AWS API Changes

2025/07/01 - AWS Clean Rooms ML - 1 new 16 updated api methods

Changes This release introduces support for incremental training and distributed training for custom models in AWS Clean Rooms ML.

ListTrainedModelVersions (new)

Link ¶

Returns a list of trained model versions for a specified trained model. This operation allows you to view all versions of a trained model, including information about their status and creation details. You can use this to track the evolution of your trained models and select specific versions for inference or further training.

See also: AWS API Documentation

Request Syntax

client.list_trained_model_versions(
    nextToken='string',
    maxResults=123,
    membershipIdentifier='string',
    trainedModelArn='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'
)

type nextToken:

string

param nextToken:

The pagination token from a previous ListTrainedModelVersions request. Use this token to retrieve the next page of results.

type maxResults:

integer

param maxResults:

The maximum number of trained model versions to return in a single page. The default value is 10, and the maximum value is 100.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership identifier for the collaboration that contains the trained model.

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model for which to list versions.

type status:

string

param status:

Filter the results to only include trained model versions with the specified status. Valid values include CREATE_PENDING, CREATE_IN_PROGRESS, ACTIVE, CREATE_FAILED, and others.

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'trainedModels': [
        {
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1),
            'trainedModelArn': 'string',
            'versionIdentifier': 'string',
            'incrementalTrainingDataChannels': [
                {
                    'channelName': 'string',
                    'versionIdentifier': 'string',
                    'modelName': 'string'
                },
            ],
            'name': 'string',
            'description': 'string',
            'membershipIdentifier': 'string',
            'collaborationIdentifier': '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',
            'configuredModelAlgorithmAssociationArn': 'string'
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The pagination token to use in a subsequent ListTrainedModelVersions request to retrieve the next page of results. This value is null when there are no more results to return.
- trainedModels (list) --
  
  A list of trained model versions that match the specified criteria. Each entry contains summary information about a trained model version, including its version identifier, status, and creation details.
  - (dict) --
    
    Summary information about the trained model.
    - createTime (datetime) --
      
      The time at which the trained model was created.
    - updateTime (datetime) --
      
      The most recent time at which the trained model was updated.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model.
    - versionIdentifier (string) --
      
      The version identifier of this trained model version.
    - incrementalTrainingDataChannels (list) --
      
      Information about the incremental training data channels used to create this version of the trained model.
      - (dict) --
        
        Contains information about an incremental training data channel that was used to create a trained model. This structure provides details about the base model and channel configuration used during incremental training.
        
        channelName (string) --
        
        The name of the incremental training data channel that was used.
        
        versionIdentifier (string) --
        
        The version identifier of the trained model that was used for incremental training.
        
        modelName (string) --
        
        The name of the base trained model that was used for incremental training.
    - name (string) --
      
      The name of the trained model.
    - description (string) --
      
      The description of the trained model.
    - 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.
    - status (string) --
      
      The status of the trained model.
    - configuredModelAlgorithmAssociationArn (string) --
      
      The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

CancelTrainedModel (updated)

Link ¶
Changes (request)

{'versionIdentifier': 'string'}

Submits a request to cancel the trained model job.

See also: AWS API Documentation

Request Syntax

client.cancel_trained_model(
    membershipIdentifier='string',
    trainedModelArn='string',
    versionIdentifier='string'
)

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the trained model job that you want to cancel.

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model job that you want to cancel.

type versionIdentifier:

string

param versionIdentifier:

The version identifier of the trained model to cancel. This parameter allows you to specify which version of the trained model you want to cancel when multiple versions exist.

If versionIdentifier is not specified, the base model will be cancelled.

returns:

None

CreateConfiguredModelAlgorithmAssociation (updated)

Link ¶
Changes (request)

{'privacyConfiguration': {'policies': {'trainedModels': {'maxArtifactSize': {'unit': 'GB',
                                                                             'value': 'double'}}}}}

Associates a configured model algorithm to a collaboration for use by any member of the collaboration.

See also: AWS API Documentation

Request Syntax

client.create_configured_model_algorithm_association(
    membershipIdentifier='string',
    configuredModelAlgorithmArn='string',
    name='string',
    description='string',
    privacyConfiguration={
        'policies': {
            'trainedModels': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'containerMetrics': {
                    'noiseLevel': 'HIGH'|'MEDIUM'|'LOW'|'NONE'
                },
                'maxArtifactSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            },
            'trainedModelExports': {
                'maxSize': {
                    'unit': 'GB',
                    'value': 123.0
                },
                'filesToExport': [
                    'MODEL'|'OUTPUT',
                ]
            },
            'trainedModelInferenceJobs': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'maxOutputSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            }
        }
    },
    tags={
        'string': 'string'
    }
)

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the member who is associating this configured model algorithm.

type configuredModelAlgorithmArn:

string

param configuredModelAlgorithmArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the configured model algorithm that you want to associate.

type name:

string

param name:

[REQUIRED]

The name of the configured model algorithm association.

type description:

string

param description:

The description of the configured model algorithm association.

type privacyConfiguration:

dict

param privacyConfiguration:

Specifies the privacy configuration information for the configured model algorithm association. This information includes the maximum data size that can be exported.

policies (dict) -- [REQUIRED]

The privacy configuration policies for a configured model algorithm association.
- trainedModels (dict) --
  
  Specifies who will receive the trained models.
  - containerLogs (list) --
    
    The container for the logs of the trained model.
    - (dict) --
      
      Provides the information necessary for a user to access the logs.
      - allowedAccountIds (list) -- [REQUIRED]
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
      - filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
  - containerMetrics (dict) --
    
    The container for the metrics of the trained model.
    - noiseLevel (string) -- [REQUIRED]
      
      The noise level for the generated metrics.
  - maxArtifactSize (dict) --
    
    The maximum size limit for trained model artifacts as defined in the configuration policy. This setting helps enforce consistent size limits across trained models in the collaboration.
    - unit (string) -- [REQUIRED]
      
