LookoutEquipment / Client / list_model_versions

list_model_versions#

LookoutEquipment.Client.list_model_versions(**kwargs)#

Generates a list of all model versions for a given model, including the model version, model version ARN, and status. To list a subset of versions, use the MaxModelVersion and MinModelVersion fields.

See also: AWS API Documentation

Request Syntax

response = client.list_model_versions(
    ModelName='string',
    NextToken='string',
    MaxResults=123,
    Status='IN_PROGRESS'|'SUCCESS'|'FAILED'|'IMPORT_IN_PROGRESS'|'CANCELED',
    SourceType='TRAINING'|'RETRAINING'|'IMPORT',
    CreatedAtEndTime=datetime(2015, 1, 1),
    CreatedAtStartTime=datetime(2015, 1, 1),
    MaxModelVersion=123,
    MinModelVersion=123
)
Parameters:

  • ModelName (string) –

    [REQUIRED]

    Then name of the machine learning model for which the model versions are to be listed.

  • NextToken (string) – If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versions. Use this token in the NextToken field in the request to list the next page of results.

  • MaxResults (integer) – Specifies the maximum number of machine learning model versions to list.

  • Status (string) – Filter the results based on the current status of the model version.

  • SourceType (string) – Filter the results based on the way the model version was generated.

  • CreatedAtEndTime (datetime) – Filter results to return all the model versions created before this time.

  • CreatedAtStartTime (datetime) – Filter results to return all the model versions created after this time.

  • MaxModelVersion (integer) – Specifies the highest version of the model to return in the list.

  • MinModelVersion (integer) – Specifies the lowest version of the model to return in the list.

Return type:

dict

Returns:

Response Syntax

{
    'NextToken': 'string',
    'ModelVersionSummaries': [
        {
            'ModelName': 'string',
            'ModelArn': 'string',
            'ModelVersion': 123,
            'ModelVersionArn': 'string',
            'CreatedAt': datetime(2015, 1, 1),
            'Status': 'IN_PROGRESS'|'SUCCESS'|'FAILED'|'IMPORT_IN_PROGRESS'|'CANCELED',
            'SourceType': 'TRAINING'|'RETRAINING'|'IMPORT',
            'ModelQuality': 'QUALITY_THRESHOLD_MET'|'CANNOT_DETERMINE_QUALITY'|'POOR_QUALITY_DETECTED'
        },
    ]
}

Response Structure

  • (dict) –

    • NextToken (string) –

      If the total number of results exceeds the limit that the response can display, the response returns an opaque pagination token indicating where to continue the listing of machine learning model versions. Use this token in the NextToken field in the request to list the next page of results.

    • ModelVersionSummaries (list) –

      Provides information on the specified model version, including the created time, model and dataset ARNs, and status.

      Note

      If you don’t supply the ModelName request parameter, or if you supply the name of a model that doesn’t exist, ListModelVersions returns an empty array in ModelVersionSummaries.

      • (dict) –

        Contains information about the specific model version.

        • ModelName (string) –

          The name of the model that this model version is a version of.

        • ModelArn (string) –

          The Amazon Resource Name (ARN) of the model that this model version is a version of.

        • ModelVersion (integer) –

          The version of the model.

        • ModelVersionArn (string) –

          The Amazon Resource Name (ARN) of the model version.

        • CreatedAt (datetime) –

          The time when this model version was created.

        • Status (string) –

          The current status of the model version.

        • SourceType (string) –

          Indicates how this model version was generated.

        • ModelQuality (string) –

          Provides a quality assessment for a model that uses labels. If Lookout for Equipment determines that the model quality is poor based on training metrics, the value is POOR_QUALITY_DETECTED. Otherwise, the value is QUALITY_THRESHOLD_MET.

          If the model is unlabeled, the model quality can’t be assessed and the value of ModelQuality is CANNOT_DETERMINE_QUALITY. In this situation, you can get a model quality assessment by adding labels to the input dataset and retraining the model.

          For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

Exceptions