[ aws . cleanroomsml ]

get-trained-model

Description

Returns information about a trained model.

See also: AWS API Documentation

Synopsis

  get-trained-model
--trained-model-arn <value>
--membership-identifier <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

--trained-model-arn (string)

The Amazon Resource Name (ARN) of the trained model that you are interested in.

--membership-identifier (string)

The membership ID of the member that created the trained model that you are interested in.

--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

membershipIdentifier -> (string)

The membership ID of the member that created the trained model.

collaborationIdentifier -> (string)

The collaboration ID of the collaboration that contains the trained model.

trainedModelArn -> (string)

The Amazon Resource Name (ARN) of the trained model.

name -> (string)

The name of the trained model.

description -> (string)

The description of the trained model.

status -> (string)

The status of the trained model.

statusDetails -> (structure)

Details about the status of a resource.

statusCode -> (string)

The status code that was returned. The status code is intended for programmatic error handling. Clean Rooms ML will not change the status code for existing error conditions.

message -> (string)

The error message that was returned. The message is intended for human consumption and can change at any time. Use the statusCode for programmatic error handling.

configuredModelAlgorithmAssociationArn -> (string)

The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create the trained model.

resourceConfig -> (structure)

The EC2 resource configuration that was used to create the trained model.

instanceCount -> (integer)

The number of resources that are used to train the model.

instanceType -> (string)

The instance type that is used to train the model.

volumeSizeInGB -> (integer)

The maximum size of the instance that is used to train the model.

stoppingCondition -> (structure)

The stopping condition that was used to terminate model training.

maxRuntimeInSeconds -> (integer)

The maximum amount of time, in seconds, that model training can run before it is terminated.

metricsStatus -> (string)

The status of the model metrics.

metricsStatusDetails -> (string)

Details about the metrics status for the trained model.

logsStatus -> (string)

The logs status for the trained model.

logsStatusDetails -> (string)

Details about the logs status for the trained model.

trainingContainerImageDigest -> (string)

Information about the training image container.

createTime -> (timestamp)

The time at which the trained model was created.

updateTime -> (timestamp)

The most recent time at which the trained model was updated.

hyperparameters -> (map)

The hyperparameters that were used to create the trained model.

key -> (string)

value -> (string)

environment -> (map)

The EC2 environment that was used to create the trained model.

key -> (string)

value -> (string)

kmsKeyArn -> (string)

The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and associated data.

tags -> (map)

The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.

The following basic restrictions apply to tags:

• Maximum number of tags per resource - 50.
• For each resource, each tag key must be unique, and each tag key can have only one value.
• Maximum key length - 128 Unicode characters in UTF-8.
• Maximum value length - 256 Unicode characters in UTF-8.
• If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
• Tag keys and values are case sensitive.
• Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.

key -> (string)

value -> (string)

dataChannels -> (list)

The data channels that were used for the trained model.

(structure)

Information about the model training data channel. A training data channel is a named data source that the training algorithms can consume.

mlInputChannelArn -> (string)

The Amazon Resource Name (ARN) of the ML input channel for this model training data channel.

channelName -> (string)

The name of the training data channel.