Personalize / Client / describe_solution_version
describe_solution_version#
- Personalize.Client.describe_solution_version(**kwargs)#
Describes a specific version of a solution. For more information on solutions, see CreateSolution
See also: AWS API Documentation
Request Syntax
response = client.describe_solution_version( solutionVersionArn='string' )
- Parameters:
solutionVersionArn (string) –
[REQUIRED]
The Amazon Resource Name (ARN) of the solution version.
- Return type:
dict
- Returns:
Response Syntax
{ 'solutionVersion': { 'name': 'string', 'solutionVersionArn': 'string', 'solutionArn': 'string', 'performHPO': True|False, 'performAutoML': True|False, 'recipeArn': 'string', 'eventType': 'string', 'datasetGroupArn': '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' }, 'trainingDataConfig': { 'excludedDatasetColumns': { 'string': [ 'string', ] } }, 'autoTrainingConfig': { 'schedulingExpression': 'string' } }, 'trainingHours': 123.0, 'trainingMode': 'FULL'|'UPDATE'|'AUTOTRAIN', 'tunedHPOParams': { 'algorithmHyperParameters': { 'string': 'string' } }, 'status': 'string', 'failureReason': 'string', 'creationDateTime': datetime(2015, 1, 1), 'lastUpdatedDateTime': datetime(2015, 1, 1), 'trainingType': 'AUTOMATIC'|'MANUAL' } }
Response Structure
(dict) –
solutionVersion (dict) –
The solution version.
name (string) –
The name of the solution version.
solutionVersionArn (string) –
The ARN of the solution version.
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 searches for the most optimal recipe according to the solution configuration. When false (the default), Amazon Personalize uses
recipeArn
.recipeArn (string) –
The ARN of the recipe used in the solution.
eventType (string) –
The event type (for example, ‘click’ or ‘like’) that is used for training the model.
datasetGroupArn (string) –
The Amazon Resource Name (ARN) of the dataset group providing the training data.
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
andMinimize
.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
is40
.maxParallelTrainingJobs (string) –
The maximum number of parallel training jobs when you create a solution version. The maximum value for
maxParallelTrainingJobs
is10
.
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 algorithm hyperparameters and their values.
(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.
trainingDataConfig (dict) –
Specifies the training data configuration to use when creating a custom solution version (trained model).
excludedDatasetColumns (dict) –
Specifies the columns to exclude from training. Each key is a dataset type, and each value is a list of columns. Exclude columns to control what data Amazon Personalize uses to generate recommendations.
For example, you might have a column that you want to use only to filter recommendations. You can exclude this column from training and Amazon Personalize considers it only when filtering.
(string) –
(list) –
(string) –
autoTrainingConfig (dict) –
Specifies the automatic training configuration to use.
schedulingExpression (string) –
Specifies how often to automatically train new solution versions. Specify a rate expression in rate(value unit) format. For value, specify a number between 1 and 30. For unit, specify
day
ordays
. For example, to automatically create a new solution version every 5 days, specifyrate(5 days)
. The default is every 7 days.For more information about auto training, see Creating and configuring a solution.
trainingHours (float) –
The time used to train the model. You are billed for the time it takes to train a model. This field is visible only after Amazon Personalize successfully trains a model.
trainingMode (string) –
The scope of training to be performed when creating the solution version. A
FULL
training considers all of the data in your dataset group. AnUPDATE
processes only the data that has changed since the latest training. Only solution versions created with the User-Personalization recipe can useUPDATE
.tunedHPOParams (dict) –
If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.
algorithmHyperParameters (dict) –
A list of the hyperparameter values of the best performing model.
(string) –
(string) –
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
CREATE FAILED
CREATE STOPPING
CREATE STOPPED
failureReason (string) –
If training a solution version fails, the reason for the failure.
creationDateTime (datetime) –
The date and time (in Unix time) that this version of the solution was created.
lastUpdatedDateTime (datetime) –
The date and time (in Unix time) that the solution was last updated.
trainingType (string) –
Whether the solution version was created automatically or manually.
Exceptions
Personalize.Client.exceptions.InvalidInputException
Personalize.Client.exceptions.ResourceNotFoundException