      The unit of measurement for the maximum artifact size. Valid values include common storage units such as bytes, kilobytes, megabytes, gigabytes, and terabytes.
    - value (float) -- [REQUIRED]
      
      The numerical value for the maximum artifact size limit. This value is interpreted according to the specified unit.
- trainedModelExports (dict) --
  
  Specifies who will receive the trained model export.
  - maxSize (dict) -- [REQUIRED]
    
    The maximum size of the data that can be exported.
    - unit (string) -- [REQUIRED]
      
      The unit of measurement for the data size.
    - value (float) -- [REQUIRED]
      
      The maximum size of the dataset to export.
  - filesToExport (list) -- [REQUIRED]
    
    The files that are exported during the trained model export job.
    - (string) --
- trainedModelInferenceJobs (dict) --
  
  Specifies who will receive the trained model inference jobs.
  - containerLogs (list) --
    
    The logs container for the trained model inference job.
    - (dict) --
      
      Provides the information necessary for a user to access the logs.
      - allowedAccountIds (list) -- [REQUIRED]
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
      - filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
  - maxOutputSize (dict) --
    
    The maximum allowed size of the output of the trained model inference job.
    - unit (string) -- [REQUIRED]
      
      The measurement unit to use.
    - value (float) -- [REQUIRED]
      
      The maximum output size value.

type tags:

dict

param tags:

The optional metadata that you apply 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) --

rtype:

dict

returns:

Response Syntax

{
    'configuredModelAlgorithmAssociationArn': 'string'
}

Response Structure

(dict) --
- configuredModelAlgorithmAssociationArn (string) --
  
  The Amazon Resource Name (ARN) of the configured model algorithm association.

CreateTrainedModel (updated)

Link ¶
Changes (request, response)
Request

{'dataChannels': {'s3DataDistributionType': 'FullyReplicated | ShardedByS3Key'},
 'incrementalTrainingDataChannels': [{'channelName': 'string',
                                      'trainedModelArn': 'string',
                                      'versionIdentifier': 'string'}],
 'trainingInputMode': 'File | FastFile | Pipe'}

Response

{'versionIdentifier': 'string'}

Creates a trained model from an associated configured model algorithm using data from any member of the collaboration.

See also: AWS API Documentation

Request Syntax

client.create_trained_model(
    membershipIdentifier='string',
    name='string',
    configuredModelAlgorithmAssociationArn='string',
    hyperparameters={
        'string': 'string'
    },
    environment={
        'string': '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
    },
    incrementalTrainingDataChannels=[
        {
            'trainedModelArn': 'string',
            'versionIdentifier': 'string',
            'channelName': 'string'
        },
    ],
    dataChannels=[
        {
            'mlInputChannelArn': 'string',
            'channelName': 'string',
            's3DataDistributionType': 'FullyReplicated'|'ShardedByS3Key'
        },
    ],
    trainingInputMode='File'|'FastFile'|'Pipe',
    description='string',
    kmsKeyArn='string',
    tags={
        'string': 'string'
    }
)

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the member that is creating the trained model.

type name:

string

param name:

[REQUIRED]

The name of the trained model.

type configuredModelAlgorithmAssociationArn:

string

param configuredModelAlgorithmAssociationArn:

[REQUIRED]

The associated configured model algorithm used to train this model.

type hyperparameters:

dict

param hyperparameters:

Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.

(string) --
- (string) --

type environment:

dict

param environment:

The environment variables to set in the Docker container.

(string) --
- (string) --

type resourceConfig:

dict

param resourceConfig:

[REQUIRED]

Information about the EC2 resources that are used to train this model.

instanceCount (integer) --

The number of resources that are used to train the model.
instanceType (string) -- [REQUIRED]

The instance type that is used to train the model.
volumeSizeInGB (integer) -- [REQUIRED]

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

type stoppingCondition:

dict

param stoppingCondition:

The criteria that is used to stop model training.

maxRuntimeInSeconds (integer) --

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

type incrementalTrainingDataChannels:

list

param incrementalTrainingDataChannels:

Specifies the incremental training data channels for the trained model.

Incremental training allows you to create a new trained model with updates without retraining from scratch. You can specify up to one incremental training data channel that references a previously trained model and its version.

Limit: Maximum of 20 channels total (including both incrementalTrainingDataChannels and dataChannels).

(dict) --

Defines an incremental training data channel that references a previously trained model. Incremental training allows you to update an existing trained model with new data, building upon the knowledge from a base model rather than training from scratch. This can significantly reduce training time and computational costs while improving model performance with additional data.
- trainedModelArn (string) -- [REQUIRED]
  
  The Amazon Resource Name (ARN) of the base trained model to use for incremental training. This model serves as the starting point for the incremental training process.
- versionIdentifier (string) --
  
  The version identifier of the base trained model to use for incremental training. If not specified, the latest version of the trained model is used.
- channelName (string) -- [REQUIRED]
  
  The name of the incremental training data channel. This name is used to identify the channel during the training process and must be unique within the training job.

type dataChannels:

list

param dataChannels:

[REQUIRED]

Defines the data channels that are used as input for the trained model request.

Limit: Maximum of 20 channels total (including both dataChannels and incrementalTrainingDataChannels).

