2024/11/07 - AWS Clean Rooms ML - 33 new api methods
Changes This release introduces support for Custom Models in AWS Clean Rooms ML.
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'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model that you want to return information about.
string
[REQUIRED]
The collaboration ID that contains the trained model that you want to return information about.
dict
Response Syntax
{
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'trainedModelArn': 'string',
'name': 'string',
'description': 'string',
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED',
'statusDetails': {
'statusCode': 'string',
'message': 'string'
},
'configuredModelAlgorithmAssociationArn': 'string',
'resourceConfig': {
'instanceCount': 123,
'instanceType': 'ml.m4.xlarge'|'ml.m4.2xlarge'|'ml.m4.4xlarge'|'ml.m4.10xlarge'|'ml.m4.16xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.12xlarge'|'ml.m5.24xlarge'|'ml.c4.xlarge'|'ml.c4.2xlarge'|'ml.c4.4xlarge'|'ml.c4.8xlarge'|'ml.p2.xlarge'|'ml.p2.8xlarge'|'ml.p2.16xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.p4d.24xlarge'|'ml.p4de.24xlarge'|'ml.p5.48xlarge'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.18xlarge'|'ml.c5n.xlarge'|'ml.c5n.2xlarge'|'ml.c5n.4xlarge'|'ml.c5n.9xlarge'|'ml.c5n.18xlarge'|'ml.g5.xlarge'|'ml.g5.2xlarge'|'ml.g5.4xlarge'|'ml.g5.8xlarge'|'ml.g5.16xlarge'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.g5.48xlarge'|'ml.trn1.2xlarge'|'ml.trn1.32xlarge'|'ml.trn1n.32xlarge'|'ml.m6i.large'|'ml.m6i.xlarge'|'ml.m6i.2xlarge'|'ml.m6i.4xlarge'|'ml.m6i.8xlarge'|'ml.m6i.12xlarge'|'ml.m6i.16xlarge'|'ml.m6i.24xlarge'|'ml.m6i.32xlarge'|'ml.c6i.xlarge'|'ml.c6i.2xlarge'|'ml.c6i.8xlarge'|'ml.c6i.4xlarge'|'ml.c6i.12xlarge'|'ml.c6i.16xlarge'|'ml.c6i.24xlarge'|'ml.c6i.32xlarge'|'ml.r5d.large'|'ml.r5d.xlarge'|'ml.r5d.2xlarge'|'ml.r5d.4xlarge'|'ml.r5d.8xlarge'|'ml.r5d.12xlarge'|'ml.r5d.16xlarge'|'ml.r5d.24xlarge'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'volumeSizeInGB': 123
},
'stoppingCondition': {
'maxRuntimeInSeconds': 123
},
'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'metricsStatusDetails': 'string',
'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'logsStatusDetails': 'string',
'trainingContainerImageDigest': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'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.
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.
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.
Assigns information about an ML configuration.
See also: AWS API Documentation
Request Syntax
client.put_ml_configuration(
membershipIdentifier='string',
defaultOutputLocation={
'destination': {
's3Destination': {
's3Uri': 'string'
}
},
'roleArn': 'string'
}
)
string
[REQUIRED]
The membership ID of the member that is being configured.
dict
[REQUIRED]
The default Amazon S3 location where ML output is stored for the specified member.
destination (dict) --
The Amazon S3 location where exported model artifacts are stored.
s3Destination (dict) -- [REQUIRED]
Provides information about an Amazon S3 bucket and path.
s3Uri (string) -- [REQUIRED]
The Amazon S3 location URI.
roleArn (string) -- [REQUIRED]
The Amazon Resource Name (ARN) of the service access role that is used to store the model artifacts.
None
Returns a list of the ML input channels in a collaboration.
See also: AWS API Documentation
Request Syntax
client.list_collaboration_ml_input_channels(
nextToken='string',
maxResults=123,
collaborationIdentifier='string'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum number of results to return.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the ML input channels that you want to list.
dict
Response Syntax
{
'nextToken': 'string',
'collaborationMLInputChannelsList': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'name': 'string',
'configuredModelAlgorithmAssociations': [
'string',
],
'mlInputChannelArn': 'string',
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE',
'creatorAccountId': 'string',
'description': 'string'
},
]
}
Response Structure
(dict) --
nextToken (string) --
The token value used to access the next page of results.
collaborationMLInputChannelsList (list) --
The list of ML input channels that you wanted.
