list_models#

LookoutEquipment.Client.list_models(**kwargs)#

Generates a list of all models in the account, including model name and ARN, dataset, and status.

Request Syntax

response = client.list_models(
    NextToken='string',
    MaxResults=123,
    Status='IN_PROGRESS'|'SUCCESS'|'FAILED'|'IMPORT_IN_PROGRESS',
    ModelNameBeginsWith='string',
    DatasetNameBeginsWith='string'
)

Parameters:

NextToken (string) – An opaque pagination token indicating where to continue the listing of machine learning models.
MaxResults (integer) – Specifies the maximum number of machine learning models to list.
Status (string) – The status of the machine learning model.
ModelNameBeginsWith (string) – The beginning of the name of the machine learning models being listed.
DatasetNameBeginsWith (string) – The beginning of the name of the dataset of the machine learning models to be listed.

Return type:

dict

Returns:

Response Syntax

{
    'NextToken': 'string',
    'ModelSummaries': [
        {
            'ModelName': 'string',
            'ModelArn': 'string',
            'DatasetName': 'string',
            'DatasetArn': 'string',
            'Status': 'IN_PROGRESS'|'SUCCESS'|'FAILED'|'IMPORT_IN_PROGRESS',
            'CreatedAt': datetime(2015, 1, 1),
            'ActiveModelVersion': 123,
            'ActiveModelVersionArn': 'string',
            'LatestScheduledRetrainingStatus': 'IN_PROGRESS'|'SUCCESS'|'FAILED'|'IMPORT_IN_PROGRESS'|'CANCELED',
            'LatestScheduledRetrainingModelVersion': 123,
            'LatestScheduledRetrainingStartTime': datetime(2015, 1, 1),
            'NextScheduledRetrainingStartDate': datetime(2015, 1, 1),
            'RetrainingSchedulerStatus': 'PENDING'|'RUNNING'|'STOPPING'|'STOPPED',
            'ModelDiagnosticsOutputConfiguration': {
                'S3OutputConfiguration': {
                    'Bucket': 'string',
                    'Prefix': 'string'
                },
                'KmsKeyId': 'string'
            },
            'ModelQuality': 'QUALITY_THRESHOLD_MET'|'CANNOT_DETERMINE_QUALITY'|'POOR_QUALITY_DETECTED'
        },
    ]
}

Response Structure

(dict) –
- NextToken (string) –
  
  An opaque pagination token indicating where to continue the listing of machine learning models.
- ModelSummaries (list) –
  
  Provides information on the specified model, including created time, model and dataset ARNs, and status.
  - (dict) –
    
    Provides information about the specified machine learning model, including dataset and model names and ARNs, as well as status.
    - ModelName (string) –
      
      The name of the machine learning model.
    - ModelArn (string) –
      
      The Amazon Resource Name (ARN) of the machine learning model.
    - DatasetName (string) –
      
      The name of the dataset being used for the machine learning model.
    - DatasetArn (string) –
      
      The Amazon Resource Name (ARN) of the dataset used to create the model.
    - Status (string) –
      
      Indicates the status of the machine learning model.
    - CreatedAt (datetime) –
      
      The time at which the specific model was created.
    - ActiveModelVersion (integer) –
      
      The model version that the inference scheduler uses to run an inference execution.
    - ActiveModelVersionArn (string) –
      
      The Amazon Resource Name (ARN) of the model version that is set as active. The active model version is the model version that the inference scheduler uses to run an inference execution.
    - LatestScheduledRetrainingStatus (string) –
      
      Indicates the status of the most recent scheduled retraining run.
    - LatestScheduledRetrainingModelVersion (integer) –
      
      Indicates the most recent model version that was generated by retraining.
    - LatestScheduledRetrainingStartTime (datetime) –
      
      Indicates the start time of the most recent scheduled retraining run.
    - NextScheduledRetrainingStartDate (datetime) –
      
      Indicates the date that the next scheduled retraining run will start on. Lookout for Equipment truncates the time you provide to the nearest UTC day.
    - RetrainingSchedulerStatus (string) –
      
      Indicates the status of the retraining scheduler.
    - ModelDiagnosticsOutputConfiguration (dict) –
      
      Output configuration information for the pointwise model diagnostics for an Amazon Lookout for Equipment model.
      - S3OutputConfiguration (dict) –
        
        The Amazon S3 location for the pointwise model diagnostics.
        
        Bucket (string) –
        
        The name of the Amazon S3 bucket where the pointwise model diagnostics are located. You must be the owner of the Amazon S3 bucket.
        
        Prefix (string) –
        
        The Amazon S3 prefix for the location of the pointwise model diagnostics. The prefix specifies the folder and evaluation result file name. ( bucket).
        
        When you call CreateModel or UpdateModel, specify the path within the bucket that you want Lookout for Equipment to save the model to. During training, Lookout for Equipment creates the model evaluation model as a compressed JSON file with the name model_diagnostics_results.json.gz.
        
        When you call DescribeModel or DescribeModelVersion, prefix contains the file path and filename of the model evaluation file.
      - KmsKeyId (string) –
        
        The Amazon Web Services Key Management Service (KMS) key identifier to encrypt the pointwise model diagnostics files.
    - 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 using labels with your models, see Understanding labeling.
      
      For information about improving the quality of a model, see Best practices with Amazon Lookout for Equipment.

Exceptions

LookoutEquipment.Client.exceptions.ValidationException
LookoutEquipment.Client.exceptions.ThrottlingException
LookoutEquipment.Client.exceptions.AccessDeniedException
LookoutEquipment.Client.exceptions.InternalServerException