(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) -- [REQUIRED]
  
  The Amazon Resource Name (ARN) of the ML input channel for this model training data channel.
- channelName (string) -- [REQUIRED]
  
  The name of the training data channel.
- s3DataDistributionType (string) --
  
  Specifies how the training data stored in Amazon S3 should be distributed to training instances. This parameter controls the data distribution strategy for the training job:
  - FullyReplicated - The entire dataset is replicated on each training instance. This is suitable for smaller datasets and algorithms that require access to the complete dataset.
  - ShardedByS3Key - The dataset is distributed across training instances based on Amazon S3 key names. This is suitable for larger datasets and distributed training scenarios where each instance processes a subset of the data.

type trainingInputMode:

string

param trainingInputMode:

The input mode for accessing the training data. This parameter determines how the training data is made available to the training algorithm. Valid values are:

File - The training data is downloaded to the training instance and made available as files.
FastFile - The training data is streamed directly from Amazon S3 to the training algorithm, providing faster access for large datasets.
Pipe - The training data is streamed to the training algorithm using named pipes, which can improve performance for certain algorithms.

type description:

string

param description:

The description of the trained model.

type kmsKeyArn:

string

param kmsKeyArn:

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 the associated data.

type tags:

dict

param tags:

The optional metadata that you apply 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) --

rtype:

dict

returns:

Response Syntax

{
    'trainedModelArn': 'string',
    'versionIdentifier': 'string'
}

Response Structure

(dict) --
- trainedModelArn (string) --
  
  The Amazon Resource Name (ARN) of the trained model.
- versionIdentifier (string) --
  
  The unique version identifier assigned to the newly created trained model. This identifier can be used to reference this specific version of the trained model in subsequent operations such as inference jobs or incremental training.
  
  The initial version identifier for the base version of the trained model is "NULL".

DeleteTrainedModelOutput (updated)

Link ¶
Changes (request)

{'versionIdentifier': 'string'}

Deletes the model artifacts stored by the service.

See also: AWS API Documentation

Request Syntax

client.delete_trained_model_output(
    trainedModelArn='string',
    membershipIdentifier='string',
    versionIdentifier='string'
)

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model whose output you want to delete.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the member that is deleting the trained model output.

type versionIdentifier:

string

param versionIdentifier:

The version identifier of the trained model to delete. If not specified, the operation will delete the base version of the trained model. When specified, only the particular version will be deleted.

returns:

None

GetCollaborationConfiguredModelAlgorithmAssociation (updated)

Link ¶
Changes (response)

{'privacyConfiguration': {'policies': {'trainedModels': {'maxArtifactSize': {'unit': 'GB',
                                                                             'value': 'double'}}}}}

Returns information about the configured model algorithm association in a collaboration.

See also: AWS API Documentation

Request Syntax

client.get_collaboration_configured_model_algorithm_association(
    configuredModelAlgorithmAssociationArn='string',
    collaborationIdentifier='string'
)

type configuredModelAlgorithmAssociationArn:

string

param configuredModelAlgorithmAssociationArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

type collaborationIdentifier:

string

param collaborationIdentifier:

[REQUIRED]

The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.

rtype:

dict

returns:

Response Syntax

{
    'createTime': datetime(2015, 1, 1),
    'updateTime': datetime(2015, 1, 1),
    'configuredModelAlgorithmAssociationArn': 'string',
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'configuredModelAlgorithmArn': 'string',
    'name': 'string',
    'description': 'string',
    'creatorAccountId': 'string',
    'privacyConfiguration': {
        'policies': {
            'trainedModels': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'containerMetrics': {
                    'noiseLevel': 'HIGH'|'MEDIUM'|'LOW'|'NONE'
                },
                'maxArtifactSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            },
            'trainedModelExports': {
                'maxSize': {
                    'unit': 'GB',
                    'value': 123.0
                },
                'filesToExport': [
                    'MODEL'|'OUTPUT',
                ]
            },
            'trainedModelInferenceJobs': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'maxOutputSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            }
        }
    }
}

Response Structure

(dict) --
- createTime (datetime) --
  
  The time at which the configured model algorithm association was created.
- updateTime (datetime) --
  
  The most recent time at which the configured model algorithm association was updated.
- configuredModelAlgorithmAssociationArn (string) --
  
  The Amazon Resource Name (ARN) of the configured model algorithm association.
- membershipIdentifier (string) --
  
  The membership ID of the member that created the configured model algorithm association.
- collaborationIdentifier (string) --
  
  The collaboration ID of the collaboration that contains the configured model algorithm association.
- configuredModelAlgorithmArn (string) --
  
  The Amazon Resource Name (ARN) of the configured model algorithm association.
- name (string) --
  
  The name of the configured model algorithm association.
- description (string) --
  
  The description of the configured model algorithm association.
- creatorAccountId (string) --
  
  The account ID of the member that created the configured model algorithm association.
- privacyConfiguration (dict) --
  
  Information about the privacy configuration for a configured model algorithm association.
  - policies (dict) --
    
    The privacy configuration policies for a configured model algorithm association.
    - trainedModels (dict) --
      
      Specifies who will receive the trained models.
      - containerLogs (list) --
        
        The container for the logs of the trained model.
        
        (dict) --
        
        Provides the information necessary for a user to access the logs.
        
        allowedAccountIds (list) --
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
        
        filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
      - containerMetrics (dict) --
        
        The container for the metrics of the trained model.
        
        noiseLevel (string) --
        
        The noise level for the generated metrics.
      - maxArtifactSize (dict) --
        
        The maximum size limit for trained model artifacts as defined in the configuration policy. This setting helps enforce consistent size limits across trained models in the collaboration.
        
        unit (string) --
        
        The unit of measurement for the maximum artifact size. Valid values include common storage units such as bytes, kilobytes, megabytes, gigabytes, and terabytes.
        
        value (float) --
        
        The numerical value for the maximum artifact size limit. This value is interpreted according to the specified unit.
    - trainedModelExports (dict) --
      
      Specifies who will receive the trained model export.
      - maxSize (dict) --
        
        The maximum size of the data that can be exported.
        
        unit (string) --
        
        The unit of measurement for the data size.
        
        value (float) --
        
        The maximum size of the dataset to export.
      - filesToExport (list) --
        
        The files that are exported during the trained model export job.
        
        (string) --
    - trainedModelInferenceJobs (dict) --
      
      Specifies who will receive the trained model inference jobs.
      - containerLogs (list) --
        
        The logs container for the trained model inference job.
        