(dict) --
Provides summary information about an ML input channel in a collaboration.
createTime (datetime) --
The time at which the ML input channel was created.
updateTime (datetime) --
The most recent time at which the ML input channel was updated.
membershipIdentifier (string) --
The membership ID of the membership that contains the ML input channel.
collaborationIdentifier (string) --
The collaboration ID of the collaboration that contains the ML input channel.
name (string) --
The name of the ML input channel.
configuredModelAlgorithmAssociations (list) --
The associated configured model algorithms used to create the ML input channel.
(string) --
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel.
status (string) --
The status of the ML input channel.
creatorAccountId (string) --
The account ID of the member who created the ML input channel.
description (string) --
The description of the ML input channel.
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'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the trained models you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'collaborationTrainedModels': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'trainedModelArn': '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',
'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.
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.
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'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the trained model export jobs that you are interested in.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model that was used to create the export jobs that you are interested in.
dict
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',
'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.
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.
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'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The membership
string
The Amazon Resource Name (ARN) of a trained model that was used to create the trained model inference jobs that you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'trainedModelInferenceJobs': [
{
'trainedModelInferenceJobArn': 'string',
'configuredModelAlgorithmAssociationArn': 'string',
'membershipIdentifier': 'string',
'trainedModelArn': '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.
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.
Returns a list of configured model algorithm associations.
See also: AWS API Documentation
Request Syntax
client.list_configured_model_algorithm_associations(
nextToken='string',
maxResults=123,
membershipIdentifier='string'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The membership ID of the member that created the configured model algorithm associations you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'configuredModelAlgorithmAssociations': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'configuredModelAlgorithmAssociationArn': 'string',
'configuredModelAlgorithmArn': 'string',
'name': 'string',
'description': 'string',
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string'
},
]
}
Response Structure
(dict) --
nextToken (string) --
The token value used to access the next page of results.
configuredModelAlgorithmAssociations (list) --
The list of configured model algorithm associations.
(dict) --
Provides summary information about the configured model algorithm association.
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.
configuredModelAlgorithmArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm that is being associated.
name (string) --
The name of the configured model algorithm association.
description (string) --
The description 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.
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',
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'
}
)
string
[REQUIRED]
The membership ID of the membership that contains the trained model inference job.
string
[REQUIRED]
The name of the trained model inference job.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model that is used for this trained model inference job.
string
The Amazon Resource Name (ARN) of the configured model algorithm association that is used for this trained model inference job.
dict
[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.
dict
[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.
dict
[REQUIRED]
Defines he 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.
string
The description of the trained model inference job.
dict
The execution parameters for the container.
maxPayloadInMB (integer) --
The maximum size of the inference container payload, specified in MB.
dict
The environment variables to set in the Docker container.
(string) --
(string) --
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.
dict
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) --
dict
Response Syntax
{
'trainedModelInferenceJobArn': 'string'
}
Response Structure
(dict) --
trainedModelInferenceJobArn (string) --
The Amazon Resource Name (ARN) of the trained model inference job.
Creates a configured model algorithm using a container image stored in an ECR repository.
See also: AWS API Documentation
Request Syntax
client.create_configured_model_algorithm(
name='string',
description='string',
roleArn='string',
trainingContainerConfig={
'imageUri': 'string',
'entrypoint': [
'string',
],
'arguments': [
'string',
],
'metricDefinitions': [
{
'name': 'string',
'regex': 'string'
},
]
},
inferenceContainerConfig={
'imageUri': 'string'
},
tags={
'string': 'string'
},
kmsKeyArn='string'
)
string
[REQUIRED]
The name of the configured model algorithm.
string
The description of the configured model algorithm.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the role that is used to access the repository.
dict
Configuration information for the training container, including entrypoints and arguments.
imageUri (string) -- [REQUIRED]
The registry path of the docker image that contains the algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.
entrypoint (list) --
The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
(string) --
arguments (list) --
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
(string) --
metricDefinitions (list) --
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. Amazon Web Services Clean Rooms ML publishes each metric to all members' Amazon CloudWatch using IAM role configured in PutMLConfiguration.
(dict) --
Information about the model metric that is reported for a trained model.
name (string) -- [REQUIRED]
The name of the model metric.
regex (string) -- [REQUIRED]
The regular expression statement that defines how the model metric is reported.
dict
Configuration information for the inference container that is used when you run an inference job on a configured model algorithm.
imageUri (string) -- [REQUIRED]
The registry path of the docker image that contains the inference algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.
dict
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) --
string
The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the configured ML model algorithm and associated data.
dict
Response Syntax
{
'configuredModelAlgorithmArn': 'string'
}
Response Structure
(dict) --
configuredModelAlgorithmArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm.
