Personalize / Client / describe_solution

describe_solution#

Personalize.Client.describe_solution(**kwargs)#

Describes a solution. For more information on solutions, see CreateSolution.

Request Syntax

response = client.describe_solution(
    solutionArn='string'
)

Parameters:

solutionArn (string) –

[REQUIRED]

The Amazon Resource Name (ARN) of the solution to describe.

Return type:

dict

Returns:

Response Syntax

{
    'solution': {
        'name': 'string',
        'solutionArn': 'string',
        'performHPO': True|False,
        'performAutoML': True|False,
        'recipeArn': 'string',
        'datasetGroupArn': 'string',
        'eventType': 'string',
        'solutionConfig': {
            'eventValueThreshold': 'string',
            'hpoConfig': {
                'hpoObjective': {
                    'type': 'string',
                    'metricName': 'string',
                    'metricRegex': 'string'
                },
                'hpoResourceConfig': {
                    'maxNumberOfTrainingJobs': 'string',
                    'maxParallelTrainingJobs': 'string'
                },
                'algorithmHyperParameterRanges': {
                    'integerHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123,
                            'maxValue': 123
                        },
                    ],
                    'continuousHyperParameterRanges': [
                        {
                            'name': 'string',
                            'minValue': 123.0,
                            'maxValue': 123.0
                        },
                    ],
                    'categoricalHyperParameterRanges': [
                        {
                            'name': 'string',
                            'values': [
                                'string',
                            ]
                        },
                    ]
                }
            },
            'algorithmHyperParameters': {
                'string': 'string'
            },
            'featureTransformationParameters': {
                'string': 'string'
            },
            'autoMLConfig': {
                'metricName': 'string',
                'recipeList': [
                    'string',
                ]
            },
            'optimizationObjective': {
                'itemAttribute': 'string',
                'objectiveSensitivity': 'LOW'|'MEDIUM'|'HIGH'|'OFF'
            }
        },
        'autoMLResult': {
            'bestRecipeArn': 'string'
        },
        'status': 'string',
        'creationDateTime': datetime(2015, 1, 1),
        'lastUpdatedDateTime': datetime(2015, 1, 1),
        'latestSolutionVersion': {
            'solutionVersionArn': 'string',
            'status': 'string',
            'creationDateTime': datetime(2015, 1, 1),
            'lastUpdatedDateTime': datetime(2015, 1, 1),
            'failureReason': 'string'
        }
    }
}

Response Structure

(dict) –
- solution (dict) –
  
  An object that describes the solution.
  - name (string) –
    
    The name of the solution.
  - solutionArn (string) –
    
    The ARN of the solution.
  - performHPO (boolean) –
    
    Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
  - performAutoML (boolean) –
    
    When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration ( recipeArn must not be specified). When false (the default), Amazon Personalize uses recipeArn for training.
  - recipeArn (string) –
    
    The ARN of the recipe used to create the solution.
  - datasetGroupArn (string) –
    
    The Amazon Resource Name (ARN) of the dataset group that provides the training data.
  - eventType (string) –
    
    The event type (for example, ‘click’ or ‘like’) that is used for training the model. If no eventType is provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.
  - solutionConfig (dict) –
    
    Describes the configuration properties for the solution.
    - eventValueThreshold (string) –
      
      Only events with a value greater than or equal to this threshold are used for training a model.
    - hpoConfig (dict) –
      
      Describes the properties for hyperparameter optimization (HPO).
      - hpoObjective (dict) –
        
        The metric to optimize during HPO.
        
        Note
        
        Amazon Personalize doesn’t support configuring the hpoObjective at this time.
        
        type (string) –
        
        The type of the metric. Valid values are Maximize and Minimize.
        
        metricName (string) –
        
        The name of the metric.
        
        metricRegex (string) –
        
        A regular expression for finding the metric in the training job logs.
      - hpoResourceConfig (dict) –
        
        Describes the resource configuration for HPO.
        
        maxNumberOfTrainingJobs (string) –
        
        The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
        
        maxParallelTrainingJobs (string) –
        
        The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.
      - algorithmHyperParameterRanges (dict) –
        
        The hyperparameters and their allowable ranges.
        
        integerHyperParameterRanges (list) –
        
        The integer-valued hyperparameters and their ranges.
        
        (dict) –
        
        Provides the name and range of an integer-valued hyperparameter.
        
        name (string) –
        
        The name of the hyperparameter.
        
        minValue (integer) –
        
        The minimum allowable value for the hyperparameter.
        
        maxValue (integer) –
        
        The maximum allowable value for the hyperparameter.
        
        continuousHyperParameterRanges (list) –
        
        The continuous hyperparameters and their ranges.
        
        (dict) –
        
        Provides the name and range of a continuous hyperparameter.
        
        name (string) –
        
        The name of the hyperparameter.
        
        minValue (float) –
        
        The minimum allowable value for the hyperparameter.
        
        maxValue (float) –
        
        The maximum allowable value for the hyperparameter.
        
        categoricalHyperParameterRanges (list) –
        
        The categorical hyperparameters and their ranges.
        
        (dict) –
        
        Provides the name and range of a categorical hyperparameter.
        
        name (string) –
        
        The name of the hyperparameter.
        
        values (list) –
        
        A list of the categories for the hyperparameter.
        
        (string) –
    - algorithmHyperParameters (dict) –
      
      Lists the hyperparameter names and ranges.
      - (string) –
        
        (string) –
    - featureTransformationParameters (dict) –
      
      Lists the feature transformation parameters.
      - (string) –
        
        (string) –
    - autoMLConfig (dict) –
      
      The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
      - metricName (string) –
        
        The metric to optimize.
      - recipeList (list) –
        
        The list of candidate recipes.
        
        (string) –
    - optimizationObjective (dict) –
      
      Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
      - itemAttribute (string) –
        
        The numerical metadata column in an Items dataset related to the optimization objective. For example, VIDEO_LENGTH (to maximize streaming minutes), or PRICE (to maximize revenue).
      - objectiveSensitivity (string) –
        
        Specifies how Amazon Personalize balances the importance of your optimization objective versus relevance.
  - autoMLResult (dict) –
    
    When performAutoML is true, specifies the best recipe found.
    - bestRecipeArn (string) –
      
      The Amazon Resource Name (ARN) of the best recipe.
  - status (string) –
    
    The status of the solution.
    
    A solution can be in one of the following states:
    - CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
    - DELETE PENDING > DELETE IN_PROGRESS
  - creationDateTime (datetime) –
    
    The creation date and time (in Unix time) of the solution.
  - lastUpdatedDateTime (datetime) –
    
    The date and time (in Unix time) that the solution was last updated.
  - latestSolutionVersion (dict) –
    
    Describes the latest version of the solution, including the status and the ARN.
    - solutionVersionArn (string) –
      
      The Amazon Resource Name (ARN) of the solution version.
    - status (string) –
      
      The status of the solution version.
      
      A solution version can be in one of the following states:
      - CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED
    - creationDateTime (datetime) –
      
      The date and time (in Unix time) that this version of a solution was created.
    - lastUpdatedDateTime (datetime) –
      
      The date and time (in Unix time) that the solution version was last updated.
    - failureReason (string) –
      
      If a solution version fails, the reason behind the failure.

Exceptions

Personalize.Client.exceptions.InvalidInputException
Personalize.Client.exceptions.ResourceNotFoundException