        (dict) --
        
        Provides the information necessary for a user to access the logs.
        
        allowedAccountIds (list) --
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
        
        filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
      - maxOutputSize (dict) --
        
        The maximum allowed size of the output of the trained model inference job.
        
        unit (string) --
        
        The measurement unit to use.
        
        value (float) --
        
        The maximum output size value.

GetCollaborationTrainedModel (updated)

Link ¶
Changes (request, response)
Request

{'versionIdentifier': 'string'}

Response

{'incrementalTrainingDataChannels': [{'channelName': 'string',
                                      'modelName': 'string',
                                      'versionIdentifier': 'string'}],
 'trainingInputMode': 'File | FastFile | Pipe',
 'versionIdentifier': 'string'}

Returns information about a trained model in a collaboration.

See also: AWS API Documentation

Request Syntax

client.get_collaboration_trained_model(
    trainedModelArn='string',
    collaborationIdentifier='string',
    versionIdentifier='string'
)

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model that you want to return information about.

type collaborationIdentifier:

string

param collaborationIdentifier:

[REQUIRED]

The collaboration ID that contains the trained model that you want to return information about.

type versionIdentifier:

string

param versionIdentifier:

The version identifier of the trained model to retrieve. If not specified, the operation returns information about the latest version of the trained model.

rtype:

dict

returns:

Response Syntax

{
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'trainedModelArn': 'string',
    'versionIdentifier': 'string',
    'incrementalTrainingDataChannels': [
        {
            'channelName': 'string',
            'versionIdentifier': 'string',
            'modelName': '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
    },
    'trainingInputMode': 'File'|'FastFile'|'Pipe',
    '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),
    'creatorAccountId': '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.
- versionIdentifier (string) --
  
  The version identifier of the trained model. This unique identifier distinguishes this version from other versions of the same trained model.
- incrementalTrainingDataChannels (list) --
  
  Information about the incremental training data channels used to create this version of the trained model. This includes details about the base model that was used for incremental training and the channel configuration.
  - (dict) --
    
    Contains information about an incremental training data channel that was used to create a trained model. This structure provides details about the base model and channel configuration used during incremental training.
    - channelName (string) --
      
      The name of the incremental training data channel that was used.
    - versionIdentifier (string) --
      
      The version identifier of the trained model that was used for incremental training.
    - modelName (string) --
      
      The name of the base trained model that was used for incremental training.
- 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 this trained model.
- resourceConfig (dict) --
  
  The EC2 resource configuration that was used to train this 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.
- trainingInputMode (string) --
  
  The input mode that was used for accessing the training data when this trained model was created. This indicates how the training data was made available to the training algorithm.
- stoppingCondition (dict) --
  
  The stopping condition that determined when model training ended.
  - 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 status information for the model metrics.
- logsStatus (string) --
  
  Status information for the logs.
- logsStatusDetails (string) --
  
  Details about the status information for the logs.
- trainingContainerImageDigest (string) --
  
  Information about the training container image.
- createTime (datetime) --
  
  The time at which the trained model was created.
- updateTime (datetime) --
  
  The most recent time at which the trained model was updated.
- creatorAccountId (string) --
  
  The account ID of the member that created the trained model.

GetConfiguredModelAlgorithmAssociation (updated)

Link ¶
Changes (response)

{'privacyConfiguration': {'policies': {'trainedModels': {'maxArtifactSize': {'unit': 'GB',
                                                                             'value': 'double'}}}}}

Returns information about a configured model algorithm association.

See also: AWS API Documentation

Request Syntax

client.get_configured_model_algorithm_association(
    configuredModelAlgorithmAssociationArn='string',
    membershipIdentifier='string'
)

type configuredModelAlgorithmAssociationArn:

string

param configuredModelAlgorithmAssociationArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the member that created the configured model algorithm association.

rtype:

dict

returns:

Response Syntax

{
    'createTime': datetime(2015, 1, 1),
    'updateTime': datetime(2015, 1, 1),
    'configuredModelAlgorithmAssociationArn': 'string',
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'configuredModelAlgorithmArn': 'string',
    'name': 'string',
    'privacyConfiguration': {
        'policies': {
            'trainedModels': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'containerMetrics': {
                    'noiseLevel': 'HIGH'|'MEDIUM'|'LOW'|'NONE'
                },
                'maxArtifactSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            },
            'trainedModelExports': {
                'maxSize': {
                    'unit': 'GB',
                    'value': 123.0
                },
                'filesToExport': [
                    'MODEL'|'OUTPUT',
                ]
            },
            'trainedModelInferenceJobs': {
                'containerLogs': [
                    {
                        'allowedAccountIds': [
                            'string',
                        ],
                        'filterPattern': 'string'
                    },
                ],
                'maxOutputSize': {
                    'unit': 'GB',
                    'value': 123.0
                }
            }
        }
    },
    'description': 'string',
    'tags': {
        'string': 'string'
    }
}

Response Structure

(dict) --
- createTime (datetime) --
  
  The time at which the configured model algorithm association was created.
- updateTime (datetime) --
  
  The most recent time at which the configured model algorithm association was updated.
- configuredModelAlgorithmAssociationArn (string) --
  
  The Amazon Resource Name (ARN) of the configured model algorithm association.
- membershipIdentifier (string) --
  
  The membership ID of the member that created the configured model algorithm association.
- collaborationIdentifier (string) --
  
  The collaboration ID of the collaboration that contains the configured model algorithm association.
- configuredModelAlgorithmArn (string) --
  
  The Amazon Resource Name (ARN) of the configured model algorithm that was associated to the collaboration.
- name (string) --
  
  The name of the configured model algorithm association.
- privacyConfiguration (dict) --
  
  The privacy configuration information for the configured model algorithm association.
  - policies (dict) --
    
    The privacy configuration policies for a configured model algorithm association.
    - trainedModels (dict) --
      
      Specifies who will receive the trained models.
      - containerLogs (list) --
        
        The container for the logs of the trained model.
        
