[ 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)
--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)
solutionArn -> (string)
performHPO -> (boolean)
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)
performAutoML is false.datasetGroupArn -> (string)
eventType -> (string)
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)
hpoConfig -> (structure)
Describes the properties for hyperparameter optimization (HPO).
hpoObjective -> (structure)
The metric to optimize during HPO.
Note
Amazon Personalize doesn’t support configuring thehpoObjective at this time.type -> (string)
Maximize and Minimize .metricName -> (string)
metricRegex -> (string)
hpoResourceConfig -> (structure)
Describes the resource configuration for HPO.
maxNumberOfTrainingJobs -> (string)
maxNumberOfTrainingJobs is 40 .maxParallelTrainingJobs -> (string)
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)
minValue -> (integer)
maxValue -> (integer)
continuousHyperParameterRanges -> (list)
The continuous hyperparameters and their ranges.
(structure)
Provides the name and range of a continuous hyperparameter.
name -> (string)
minValue -> (double)
maxValue -> (double)
categoricalHyperParameterRanges -> (list)
The categorical hyperparameters and their ranges.
(structure)
Provides the name and range of a categorical hyperparameter.
name -> (string)
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)
recipeList -> (list)
The list of candidate recipes.
(string)
eventsConfig -> (structure)
Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.
eventParametersList -> (list)
A list of event parameters, which includes event types and their event value thresholds and weights.
(structure)
Describes the parameters of events, which are used in solution creation.
eventType -> (string)
eventValueThreshold -> (double)
weight -> (double)
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)
objectiveSensitivity -> (string)
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)
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)
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)
lastUpdatedDateTime -> (timestamp)
latestSolutionVersion -> (structure)
Describes the latest version of the solution, including the status and the ARN.
solutionVersionArn -> (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 -or- CREATE FAILED
trainingMode -> (string)
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)
creationDateTime -> (timestamp)
lastUpdatedDateTime -> (timestamp)
failureReason -> (string)
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 .
eventsConfig -> (structure)
Describes the configuration of an event, which includes a list of event parameters. You can specify up to 10 event parameters. Events are used in solution creation.
eventParametersList -> (list)
A list of event parameters, which includes event types and their event value thresholds and weights.
(structure)
Describes the parameters of events, which are used in solution creation.
eventType -> (string)
eventValueThreshold -> (double)
weight -> (double)
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)
creationDateTime -> (timestamp)
lastUpdatedDateTime -> (timestamp)
failureReason -> (string)
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