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'
}
},
'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'
}
)
string
[REQUIRED]
The membership ID of the member who is associating this configured model algorithm.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm that you want to associate.
string
[REQUIRED]
The name of the configured model algorithm association.
string
The description of the configured model algorithm association.
dict
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.
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.
dict
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) --
dict
Response Syntax
{
'configuredModelAlgorithmAssociationArn': 'string'
}
Response Structure
(dict) --
configuredModelAlgorithmAssociationArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm association.
Returns information about a configured model algorithm.
See also: AWS API Documentation
Request Syntax
client.get_configured_model_algorithm(
configuredModelAlgorithmArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm that you want to return information about.
dict
Response Syntax
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'configuredModelAlgorithmArn': 'string',
'name': 'string',
'trainingContainerConfig': {
'imageUri': 'string',
'entrypoint': [
'string',
],
'arguments': [
'string',
],
'metricDefinitions': [
{
'name': 'string',
'regex': 'string'
},
]
},
'inferenceContainerConfig': {
'imageUri': 'string'
},
'roleArn': 'string',
'description': 'string',
'tags': {
'string': 'string'
},
'kmsKeyArn': 'string'
}
Response Structure
(dict) --
createTime (datetime) --
The time at which the configured model algorithm was created.
updateTime (datetime) --
The most recent time at which the configured model algorithm was updated.
configuredModelAlgorithmArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm.
name (string) --
The name of the configured model algorithm.
trainingContainerConfig (dict) --
The configuration information of the training container for the configured model algorithm.
imageUri (string) --
The registry path of the docker image that contains the algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.
entrypoint (list) --
The entrypoint script for a Docker container used to run a training job. This script takes precedence over the default train processing instructions. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
(string) --
arguments (list) --
The arguments for a container used to run a training job. See How Amazon SageMaker Runs Your Training Image for additional information. For more information, see How Sagemaker runs your training image.
(string) --
metricDefinitions (list) --
A list of metric definition objects. Each object specifies the metric name and regular expressions used to parse algorithm logs. Amazon Web Services Clean Rooms ML publishes each metric to all members' Amazon CloudWatch using IAM role configured in PutMLConfiguration.
(dict) --
Information about the model metric that is reported for a trained model.
name (string) --
The name of the model metric.
regex (string) --
The regular expression statement that defines how the model metric is reported.
inferenceContainerConfig (dict) --
Configuration information for the inference container.
imageUri (string) --
The registry path of the docker image that contains the inference algorithm. Clean Rooms ML supports both registry/repository[:tag] and registry/repositry[@digest] image path formats. For more information about using images in Clean Rooms ML, see the Sagemaker API reference.
roleArn (string) --
The Amazon Resource Name (ARN) of the service role that was used to create the configured model algorithm.
description (string) --
The description of the configured model algorithm.
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) --
kmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the configured ML model and associated data.
Returns information about a trained model.
See also: AWS API Documentation
Request Syntax
client.get_trained_model(
trainedModelArn='string',
membershipIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model that you are interested in.
string
[REQUIRED]
The membership ID of the member that created the trained model that you are interested in.
