CleanRoomsML / Client / get_trained_model

get_trained_model#

CleanRoomsML.Client.get_trained_model(**kwargs)#

Returns information about a trained model.

Request Syntax

response = client.get_trained_model(
    trainedModelArn='string',
    membershipIdentifier='string'
)

Parameters:

trainedModelArn (string) –
[REQUIRED]

The Amazon Resource Name (ARN) of the trained model that you are interested in.
membershipIdentifier (string) –
[REQUIRED]

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

Return type:

dict

Returns:

Response Syntax

{
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'trainedModelArn': 'string',
    'name': 'string',
    'description': 'string',
    'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED',
    'statusDetails': {
        'statusCode': 'string',
        'message': 'string'
    },
    'configuredModelAlgorithmAssociationArn': 'string',
    'resourceConfig': {
        'instanceCount': 123,
        'instanceType': 'ml.m4.xlarge'|'ml.m4.2xlarge'|'ml.m4.4xlarge'|'ml.m4.10xlarge'|'ml.m4.16xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.12xlarge'|'ml.m5.24xlarge'|'ml.c4.xlarge'|'ml.c4.2xlarge'|'ml.c4.4xlarge'|'ml.c4.8xlarge'|'ml.p2.xlarge'|'ml.p2.8xlarge'|'ml.p2.16xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.p4d.24xlarge'|'ml.p4de.24xlarge'|'ml.p5.48xlarge'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.18xlarge'|'ml.c5n.xlarge'|'ml.c5n.2xlarge'|'ml.c5n.4xlarge'|'ml.c5n.9xlarge'|'ml.c5n.18xlarge'|'ml.g5.xlarge'|'ml.g5.2xlarge'|'ml.g5.4xlarge'|'ml.g5.8xlarge'|'ml.g5.16xlarge'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.g5.48xlarge'|'ml.trn1.2xlarge'|'ml.trn1.32xlarge'|'ml.trn1n.32xlarge'|'ml.m6i.large'|'ml.m6i.xlarge'|'ml.m6i.2xlarge'|'ml.m6i.4xlarge'|'ml.m6i.8xlarge'|'ml.m6i.12xlarge'|'ml.m6i.16xlarge'|'ml.m6i.24xlarge'|'ml.m6i.32xlarge'|'ml.c6i.xlarge'|'ml.c6i.2xlarge'|'ml.c6i.8xlarge'|'ml.c6i.4xlarge'|'ml.c6i.12xlarge'|'ml.c6i.16xlarge'|'ml.c6i.24xlarge'|'ml.c6i.32xlarge'|'ml.r5d.large'|'ml.r5d.xlarge'|'ml.r5d.2xlarge'|'ml.r5d.4xlarge'|'ml.r5d.8xlarge'|'ml.r5d.12xlarge'|'ml.r5d.16xlarge'|'ml.r5d.24xlarge'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
        'volumeSizeInGB': 123
    },
    'stoppingCondition': {
        'maxRuntimeInSeconds': 123
    },
    'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
    'metricsStatusDetails': 'string',
    'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
    'logsStatusDetails': 'string',
    'trainingContainerImageDigest': 'string',
    'createTime': datetime(2015, 1, 1),
    'updateTime': datetime(2015, 1, 1),
    'hyperparameters': {
        'string': 'string'
    },
    'environment': {
        'string': 'string'
    },
    'kmsKeyArn': 'string',
    'tags': {
        'string': 'string'
    },
    'dataChannels': [
        {
            'mlInputChannelArn': 'string',
            'channelName': 'string'
        },
    ]
}

Response Structure

(dict) –
- 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 (dict) –
  
  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 (dict) –
  
  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 (dict) –
  
  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 (datetime) –
  
  The time at which the trained model was created.
- updateTime (datetime) –
  
  The most recent time at which the trained model was updated.
- hyperparameters (dict) –
  
  The hyperparameters that were used to create the trained model.
  - (string) –
    - (string) –
- environment (dict) –
  
  The EC2 environment that was used to create the trained model.
  - (string) –
    - (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 (dict) –
  
  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.
  - (string) –
    - (string) –
- dataChannels (list) –
  
  The data channels that were used for the trained model.
  - (dict) –
    
    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.

get_trained_model#

Request Syntax

Response Syntax

Response Structure

Exceptions