AWS CLI Command Reference

[ aws . personalize ]

describe-solution

Description

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

See also: AWS API Documentation

Synopsis

  describe-solution
--solution-arn <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]
[--cli-binary-format <value>]
[--no-cli-pager]
[--cli-auto-prompt]
[--no-cli-auto-prompt]

Options

--solution-arn (string)

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

--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. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command’s default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

  • json
  • text
  • table
  • yaml
  • yaml-stream

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

  • on
  • off
  • auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

--cli-binary-format (string)

The formatting style to be used for binary blobs. The default format is base64. The base64 format expects binary blobs to be provided as a base64 encoded string. The raw-in-base64-out format preserves compatibility with AWS CLI V1 behavior and binary values must be passed literally. When providing contents from a file that map to a binary blob fileb:// will always be treated as binary and use the file contents directly regardless of the cli-binary-format setting. When using file:// the file contents will need to properly formatted for the configured cli-binary-format.

  • base64
  • raw-in-base64-out

--no-cli-pager (boolean)

Disable cli pager for output.

--cli-auto-prompt (boolean)

Automatically prompt for CLI input parameters.

--no-cli-auto-prompt (boolean)

Disable automatically prompt for CLI input parameters.

Output

solution -> (structure)

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)

Warning

We don’t recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Determining your use case.

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.

performAutoTraining -> (boolean)

Specifies whether the solution automatically creates solution versions. The default is True and the solution automatically creates new solution versions every 7 days.

For more information about auto training, see Creating and configuring a solution .

recipeArn -> (string)

The ARN of the recipe used to create the solution. This is required when performAutoML is false.

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 -> (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 algorithm hyperparameters and their values.

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.

trainingDataConfig -> (structure)

Specifies the training data configuration to use when creating a custom solution version (trained model).

excludedDatasetColumns -> (map)

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.

key -> (string)

value -> (list)

(string)

autoTrainingConfig -> (structure)

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 or days . For example, to automatically create a new solution version every 5 days, specify rate(5 days) . The default is every 7 days.

For more information about auto training, see Creating and configuring a solution .

autoMLResult -> (structure)

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 -> (timestamp)

The creation date and time (in Unix time) of the solution.

lastUpdatedDateTime -> (timestamp)

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

latestSolutionVersion -> (structure)

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

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. An UPDATE processes only the data that has changed since the latest training. Only solution versions created with the User-Personalization recipe can use UPDATE .

trainingType -> (string)

Whether the solution version was created automatically or manually.

creationDateTime -> (timestamp)

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

lastUpdatedDateTime -> (timestamp)

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.

latestSolutionUpdate -> (structure)

Provides a summary of the latest updates to the solution.

solutionUpdateConfig -> (structure)

The configuration details of the solution.

autoTrainingConfig -> (structure)

The automatic training configuration to use when performAutoTraining is true.

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 or days . For example, to automatically create a new solution version every 5 days, specify rate(5 days) . The default is every 7 days.

For more information about auto training, see Creating and configuring a solution .

status -> (string)

The status of the solution update. A solution update can be in one of the following states:

CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

performAutoTraining -> (boolean)

Whether the solution automatically creates solution versions.

creationDateTime -> (timestamp)

The date and time (in Unix format) that the solution update was created.

lastUpdatedDateTime -> (timestamp)

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

failureReason -> (string)

If a solution update fails, the reason behind the failure.
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