        (dict) --
        
        Provides the information necessary for a user to access the logs.
        
        allowedAccountIds (list) --
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
        
        filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
      - containerMetrics (dict) --
        
        The container for the metrics of the trained model.
        
        noiseLevel (string) --
        
        The noise level for the generated metrics.
      - maxArtifactSize (dict) --
        
        The maximum size limit for trained model artifacts as defined in the configuration policy. This setting helps enforce consistent size limits across trained models in the collaboration.
        
        unit (string) --
        
        The unit of measurement for the maximum artifact size. Valid values include common storage units such as bytes, kilobytes, megabytes, gigabytes, and terabytes.
        
        value (float) --
        
        The numerical value for the maximum artifact size limit. This value is interpreted according to the specified unit.
    - trainedModelExports (dict) --
      
      Specifies who will receive the trained model export.
      - maxSize (dict) --
        
        The maximum size of the data that can be exported.
        
        unit (string) --
        
        The unit of measurement for the data size.
        
        value (float) --
        
        The maximum size of the dataset to export.
      - filesToExport (list) --
        
        The files that are exported during the trained model export job.
        
        (string) --
    - trainedModelInferenceJobs (dict) --
      
      Specifies who will receive the trained model inference jobs.
      - containerLogs (list) --
        
        The logs container for the trained model inference job.
        
        (dict) --
        
        Provides the information necessary for a user to access the logs.
        
        allowedAccountIds (list) --
        
        A list of account IDs that are allowed to access the logs.
        
        (string) --
        
        filterPattern (string) --
        
        A regular expression pattern that is used to parse the logs and return information that matches the pattern.
      - maxOutputSize (dict) --
        
        The maximum allowed size of the output of the trained model inference job.
        
        unit (string) --
        
        The measurement unit to use.
        
        value (float) --
        
        The maximum output size value.
- description (string) --
  
  The description of the configured model algorithm association.
- 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) --

GetTrainedModel (updated)

Link ¶
Changes (request, response)
Request

{'versionIdentifier': 'string'}

Response

{'dataChannels': {'s3DataDistributionType': 'FullyReplicated | ShardedByS3Key'},
 'incrementalTrainingDataChannels': [{'channelName': 'string',
                                      'modelName': 'string',
                                      'versionIdentifier': 'string'}],
 'trainingInputMode': 'File | FastFile | Pipe',
 'versionIdentifier': 'string'}

Returns information about a trained model.

See also: AWS API Documentation

Request Syntax

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

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

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

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

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

type versionIdentifier:

string

param versionIdentifier:

The version identifier of the trained model to retrieve. If not specified, the operation returns information about the latest version of the trained model.

rtype:

dict

returns:

Response Syntax

{
    'membershipIdentifier': 'string',
    'collaborationIdentifier': 'string',
    'trainedModelArn': 'string',
    'versionIdentifier': 'string',
    'incrementalTrainingDataChannels': [
        {
            'channelName': 'string',
            'versionIdentifier': 'string',
            'modelName': '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
    },
    'trainingInputMode': 'File'|'FastFile'|'Pipe',
    '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',
            's3DataDistributionType': 'FullyReplicated'|'ShardedByS3Key'
        },
    ]
}

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.
- versionIdentifier (string) --
  
  The version identifier of the trained model. This unique identifier distinguishes this version from other versions of the same trained model.
- incrementalTrainingDataChannels (list) --
  
  Information about the incremental training data channels used to create this version of the trained model. This includes details about the base model that was used for incremental training and the channel configuration.
  - (dict) --
    
    Contains information about an incremental training data channel that was used to create a trained model. This structure provides details about the base model and channel configuration used during incremental training.
    - channelName (string) --
      
      The name of the incremental training data channel that was used.
    - versionIdentifier (string) --
      
      The version identifier of the trained model that was used for incremental training.
    - modelName (string) --
      
      The name of the base trained model that was used for incremental training.
- 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.
- trainingInputMode (string) --
  
  The input mode that was used for accessing the training data when this trained model was created. This indicates how the training data was made available to the training algorithm.
- 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.
    - s3DataDistributionType (string) --
      
      Specifies how the training data stored in Amazon S3 should be distributed to training instances. This parameter controls the data distribution strategy for the training job:
      - FullyReplicated - The entire dataset is replicated on each training instance. This is suitable for smaller datasets and algorithms that require access to the complete dataset.
      - ShardedByS3Key - The dataset is distributed across training instances based on Amazon S3 key names. This is suitable for larger datasets and distributed training scenarios where each instance processes a subset of the data.

GetTrainedModelInferenceJob (updated)

Link ¶
Changes (response)

{'trainedModelVersionIdentifier': 'string'}

Returns information about a trained model inference job.

See also: AWS API Documentation

Request Syntax

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

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

Provides the membership ID of the membership that contains the trained model inference job that you are interested in.

type trainedModelInferenceJobArn:

string

param trainedModelInferenceJobArn:

[REQUIRED]

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

rtype:

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',
    'trainedModelVersionIdentifier': '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.
- trainedModelVersionIdentifier (string) --
  
  The version identifier of the trained model used for this inference job. This identifies the specific version of the trained model that was used to generate the inference results.
- 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) --

ListCollaborationTrainedModelExportJobs (updated)

Link ¶
Changes (request, response)
Request

{'trainedModelVersionIdentifier': 'string'}

Response

{'collaborationTrainedModelExportJobs': {'trainedModelVersionIdentifier': 'string'}}

Returns a list of the export jobs for a trained model in a collaboration.

See also: AWS API Documentation

Request Syntax

client.list_collaboration_trained_model_export_jobs(
    nextToken='string',
    maxResults=123,
    collaborationIdentifier='string',
    trainedModelArn='string',
    trainedModelVersionIdentifier='string'
)

type nextToken:

string

param nextToken:

The token value retrieved from a previous call to access the next page of results.

type maxResults:

integer

param maxResults:

The maximum size of the results that is returned per call.

type collaborationIdentifier:

string

param collaborationIdentifier:

[REQUIRED]

The collaboration ID of the collaboration that contains the trained model export jobs that you are interested in.

