Analytics¶
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class
sagemaker.analytics.
AnalyticsMetricsBase
¶ Bases:
object
Base class for tuning job or training job analytics classes. Understands common functionality like persistence and caching.
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export_csv
(filename)¶ Persists the analytics dataframe to a file.
Parameters: filename (str) – The name of the file to save to.
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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.
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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.
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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.
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name
¶ Name of the HyperparameterTuningJob being analyzed
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clear_cache
()¶ Clear the object of all local caches of API methods.
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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.
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class
sagemaker.analytics.
TrainingJobAnalytics
(training_job_name, metric_names=None, sagemaker_session=None, start_time=None, end_time=None, period=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.
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CLOUDWATCH_NAMESPACE
= '/aws/sagemaker/TrainingJobs'¶
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name
¶ Name of the TrainingJob being analyzed
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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.