ListCandidatesForAutoMLJob

class SageMaker.Paginator.ListCandidatesForAutoMLJob
paginator = client.get_paginator('list_candidates_for_auto_ml_job')
paginate(**kwargs)

Creates an iterator that will paginate through responses from SageMaker.Client.list_candidates_for_auto_ml_job().

See also: AWS API Documentation

Request Syntax

response_iterator = paginator.paginate(
    AutoMLJobName='string',
    StatusEquals='Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
    CandidateNameEquals='string',
    SortOrder='Ascending'|'Descending',
    SortBy='CreationTime'|'Status'|'FinalObjectiveMetricValue',
    PaginationConfig={
        'MaxItems': 123,
        'PageSize': 123,
        'StartingToken': 'string'
    }
)
Parameters
  • AutoMLJobName (string) --

    [REQUIRED]

    List the candidates created for the job by providing the job's name.

  • StatusEquals (string) -- List the candidates for the job and filter by status.
  • CandidateNameEquals (string) -- List the candidates for the job and filter by candidate name.
  • SortOrder (string) -- The sort order for the results. The default is Ascending .
  • SortBy (string) -- The parameter by which to sort the results. The default is Descending .
  • PaginationConfig (dict) --

    A dictionary that provides parameters to control pagination.

    • MaxItems (integer) --

      The total number of items to return. If the total number of items available is more than the value specified in max-items then a NextToken will be provided in the output that you can use to resume pagination.

    • PageSize (integer) --

      The size of each page.

    • StartingToken (string) --

      A token to specify where to start paginating. This is the NextToken from a previous response.

Return type

dict

Returns

Response Syntax

{
    'Candidates': [
        {
            'CandidateName': 'string',
            'FinalAutoMLJobObjectiveMetric': {
                'Type': 'Maximize'|'Minimize',
                'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro',
                'Value': ...,
                'StandardMetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro'
            },
            'ObjectiveStatus': 'Succeeded'|'Pending'|'Failed',
            'CandidateSteps': [
                {
                    'CandidateStepType': 'AWS::SageMaker::TrainingJob'|'AWS::SageMaker::TransformJob'|'AWS::SageMaker::ProcessingJob',
                    'CandidateStepArn': 'string',
                    'CandidateStepName': 'string'
                },
            ],
            'CandidateStatus': 'Completed'|'InProgress'|'Failed'|'Stopped'|'Stopping',
            'InferenceContainers': [
                {
                    'Image': 'string',
                    'ModelDataUrl': 'string',
                    'Environment': {
                        'string': 'string'
                    }
                },
            ],
            'CreationTime': datetime(2015, 1, 1),
            'EndTime': datetime(2015, 1, 1),
            'LastModifiedTime': datetime(2015, 1, 1),
            'FailureReason': 'string',
            'CandidateProperties': {
                'CandidateArtifactLocations': {
                    'Explainability': 'string',
                    'ModelInsights': 'string'
                },
                'CandidateMetrics': [
                    {
                        'MetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro',
                        'Value': ...,
                        'Set': 'Train'|'Validation'|'Test',
                        'StandardMetricName': 'Accuracy'|'MSE'|'F1'|'F1macro'|'AUC'|'RMSE'|'MAE'|'R2'|'BalancedAccuracy'|'Precision'|'PrecisionMacro'|'Recall'|'RecallMacro'|'LogLoss'|'InferenceLatency'
                    },
                ]
            }
        },
    ],

}

Response Structure

  • (dict) --

    • Candidates (list) --

      Summaries about the AutoMLCandidates .

      • (dict) --

        Information about a candidate produced by an AutoML training job, including its status, steps, and other properties.

        • CandidateName (string) --

          The name of the candidate.

        • FinalAutoMLJobObjectiveMetric (dict) --

          The best candidate result from an AutoML training job.

          • Type (string) --

            The type of metric with the best result.

          • MetricName (string) --

            The name of the metric with the best result. For a description of the possible objective metrics, see AutoMLJobObjective$MetricName.

          • Value (float) --

            The value of the metric with the best result.

          • StandardMetricName (string) --

            The name of the standard metric. For a description of the standard metrics, see Autopilot candidate metrics.

        • ObjectiveStatus (string) --

          The objective's status.

        • CandidateSteps (list) --

          Information about the candidate's steps.

          • (dict) --

            Information about the steps for a candidate and what step it is working on.

            • CandidateStepType (string) --

              Whether the candidate is at the transform, training, or processing step.

            • CandidateStepArn (string) --

              The ARN for the candidate's step.

            • CandidateStepName (string) --

              The name for the candidate's step.

        • CandidateStatus (string) --

          The candidate's status.

        • InferenceContainers (list) --

          Information about the inference container definitions.

          • (dict) --

            A list of container definitions that describe the different containers that make up an AutoML candidate. For more information, see .

            • Image (string) --

              The Amazon Elastic Container Registry (Amazon ECR) path of the container. For more information, see .

            • ModelDataUrl (string) --

              The location of the model artifacts. For more information, see .

            • Environment (dict) --

              The environment variables to set in the container. For more information, see .

              • (string) --
                • (string) --
        • CreationTime (datetime) --

          The creation time.

        • EndTime (datetime) --

          The end time.

        • LastModifiedTime (datetime) --

          The last modified time.

        • FailureReason (string) --

          The failure reason.

        • CandidateProperties (dict) --

          The properties of an AutoML candidate job.

          • CandidateArtifactLocations (dict) --

            The Amazon S3 prefix to the artifacts generated for an AutoML candidate.

            • Explainability (string) --

              The Amazon S3 prefix to the explainability artifacts generated for the AutoML candidate.

            • ModelInsights (string) --

              The Amazon S3 prefix to the model insight artifacts generated for the AutoML candidate.

          • CandidateMetrics (list) --

            Information about the candidate metrics for an AutoML job.

            • (dict) --

              Information about the metric for a candidate produced by an AutoML job.

              • MetricName (string) --

                The name of the metric.

              • Value (float) --

                The value of the metric.

              • Set (string) --

                The dataset split from which the AutoML job produced the metric.

              • StandardMetricName (string) --

                The name of the standard metric.

                Note

                For definitions of the standard metrics, see Autopilot candidate metrics.