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model that was used to create the export jobs that you are interested in.

type trainedModelVersionIdentifier:

string

param trainedModelVersionIdentifier:

The version identifier of the trained model to filter export jobs by. When specified, only export jobs for this specific version of the trained model are returned.

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'collaborationTrainedModelExportJobs': [
        {
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1),
            'name': 'string',
            'outputConfiguration': {
                'members': [
                    {
                        'accountId': 'string'
                    },
                ]
            },
            'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE',
            'statusDetails': {
                'statusCode': 'string',
                'message': 'string'
            },
            'description': 'string',
            'creatorAccountId': 'string',
            'trainedModelArn': 'string',
            'trainedModelVersionIdentifier': 'string',
            'membershipIdentifier': 'string',
            'collaborationIdentifier': 'string'
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The token value used to access the next page of results.
- collaborationTrainedModelExportJobs (list) --
  
  The exports jobs that exist for the requested trained model in the requested collaboration.
  - (dict) --
    
    Provides summary information about a trained model export job in a collaboration.
    - createTime (datetime) --
      
      The time at which the trained model export job was created.
    - updateTime (datetime) --
      
      The most recent time at which the trained model export job was updated.
    - name (string) --
      
      The name of the trained model export job.
    - outputConfiguration (dict) --
      
      Information about the output of the trained model export job.
      - members (list) --
        
        The members that will received the exported trained model output.
        
        (dict) --
        
        Provides information about the member who will receive trained model exports.
        
        accountId (string) --
        
        The account ID of the member who will receive trained model exports.
    - 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.
    - description (string) --
      
      The description of the trained model.
    - creatorAccountId (string) --
      
      The account ID of the member that created the trained model.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model that is being exported.
    - trainedModelVersionIdentifier (string) --
      
      The version identifier of the trained model that was exported in this job.
    - membershipIdentifier (string) --
      
      The membership ID of the member that created the trained model export job.
    - collaborationIdentifier (string) --
      
      The collaboration ID of the collaboration that contains the trained model export job.

ListCollaborationTrainedModelInferenceJobs (updated)

Link ¶
Changes (request, response)
Request

{'trainedModelVersionIdentifier': 'string'}

Response

{'collaborationTrainedModelInferenceJobs': {'trainedModelVersionIdentifier': 'string'}}

Returns a list of trained model inference jobs in a specified collaboration.

See also: AWS API Documentation

Request Syntax

client.list_collaboration_trained_model_inference_jobs(
    nextToken='string',
    maxResults=123,
    collaborationIdentifier='string',
    trainedModelArn='string',
    trainedModelVersionIdentifier='string'
)

type nextToken:

string

param nextToken:

The token value retrieved from a previous call to access the next page of results.

type maxResults:

integer

param maxResults:

The maximum size of the results that is returned per call.

type collaborationIdentifier:

string

param collaborationIdentifier:

[REQUIRED]

The collaboration ID of the collaboration that contains the trained model inference jobs that you are interested in.

type trainedModelArn:

string

param trainedModelArn:

The Amazon Resource Name (ARN) of the trained model that was used to create the trained model inference jobs that you are interested in.

type trainedModelVersionIdentifier:

string

param trainedModelVersionIdentifier:

The version identifier of the trained model to filter inference jobs by. When specified, only inference jobs that used this specific version of the trained model are returned.

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'collaborationTrainedModelInferenceJobs': [
        {
            'trainedModelInferenceJobArn': 'string',
            'configuredModelAlgorithmAssociationArn': 'string',
            'membershipIdentifier': 'string',
            'trainedModelArn': 'string',
            'trainedModelVersionIdentifier': 'string',
            'collaborationIdentifier': 'string',
            'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED'|'INACTIVE',
            'outputConfiguration': {
                'accept': 'string',
                'members': [
                    {
                        'accountId': 'string'
                    },
                ]
            },
            'name': 'string',
            'description': 'string',
            'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
            'metricsStatusDetails': 'string',
            'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
            'logsStatusDetails': 'string',
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1),
            'creatorAccountId': 'string'
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The token value used to access the next page of results.
- collaborationTrainedModelInferenceJobs (list) --
  
  The trained model inference jobs that you are interested in.
  - (dict) --
    
    Provides summary information about a trained model inference job in a collaboration.
    - 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 is used for the trained model inference job.
    - membershipIdentifier (string) --
      
      The membership ID of the membership that contains the trained model inference job.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.
    - trainedModelVersionIdentifier (string) --
      
      The version identifier of the trained model that was used for inference in this job.
    - collaborationIdentifier (string) --
      
      The collaboration ID of the collaboration that contains the trained model inference job.
    - status (string) --
      
      The status of the trained model inference job.
    - outputConfiguration (dict) --
      
      Returns 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.
    - name (string) --
      
      The name of the trained model inference job.
    - description (string) --
      
      The description of the trained model inference job.
    - metricsStatus (string) --
      
      the trained model inference job metrics status.
    - metricsStatusDetails (string) --
      
      Details about the metrics status for trained model inference job.
    - logsStatus (string) --
      
      The trained model inference job logs status.
    - logsStatusDetails (string) --
      
      Details about the logs status for the trained model inference job.
    - 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.
    - creatorAccountId (string) --
      
      The account ID that created the trained model inference job.

ListCollaborationTrainedModels (updated)

Link ¶
Changes (response)

{'collaborationTrainedModels': {'incrementalTrainingDataChannels': [{'channelName': 'string',
                                                                     'modelName': 'string',
                                                                     'versionIdentifier': 'string'}],
                                'versionIdentifier': 'string'}}

Returns a list of the trained models in a collaboration.

