `DescribeHyperParameterTuningJob`.
Return type:	dict

training_job_summaries(force_refresh=False)¶

A (paginated) list of everything from ListTrainingJobsForTuningJob.

Parameters:	force_refresh (bool) – Set to True to fetch the latest data from SageMaker API.
Returns:	The Amazon SageMaker response for `ListTrainingJobsForTuningJob`.
Return type:	dict

class sagemaker.analytics.TrainingJobAnalytics(training_job_name, metric_names=None, sagemaker_session=None)¶

Bases: sagemaker.analytics.AnalyticsMetricsBase

Fetch training curve data from CloudWatch Metrics for a specific training job.

Initialize a TrainingJobAnalytics instance.

Parameters:

training_job_name (str) – name of the TrainingJob to analyze.
metric_names (list, optional) – string names of all the metrics to collect for this training job. If not specified, then it will use all metric names configured for this job.
sagemaker_session (sagemaker.session.Session) – Session object which manages interactions with Amazon SageMaker APIs and any other AWS services needed. If not specified, one is specified using the default AWS configuration chain.

CLOUDWATCH_NAMESPACE = '/aws/sagemaker/HyperParameterTuningJobs'¶

name¶: Name of the TrainingJob being analyzed

clear_cache()¶: Clear the object of all local caches of API methods, so that the next time any properties are accessed they will be refreshed from the service.