CleanRoomsML / Client / get_trained_model_inference_job

get_trained_model_inference_job#

CleanRoomsML.Client.get_trained_model_inference_job(**kwargs)#

Returns information about a trained model inference job.

Request Syntax

response = client.get_trained_model_inference_job(
    membershipIdentifier='string',
    trainedModelInferenceJobArn='string'
)

Parameters:

membershipIdentifier (string) –
[REQUIRED]

Provides the membership ID of the membership that contains the trained model inference job that you are interested in.
trainedModelInferenceJobArn (string) –
[REQUIRED]

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

Return type:

dict

Returns:

Response Syntax

{
    'createTime': datetime(2015, 1, 1),
    'updateTime': datetime(2015, 1, 1),
    'trainedModelInferenceJobArn': 'string',
    'configuredModelAlgorithmAssociationArn': 'string',
    'name': 'string',
    'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED'|'INACTIVE',
    'trainedModelArn': 'string',
    'resourceConfig': {
        'instanceType': 'ml.r7i.48xlarge'|'ml.r6i.16xlarge'|'ml.m6i.xlarge'|'ml.m5.4xlarge'|'ml.p2.xlarge'|'ml.m4.16xlarge'|'ml.r7i.16xlarge'|'ml.m7i.xlarge'|'ml.m6i.12xlarge'|'ml.r7i.8xlarge'|'ml.r7i.large'|'ml.m7i.12xlarge'|'ml.m6i.24xlarge'|'ml.m7i.24xlarge'|'ml.r6i.8xlarge'|'ml.r6i.large'|'ml.g5.2xlarge'|'ml.m5.large'|'ml.p3.16xlarge'|'ml.m7i.48xlarge'|'ml.m6i.16xlarge'|'ml.p2.16xlarge'|'ml.g5.4xlarge'|'ml.m7i.16xlarge'|'ml.c4.2xlarge'|'ml.c5.2xlarge'|'ml.c6i.32xlarge'|'ml.c4.4xlarge'|'ml.g5.8xlarge'|'ml.c6i.xlarge'|'ml.c5.4xlarge'|'ml.g4dn.xlarge'|'ml.c7i.xlarge'|'ml.c6i.12xlarge'|'ml.g4dn.12xlarge'|'ml.c7i.12xlarge'|'ml.c6i.24xlarge'|'ml.g4dn.2xlarge'|'ml.c7i.24xlarge'|'ml.c7i.2xlarge'|'ml.c4.8xlarge'|'ml.c6i.2xlarge'|'ml.g4dn.4xlarge'|'ml.c7i.48xlarge'|'ml.c7i.4xlarge'|'ml.c6i.16xlarge'|'ml.c5.9xlarge'|'ml.g4dn.16xlarge'|'ml.c7i.16xlarge'|'ml.c6i.4xlarge'|'ml.c5.xlarge'|'ml.c4.xlarge'|'ml.g4dn.8xlarge'|'ml.c7i.8xlarge'|'ml.c7i.large'|'ml.g5.xlarge'|'ml.c6i.8xlarge'|'ml.c6i.large'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.m7i.2xlarge'|'ml.c5.18xlarge'|'ml.g5.48xlarge'|'ml.m6i.2xlarge'|'ml.g5.16xlarge'|'ml.m7i.4xlarge'|'ml.p3.2xlarge'|'ml.r6i.32xlarge'|'ml.m6i.4xlarge'|'ml.m5.xlarge'|'ml.m4.10xlarge'|'ml.r6i.xlarge'|'ml.m5.12xlarge'|'ml.m4.xlarge'|'ml.r7i.2xlarge'|'ml.r7i.xlarge'|'ml.r6i.12xlarge'|'ml.m5.24xlarge'|'ml.r7i.12xlarge'|'ml.m7i.8xlarge'|'ml.m7i.large'|'ml.r6i.24xlarge'|'ml.r6i.2xlarge'|'ml.m4.2xlarge'|'ml.r7i.24xlarge'|'ml.r7i.4xlarge'|'ml.m6i.8xlarge'|'ml.m6i.large'|'ml.m5.2xlarge'|'ml.p2.8xlarge'|'ml.r6i.4xlarge'|'ml.m6i.32xlarge'|'ml.p3.8xlarge'|'ml.m4.4xlarge',
        'instanceCount': 123
    },
    'outputConfiguration': {
        'accept': 'string',
        'members': [
            {
                'accountId': 'string'
            },
        ]
    },
    'membershipIdentifier': 'string',
    'dataSource': {
        'mlInputChannelArn': 'string'
    },
    'containerExecutionParameters': {
        'maxPayloadInMB': 123
    },
    'statusDetails': {
        'statusCode': 'string',
        'message': 'string'
    },
    'description': 'string',
    'inferenceContainerImageDigest': 'string',
    'environment': {
        'string': 'string'
    },
    'kmsKeyArn': 'string',
    'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
    'metricsStatusDetails': 'string',
    'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
    'logsStatusDetails': 'string',
    'tags': {
        'string': 'string'
    }
}

Response Structure

(dict) –
- createTime (datetime) –
  
  The time at which the trained model inference job was created.
- updateTime (datetime) –
  
  The most recent time at which the trained model inference job was updated.
- trainedModelInferenceJobArn (string) –
  
  The Amazon Resource Name (ARN) of the trained model inference job.
- configuredModelAlgorithmAssociationArn (string) –
  
  The Amazon Resource Name (ARN) of the configured model algorithm association that was used for the trained model inference job.
- name (string) –
  
  The name of the trained model inference job.
- status (string) –
  
  The status of the trained model inference job.
- trainedModelArn (string) –
  
  The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.
- resourceConfig (dict) –
  
  The resource configuration information for the trained model inference job.
  - instanceType (string) –
    
    The type of instance that is used to perform model inference.
  - instanceCount (integer) –
    
    The number of instances to use.
- outputConfiguration (dict) –
  
  The output configuration information for the trained model inference job.
  - accept (string) –
    
    The MIME type used to specify the output data.
  - members (list) –
    
    Defines the members that can receive inference output.
    - (dict) –
      
      Defines who will receive inference results.
      - accountId (string) –
        
        The account ID of the member that can receive inference results.
- membershipIdentifier (string) –
  
  The membership ID of the membership that contains the trained model inference job.
- dataSource (dict) –
  
  The data source that was used for the trained model inference job.
  - mlInputChannelArn (string) –
    
    The Amazon Resource Name (ARN) of the ML input channel for this model inference data source.
- containerExecutionParameters (dict) –
  
  The execution parameters for the model inference job container.
  - maxPayloadInMB (integer) –
    
    The maximum size of the inference container payload, specified in MB.
- 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.
- description (string) –
  
  The description of the trained model inference job.
- inferenceContainerImageDigest (string) –
  
  Information about the training container image.
- environment (dict) –
  
  The environment variables to set in the Docker container.
  - (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 ML inference job and associated data.
- metricsStatus (string) –
  
  The metrics status for the trained model inference job.
- metricsStatusDetails (string) –
  
  Details about the metrics status for the trained model inference job.
- logsStatus (string) –
  
  The logs status for the trained model inference job.
- logsStatusDetails (string) –
  
  Details about the logs status for the trained model inference job.
- 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) –

get_trained_model_inference_job#

Request Syntax

Response Syntax

Response Structure

Exceptions