See also: AWS API Documentation

Request Syntax

client.list_collaboration_trained_models(
    nextToken='string',
    maxResults=123,
    collaborationIdentifier='string'
)

type nextToken:

string

param nextToken:

The token value retrieved from a previous call to access the next page of results.

type maxResults:

integer

param maxResults:

The maximum size of the results that is returned per call.

type collaborationIdentifier:

string

param collaborationIdentifier:

[REQUIRED]

The collaboration ID of the collaboration that contains the trained models you are interested in.

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'collaborationTrainedModels': [
        {
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1),
            'trainedModelArn': 'string',
            'name': 'string',
            'versionIdentifier': 'string',
            'incrementalTrainingDataChannels': [
                {
                    'channelName': 'string',
                    'versionIdentifier': 'string',
                    'modelName': 'string'
                },
            ],
            'description': 'string',
            'membershipIdentifier': 'string',
            'collaborationIdentifier': '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',
            'configuredModelAlgorithmAssociationArn': 'string',
            'creatorAccountId': 'string'
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The token value used to access the next page of results.
- collaborationTrainedModels (list) --
  
  The trained models in the collaboration that you requested.
  - (dict) --
    
    Provides summary information about a trained model in a collaboration.
    - createTime (datetime) --
      
      The time at which the trained model was created.
    - updateTime (datetime) --
      
      The most recent time at which the trained model was updated.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model.
    - name (string) --
      
      The name of the trained model.
    - versionIdentifier (string) --
      
      The version identifier of this trained model version.
    - incrementalTrainingDataChannels (list) --
      
      Information about the incremental training data channels used to create this version of the trained model.
      - (dict) --
        
        Contains information about an incremental training data channel that was used to create a trained model. This structure provides details about the base model and channel configuration used during incremental training.
        
        channelName (string) --
        
        The name of the incremental training data channel that was used.
        
        versionIdentifier (string) --
        
        The version identifier of the trained model that was used for incremental training.
        
        modelName (string) --
        
        The name of the base trained model that was used for incremental training.
    - description (string) --
      
      The description of the trained model.
    - 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.
    - status (string) --
      
      The status of the trained model.
    - configuredModelAlgorithmAssociationArn (string) --
      
      The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model.
    - creatorAccountId (string) --
      
      The account ID of the member that created the trained model.

ListTrainedModelInferenceJobs (updated)

Link ¶
Changes (request, response)
Request

{'trainedModelVersionIdentifier': 'string'}

Response

{'trainedModelInferenceJobs': {'trainedModelVersionIdentifier': 'string'}}

Returns a list of trained model inference jobs that match the request parameters.

See also: AWS API Documentation

Request Syntax

client.list_trained_model_inference_jobs(
    nextToken='string',
    maxResults=123,
    membershipIdentifier='string',
    trainedModelArn='string',
    trainedModelVersionIdentifier='string'
)

type nextToken:

string

param nextToken:

The token value retrieved from a previous call to access the next page of results.

type maxResults:

integer

param maxResults:

The maximum size of the results that is returned per call.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership

type trainedModelArn:

string

param trainedModelArn:

The Amazon Resource Name (ARN) of a trained model that was used to create the trained model inference jobs that you are interested in.

type trainedModelVersionIdentifier:

string

param trainedModelVersionIdentifier:

The version identifier of the trained model to filter inference jobs by. When specified, only inference jobs that used this specific version of the trained model are returned.

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'trainedModelInferenceJobs': [
        {
            'trainedModelInferenceJobArn': 'string',
            'configuredModelAlgorithmAssociationArn': 'string',
            'membershipIdentifier': 'string',
            'trainedModelArn': 'string',
            'trainedModelVersionIdentifier': 'string',
            'collaborationIdentifier': 'string',
            'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED'|'INACTIVE',
            'outputConfiguration': {
                'accept': 'string',
                'members': [
                    {
                        'accountId': 'string'
                    },
                ]
            },
            'name': 'string',
            'description': 'string',
            'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
            'metricsStatusDetails': 'string',
            'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
            'logsStatusDetails': 'string',
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1)
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The token value used to access the next page of results.
- trainedModelInferenceJobs (list) --
  
  Returns the requested trained model inference jobs.
  - (dict) --
    
    Provides information about the trained model inference job.
    - 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 is used for the trained model inference job.
    - membershipIdentifier (string) --
      
      The membership ID of the membership that contains the trained model inference job.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model that is used for the trained model inference job.
    - trainedModelVersionIdentifier (string) --
      
      The version identifier of the trained model that was used for inference in this job.
    - collaborationIdentifier (string) --
      
      The collaboration ID of the collaboration that contains the trained model inference job.
    - status (string) --
      
      The status of the trained model inference job.
    - outputConfiguration (dict) --
      
      The output configuration information of the trained model 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.
    - name (string) --
      
      The name of the trained model inference job.
    - description (string) --
      
      The description of the trained model inference job.
    - metricsStatus (string) --
      
      The metric status of the trained model inference job.
    - metricsStatusDetails (string) --
      
      Details about the metrics status for the trained model inference job.
    - logsStatus (string) --
      
      The log status of the trained model inference job.
    - logsStatusDetails (string) --
      
      Details about the log status for the trained model inference job.
    - 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.

ListTrainedModels (updated)

Link ¶
Changes (response)

{'trainedModels': {'incrementalTrainingDataChannels': [{'channelName': 'string',
                                                        'modelName': 'string',
                                                        'versionIdentifier': 'string'}],
                   'versionIdentifier': 'string'}}

Returns a list of trained models.