dict
Response Syntax
{
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'trainedModelArn': 'string',
'name': 'string',
'description': 'string',
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED',
'statusDetails': {
'statusCode': 'string',
'message': 'string'
},
'configuredModelAlgorithmAssociationArn': 'string',
'resourceConfig': {
'instanceCount': 123,
'instanceType': 'ml.m4.xlarge'|'ml.m4.2xlarge'|'ml.m4.4xlarge'|'ml.m4.10xlarge'|'ml.m4.16xlarge'|'ml.g4dn.xlarge'|'ml.g4dn.2xlarge'|'ml.g4dn.4xlarge'|'ml.g4dn.8xlarge'|'ml.g4dn.12xlarge'|'ml.g4dn.16xlarge'|'ml.m5.large'|'ml.m5.xlarge'|'ml.m5.2xlarge'|'ml.m5.4xlarge'|'ml.m5.12xlarge'|'ml.m5.24xlarge'|'ml.c4.xlarge'|'ml.c4.2xlarge'|'ml.c4.4xlarge'|'ml.c4.8xlarge'|'ml.p2.xlarge'|'ml.p2.8xlarge'|'ml.p2.16xlarge'|'ml.p3.2xlarge'|'ml.p3.8xlarge'|'ml.p3.16xlarge'|'ml.p3dn.24xlarge'|'ml.p4d.24xlarge'|'ml.p4de.24xlarge'|'ml.p5.48xlarge'|'ml.c5.xlarge'|'ml.c5.2xlarge'|'ml.c5.4xlarge'|'ml.c5.9xlarge'|'ml.c5.18xlarge'|'ml.c5n.xlarge'|'ml.c5n.2xlarge'|'ml.c5n.4xlarge'|'ml.c5n.9xlarge'|'ml.c5n.18xlarge'|'ml.g5.xlarge'|'ml.g5.2xlarge'|'ml.g5.4xlarge'|'ml.g5.8xlarge'|'ml.g5.16xlarge'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.g5.48xlarge'|'ml.trn1.2xlarge'|'ml.trn1.32xlarge'|'ml.trn1n.32xlarge'|'ml.m6i.large'|'ml.m6i.xlarge'|'ml.m6i.2xlarge'|'ml.m6i.4xlarge'|'ml.m6i.8xlarge'|'ml.m6i.12xlarge'|'ml.m6i.16xlarge'|'ml.m6i.24xlarge'|'ml.m6i.32xlarge'|'ml.c6i.xlarge'|'ml.c6i.2xlarge'|'ml.c6i.8xlarge'|'ml.c6i.4xlarge'|'ml.c6i.12xlarge'|'ml.c6i.16xlarge'|'ml.c6i.24xlarge'|'ml.c6i.32xlarge'|'ml.r5d.large'|'ml.r5d.xlarge'|'ml.r5d.2xlarge'|'ml.r5d.4xlarge'|'ml.r5d.8xlarge'|'ml.r5d.12xlarge'|'ml.r5d.16xlarge'|'ml.r5d.24xlarge'|'ml.t3.medium'|'ml.t3.large'|'ml.t3.xlarge'|'ml.t3.2xlarge'|'ml.r5.large'|'ml.r5.xlarge'|'ml.r5.2xlarge'|'ml.r5.4xlarge'|'ml.r5.8xlarge'|'ml.r5.12xlarge'|'ml.r5.16xlarge'|'ml.r5.24xlarge',
'volumeSizeInGB': 123
},
'stoppingCondition': {
'maxRuntimeInSeconds': 123
},
'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'metricsStatusDetails': 'string',
'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'logsStatusDetails': 'string',
'trainingContainerImageDigest': 'string',
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'hyperparameters': {
'string': 'string'
},
'environment': {
'string': 'string'
},
'kmsKeyArn': 'string',
'tags': {
'string': 'string'
},
'dataChannels': [
{
'mlInputChannelArn': 'string',
'channelName': 'string'
},
]
}
Response Structure
(dict) --
membershipIdentifier (string) --
The membership ID of the member that created the trained model.
collaborationIdentifier (string) --
The collaboration ID of the collaboration that contains the trained model.
trainedModelArn (string) --
The Amazon Resource Name (ARN) of the trained model.
name (string) --
The name of the trained model.
description (string) --
The description of the trained model.
status (string) --
The status of the trained model.
statusDetails (dict) --
Details about the status of a resource.
statusCode (string) --
The status code that was returned. The status code is intended for programmatic error handling. Clean Rooms ML will not change the status code for existing error conditions.
message (string) --
The error message that was returned. The message is intended for human consumption and can change at any time. Use the statusCode for programmatic error handling.
configuredModelAlgorithmAssociationArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm association that was used to create the trained model.
resourceConfig (dict) --
The EC2 resource configuration that was used to create the trained model.
instanceCount (integer) --
The number of resources that are used to train the model.
instanceType (string) --
The instance type that is used to train the model.
volumeSizeInGB (integer) --
The maximum size of the instance that is used to train the model.
stoppingCondition (dict) --
The stopping condition that was used to terminate model training.
maxRuntimeInSeconds (integer) --
The maximum amount of time, in seconds, that model training can run before it is terminated.
metricsStatus (string) --
The status of the model metrics.
metricsStatusDetails (string) --
Details about the metrics status for the trained model.
logsStatus (string) --
The logs status for the trained model.
logsStatusDetails (string) --
Details about the logs status for the trained model.
trainingContainerImageDigest (string) --
Information about the training image container.
createTime (datetime) --
The time at which the trained model was created.
updateTime (datetime) --
The most recent time at which the trained model was updated.
hyperparameters (dict) --
The hyperparameters that were used to create the trained model.
