:doc:`SageMaker <../../sagemaker>` / Paginator / ListTrainingJobsForHyperParameterTuningJob

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ListTrainingJobsForHyperParameterTuningJob
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.. py:class:: SageMaker.Paginator.ListTrainingJobsForHyperParameterTuningJob

  ::

    
    paginator = client.get_paginator('list_training_jobs_for_hyper_parameter_tuning_job')

  
  

  .. py:method:: paginate(**kwargs)

    Creates an iterator that will paginate through responses from :py:meth:`SageMaker.Client.list_training_jobs_for_hyper_parameter_tuning_job`.

    See also: `AWS API Documentation <https://docs.aws.amazon.com/goto/WebAPI/sagemaker-2017-07-24/ListTrainingJobsForHyperParameterTuningJob>`_    


    **Request Syntax**
    ::

      response_iterator = paginator.paginate(
          HyperParameterTuningJobName='string',
          StatusEquals='InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped'|'Deleting',
          SortBy='Name'|'CreationTime'|'Status'|'FinalObjectiveMetricValue',
          SortOrder='Ascending'|'Descending',
          PaginationConfig={
              'MaxItems': 123,
              'PageSize': 123,
              'StartingToken': 'string'
          }
      )
      
    :type HyperParameterTuningJobName: string
    :param HyperParameterTuningJobName: **[REQUIRED]** 

      The name of the tuning job whose training jobs you want to list.

      

    
    :type StatusEquals: string
    :param StatusEquals: 

      A filter that returns only training jobs with the specified status.

      

    
    :type SortBy: string
    :param SortBy: 

      The field to sort results by. The default is ``Name``.

       

      If the value of this field is ``FinalObjectiveMetricValue``, any training jobs that did not return an objective metric are not listed.

      

    
    :type SortOrder: string
    :param SortOrder: 

      The sort order for results. The default is ``Ascending``.

      

    
    :type PaginationConfig: dict
    :param PaginationConfig: 

      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.

        

      
    
    
    :rtype: dict
    :returns: 
      
      **Response Syntax**

      
      ::

        {
            'TrainingJobSummaries': [
                {
                    'TrainingJobDefinitionName': 'string',
                    'TrainingJobName': 'string',
                    'TrainingJobArn': 'string',
                    'TuningJobName': 'string',
                    'CreationTime': datetime(2015, 1, 1),
                    'TrainingStartTime': datetime(2015, 1, 1),
                    'TrainingEndTime': datetime(2015, 1, 1),
                    'TrainingJobStatus': 'InProgress'|'Completed'|'Failed'|'Stopping'|'Stopped'|'Deleting',
                    'TunedHyperParameters': {
                        'string': 'string'
                    },
                    'FailureReason': 'string',
                    'FinalHyperParameterTuningJobObjectiveMetric': {
                        'Type': 'Maximize'|'Minimize',
                        'MetricName': 'string',
                        'Value': ...
                    },
                    'ObjectiveStatus': 'Succeeded'|'Pending'|'Failed'
                },
            ],
            
        }
        
      **Response Structure**

      

      - *(dict) --* 
        

        - **TrainingJobSummaries** *(list) --* 

          A list of `TrainingJobSummary <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_TrainingJobSummary.html>`__ objects that describe the training jobs that the ``ListTrainingJobsForHyperParameterTuningJob`` request returned.

          
          

          - *(dict) --* 

            The container for the summary information about a training job.

            
            

            - **TrainingJobDefinitionName** *(string) --* 

              The training job definition name.

              
            

            - **TrainingJobName** *(string) --* 

              The name of the training job.

              
            

            - **TrainingJobArn** *(string) --* 

              The Amazon Resource Name (ARN) of the training job.

              
            

            - **TuningJobName** *(string) --* 

              The HyperParameter tuning job that launched the training job.

              
            

            - **CreationTime** *(datetime) --* 

              The date and time that the training job was created.

              
            

            - **TrainingStartTime** *(datetime) --* 

              The date and time that the training job started.

              
            

            - **TrainingEndTime** *(datetime) --* 

              Specifies the time when the training job ends on training instances. You are billed for the time interval between the value of ``TrainingStartTime`` and this time. For successful jobs and stopped jobs, this is the time after model artifacts are uploaded. For failed jobs, this is the time when SageMaker detects a job failure.

              
            

            - **TrainingJobStatus** *(string) --* 

              The status of the training job.

              
            

            - **TunedHyperParameters** *(dict) --* 

              A list of the hyperparameters for which you specified ranges to search.

              
              

              - *(string) --* 
                

                - *(string) --* 
          
        
            

            - **FailureReason** *(string) --* 

              The reason that the training job failed.

              
            

            - **FinalHyperParameterTuningJobObjectiveMetric** *(dict) --* 

              The `FinalHyperParameterTuningJobObjectiveMetric <https://docs.aws.amazon.com/sagemaker/latest/APIReference/API_FinalHyperParameterTuningJobObjectiveMetric.html>`__ object that specifies the value of the objective metric of the tuning job that launched this training job.

              
              

              - **Type** *(string) --* 

                Select if you want to minimize or maximize the objective metric during hyperparameter tuning.

                
              

              - **MetricName** *(string) --* 

                The name of the objective metric. For SageMaker built-in algorithms, metrics are defined per algorithm. See the `metrics for XGBoost <https://docs.aws.amazon.com/sagemaker/latest/dg/xgboost-tuning.html>`__ as an example. You can also use a custom algorithm for training and define your own metrics. For more information, see `Define metrics and environment variables <https://docs.aws.amazon.com/sagemaker/latest/dg/automatic-model-tuning-define-metrics-variables.html>`__.

                
              

              - **Value** *(float) --* 

                The value of the objective metric.

                
          
            

            - **ObjectiveStatus** *(string) --* 

              The status of the objective metric for the training job:

               

              
              * Succeeded: The final objective metric for the training job was evaluated by the hyperparameter tuning job and used in the hyperparameter tuning process.
              

               

              
              * Pending: The training job is in progress and evaluation of its final objective metric is pending.
              

               

              
              * Failed: The final objective metric for the training job was not evaluated, and was not used in the hyperparameter tuning process. This typically occurs when the training job failed or did not emit an objective metric.
              

              
        
      
    