See also: AWS API Documentation

Request Syntax

client.list_trained_models(
    nextToken='string',
    maxResults=123,
    membershipIdentifier='string'
)

type nextToken:

string

param nextToken:

The token value retrieved from a previous call to access the next page of results.

type maxResults:

integer

param maxResults:

The maximum size of the results that is returned per call.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

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

rtype:

dict

returns:

Response Syntax

{
    'nextToken': 'string',
    'trainedModels': [
        {
            'createTime': datetime(2015, 1, 1),
            'updateTime': datetime(2015, 1, 1),
            'trainedModelArn': 'string',
            'versionIdentifier': 'string',
            'incrementalTrainingDataChannels': [
                {
                    'channelName': 'string',
                    'versionIdentifier': 'string',
                    'modelName': 'string'
                },
            ],
            'name': 'string',
            'description': 'string',
            'membershipIdentifier': 'string',
            'collaborationIdentifier': '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',
            'configuredModelAlgorithmAssociationArn': 'string'
        },
    ]
}

Response Structure

(dict) --
- nextToken (string) --
  
  The token value used to access the next page of results.
- trainedModels (list) --
  
  The list of trained models.
  - (dict) --
    
    Summary information about the trained model.
    - createTime (datetime) --
      
      The time at which the trained model was created.
    - updateTime (datetime) --
      
      The most recent time at which the trained model was updated.
    - trainedModelArn (string) --
      
      The Amazon Resource Name (ARN) of the trained model.
    - versionIdentifier (string) --
      
      The version identifier of this trained model version.
    - incrementalTrainingDataChannels (list) --
      
      Information about the incremental training data channels used to create this version of the trained model.
      - (dict) --
        
        Contains information about an incremental training data channel that was used to create a trained model. This structure provides details about the base model and channel configuration used during incremental training.
        
        channelName (string) --
        
        The name of the incremental training data channel that was used.
        
        versionIdentifier (string) --
        
        The version identifier of the trained model that was used for incremental training.
        
        modelName (string) --
        
        The name of the base trained model that was used for incremental training.
    - name (string) --
      
      The name of the trained model.
    - description (string) --
      
      The description of the trained model.
    - 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.
    - status (string) --
      
      The status of the trained model.
    - configuredModelAlgorithmAssociationArn (string) --
      
      The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create this trained model.

StartTrainedModelExportJob (updated)

Link ¶
Changes (request)

{'trainedModelVersionIdentifier': 'string'}

Provides the information necessary to start a trained model export job.

See also: AWS API Documentation

Request Syntax

client.start_trained_model_export_job(
    name='string',
    trainedModelArn='string',
    trainedModelVersionIdentifier='string',
    membershipIdentifier='string',
    outputConfiguration={
        'members': [
            {
                'accountId': 'string'
            },
        ]
    },
    description='string'
)

type name:

string

param name:

[REQUIRED]

The name of the trained model export job.

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model that you want to export.

type trainedModelVersionIdentifier:

string

param trainedModelVersionIdentifier:

The version identifier of the trained model to export. This specifies which version of the trained model should be exported to the specified destination.

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the member that is receiving the exported trained model artifacts.

type outputConfiguration:

dict

param outputConfiguration:

[REQUIRED]

The output configuration information for the trained model export job.

members (list) -- [REQUIRED]

The members that will received the exported trained model output.
- (dict) --
  
  Provides information about the member who will receive trained model exports.
  - accountId (string) -- [REQUIRED]
    
    The account ID of the member who will receive trained model exports.

type description:

string

param description:

The description of the trained model export job.

returns:

None

StartTrainedModelInferenceJob (updated)

Link ¶
Changes (request)

{'trainedModelVersionIdentifier': 'string'}

Defines the information necessary to begin a trained model inference job.

See also: AWS API Documentation

Request Syntax

client.start_trained_model_inference_job(
    membershipIdentifier='string',
    name='string',
    trainedModelArn='string',
    trainedModelVersionIdentifier='string',
    configuredModelAlgorithmAssociationArn='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'
            },
        ]
    },
    dataSource={
        'mlInputChannelArn': 'string'
    },
    description='string',
    containerExecutionParameters={
        'maxPayloadInMB': 123
    },
    environment={
        'string': 'string'
    },
    kmsKeyArn='string',
    tags={
        'string': 'string'
    }
)

type membershipIdentifier:

string

param membershipIdentifier:

[REQUIRED]

The membership ID of the membership that contains the trained model inference job.

type name:

string

param name:

[REQUIRED]

The name of the trained model inference job.

type trainedModelArn:

string

param trainedModelArn:

[REQUIRED]

The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.

type trainedModelVersionIdentifier:

string

param trainedModelVersionIdentifier:

The version identifier of the trained model to use for inference. This specifies which version of the trained model should be used to generate predictions on the input data.

type configuredModelAlgorithmAssociationArn:

string

param configuredModelAlgorithmAssociationArn:

The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.

type resourceConfig:

dict

param resourceConfig:

[REQUIRED]

Defines the resource configuration for the trained model inference job.

instanceType (string) -- [REQUIRED]

The type of instance that is used to perform model inference.
instanceCount (integer) --

The number of instances to use.

type outputConfiguration:

dict

param outputConfiguration:

[REQUIRED]

Defines the output configuration information for the trained model inference job.

accept (string) --

The MIME type used to specify the output data.
members (list) -- [REQUIRED]

Defines the members that can receive inference output.
- (dict) --
  
  Defines who will receive inference results.
  - accountId (string) -- [REQUIRED]
    
    The account ID of the member that can receive inference results.

type dataSource:

dict

param dataSource:

[REQUIRED]

Defines the data source that is used for the trained model inference job.

mlInputChannelArn (string) -- [REQUIRED]

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

type description:

string

param description:

The description of the trained model inference job.

type containerExecutionParameters:

dict

param containerExecutionParameters:

The execution parameters for the container.

maxPayloadInMB (integer) --

The maximum size of the inference container payload, specified in MB.

type environment:

dict

param environment:

The environment variables to set in the Docker container.

(string) --
- (string) --

type kmsKeyArn:

string

param kmsKeyArn:

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.

type tags:

dict

param tags:

The optional metadata that you apply 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) --

rtype:

dict

returns:

Response Syntax

{
    'trainedModelInferenceJobArn': 'string'
}

Response Structure

(dict) --
- trainedModelInferenceJobArn (string) --
  
  The Amazon Resource Name (ARN) of the trained model inference job.