(string) --
(string) --
environment (dict) --
The EC2 environment that was used to create the trained model.
(string) --
(string) --
kmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the trained ML model and associated data.
tags (dict) --
The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.
(string) --
(string) --
dataChannels (list) --
The data channels that were used for the trained model.
(dict) --
Information about the model training data channel. A training data channel is a named data source that the training algorithms can consume.
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel for this model training data channel.
channelName (string) --
The name of the training data channel.
Returns a list of ML input channels.
See also: AWS API Documentation
Request Syntax
client.list_ml_input_channels(
nextToken='string',
maxResults=123,
membershipIdentifier='string'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum number of ML input channels to return.
string
[REQUIRED]
The membership ID of the membership that contains the ML input channels that you want to list.
dict
Response Syntax
{
'nextToken': 'string',
'mlInputChannelsList': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'name': 'string',
'configuredModelAlgorithmAssociations': [
'string',
],
'protectedQueryIdentifier': 'string',
'mlInputChannelArn': 'string',
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE',
'description': 'string'
},
]
}
Response Structure
(dict) --
nextToken (string) --
The token value used to access the next page of results.
mlInputChannelsList (list) --
The list of ML input channels that you wanted.
(dict) --
Provides summary information about the ML input channel.
createTime (datetime) --
The time at which the ML input channel was created.
updateTime (datetime) --
The most recent time at which the ML input channel was updated.
membershipIdentifier (string) --
The membership ID of the membership that contains the ML input channel.
collaborationIdentifier (string) --
The collaboration ID of the collaboration that contains the ML input channel.
name (string) --
The name of the ML input channel.
configuredModelAlgorithmAssociations (list) --
The associated configured model algorithms used to create the ML input channel.
(string) --
protectedQueryIdentifier (string) --
The ID of the protected query that was used to create the ML input channel.
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel.
status (string) --
The status of the ML input channel.
description (string) --
The description of the ML input channel.
Returns information about a specific ML configuration.
See also: AWS API Documentation
Request Syntax
client.get_ml_configuration(
membershipIdentifier='string'
)
string
[REQUIRED]
The membership ID of the member that owns the ML configuration you want to return information about.
dict
Response Syntax
{
'membershipIdentifier': 'string',
'defaultOutputLocation': {
'destination': {
's3Destination': {
's3Uri': 'string'
}
},
'roleArn': 'string'
},
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1)
}
Response Structure
(dict) --
membershipIdentifier (string) --
The membership ID of the member that owns the ML configuration you requested.
defaultOutputLocation (dict) --
The Amazon S3 location where ML model output is stored.
destination (dict) --
The Amazon S3 location where exported model artifacts are stored.
s3Destination (dict) --
Provides information about an Amazon S3 bucket and path.
s3Uri (string) --
The Amazon S3 location URI.
roleArn (string) --
The Amazon Resource Name (ARN) of the service access role that is used to store the model artifacts.
createTime (datetime) --
The time at which the ML configuration was created.
updateTime (datetime) --
The most recent time at which the ML configuration was updated.
Submits a request to cancel the trained model job.
See also: AWS API Documentation
Request Syntax
client.cancel_trained_model(
membershipIdentifier='string',
trainedModelArn='string'
)
string
[REQUIRED]
The membership ID of the trained model job that you want to cancel.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model job that you want to cancel.
None
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
},
dataChannels=[
{
'mlInputChannelArn': 'string',
'channelName': 'string'
},
],
description='string',
kmsKeyArn='string',
tags={
'string': 'string'
}
)
string
[REQUIRED]
The membership ID of the member that is creating the trained model.
string
[REQUIRED]
The name of the trained model.
string
[REQUIRED]
The associated configured model algorithm used to train this model.
dict
Algorithm-specific parameters that influence the quality of the model. You set hyperparameters before you start the learning process.
(string) --
(string) --
dict
The environment variables to set in the Docker container.
(string) --
(string) --
dict
[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.
dict
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.
list
[REQUIRED]
Defines the data channels that are used as input for the trained model request.
(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.
string
The description of the trained model.
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 the associated data.
dict
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) --
dict
Response Syntax
{
'trainedModelArn': 'string'
}
Response Structure
(dict) --
trainedModelArn (string) --
The Amazon Resource Name (ARN) of the trained model.
Provides the information to create an ML input channel. An ML input channel is the result of a query that can be used for ML modeling.
