describe-solution-version¶

Description¶

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

Synopsis¶

  describe-solution-version
--solution-version-arn <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]

Options¶

--solution-version-arn (string)

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

--cli-input-json | --cli-input-yaml (string) Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.

--generate-cli-skeleton (string) Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.

See ‘aws help’ for descriptions of global parameters.

Output¶

solutionVersion -> (structure)

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 -> (structure)

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 -> (structure)

Describes the properties for hyperparameter optimization (HPO).

hpoObjective -> (structure)

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 -> (structure)

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 -> (structure)

The hyperparameters and their allowable ranges.

integerHyperParameterRanges -> (list)

The integer-valued hyperparameters and their ranges.

(structure)

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.

(structure)

Provides the name and range of a continuous hyperparameter.

name -> (string)

The name of the hyperparameter.

minValue -> (double)

The minimum allowable value for the hyperparameter.

maxValue -> (double)

The maximum allowable value for the hyperparameter.

categoricalHyperParameterRanges -> (list)

The categorical hyperparameters and their ranges.

(structure)

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 -> (map)

Lists the hyperparameter names and ranges.

key -> (string)

value -> (string)

featureTransformationParameters -> (map)

Lists the feature transformation parameters.

key -> (string)

value -> (string)

autoMLConfig -> (structure)

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 -> (structure)

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.

trainingHours -> (double)

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. The FULL option trains the solution version based on the entirety of the input solution’s training data, while the UPDATE option processes only the data that has changed in comparison to the input solution. Choose UPDATE when you want to incrementally update your solution version instead of creating an entirely new one.

Warning

The UPDATE option can only be used when you already have an active solution version created from the input solution using the FULL option and the input solution was trained with the User-Personalization recipe or the HRNN-Coldstart recipe.

tunedHPOParams -> (structure)

If hyperparameter optimization was performed, contains the hyperparameter values of the best performing model.

algorithmHyperParameters -> (map)

A list of the hyperparameter values of the best performing model.

key -> (string)

value -> (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 -> (timestamp)

The date and time (in Unix time) that this version of the solution was created.

lastUpdatedDateTime -> (timestamp)

The date and time (in Unix time) that the solution was last updated.

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