See also: AWS API Documentation
Request Syntax
client.create_ml_input_channel(
membershipIdentifier='string',
configuredModelAlgorithmAssociations=[
'string',
],
inputChannel={
'dataSource': {
'protectedQueryInputParameters': {
'sqlParameters': {
'queryString': 'string',
'analysisTemplateArn': 'string',
'parameters': {
'string': 'string'
}
},
'computeConfiguration': {
'worker': {
'type': 'CR.1X'|'CR.4X',
'number': 123
}
}
}
},
'roleArn': 'string'
},
name='string',
retentionInDays=123,
description='string',
kmsKeyArn='string',
tags={
'string': 'string'
}
)
string
[REQUIRED]
The membership ID of the member that is creating the ML input channel.
list
[REQUIRED]
The associated configured model algorithms that are necessary to create this ML input channel.
(string) --
dict
[REQUIRED]
The input data that is used to create this ML input channel.
dataSource (dict) -- [REQUIRED]
The data source that is used to create the ML input channel.
protectedQueryInputParameters (dict) --
Provides information necessary to perform the protected query.
sqlParameters (dict) -- [REQUIRED]
The parameters for the SQL type Protected Query.
queryString (string) --
The query string to be submitted.
analysisTemplateArn (string) --
The Amazon Resource Name (ARN) associated with the analysis template within a collaboration.
parameters (dict) --
The protected query SQL parameters.
(string) --
(string) --
computeConfiguration (dict) --
Provides configuration information for the workers that will perform the protected query.
worker (dict) --
The worker instances that will perform the compute work.
type (string) --
The instance type of the compute workers that are used.
number (integer) --
The number of compute workers that are used.
roleArn (string) -- [REQUIRED]
The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field the input channel.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.
string
[REQUIRED]
The name of the ML input channel.
integer
[REQUIRED]
The number of days that the data in the ML input channel is retained.
string
The description of the ML input channel.
string
The Amazon Resource Name (ARN) of the KMS key that is used to access the input channel.
dict
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) --
dict
Response Syntax
{
'mlInputChannelArn': 'string'
}
Response Structure
(dict) --
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel.
Provides the information necessary to delete an ML input channel.
See also: AWS API Documentation
Request Syntax
client.delete_ml_input_channel_data(
mlInputChannelArn='string',
membershipIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the ML input channel that you want to delete.
string
[REQUIRED]
The membership ID of the membership that contains the ML input channel you want to delete.
None
Deletes a configured model algorithm.
See also: AWS API Documentation
Request Syntax
client.delete_configured_model_algorithm(
configuredModelAlgorithmArn='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm that you want to delete.
None
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'
)
string
[REQUIRED]
Provides the membership ID of the membership that contains the trained model inference job that you are interested in.
string
[REQUIRED]
Provides the Amazon Resource Name (ARN) of the trained model inference job that you are interested in.
dict
Response Syntax
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'trainedModelInferenceJobArn': 'string',
'configuredModelAlgorithmAssociationArn': 'string',
'name': 'string',
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'CANCEL_PENDING'|'CANCEL_IN_PROGRESS'|'CANCEL_FAILED'|'INACTIVE',
'trainedModelArn': 'string',
'resourceConfig': {
'instanceType': 'ml.r7i.48xlarge'|'ml.r6i.16xlarge'|'ml.m6i.xlarge'|'ml.m5.4xlarge'|'ml.p2.xlarge'|'ml.m4.16xlarge'|'ml.r7i.16xlarge'|'ml.m7i.xlarge'|'ml.m6i.12xlarge'|'ml.r7i.8xlarge'|'ml.r7i.large'|'ml.m7i.12xlarge'|'ml.m6i.24xlarge'|'ml.m7i.24xlarge'|'ml.r6i.8xlarge'|'ml.r6i.large'|'ml.g5.2xlarge'|'ml.m5.large'|'ml.p3.16xlarge'|'ml.m7i.48xlarge'|'ml.m6i.16xlarge'|'ml.p2.16xlarge'|'ml.g5.4xlarge'|'ml.m7i.16xlarge'|'ml.c4.2xlarge'|'ml.c5.2xlarge'|'ml.c6i.32xlarge'|'ml.c4.4xlarge'|'ml.g5.8xlarge'|'ml.c6i.xlarge'|'ml.c5.4xlarge'|'ml.g4dn.xlarge'|'ml.c7i.xlarge'|'ml.c6i.12xlarge'|'ml.g4dn.12xlarge'|'ml.c7i.12xlarge'|'ml.c6i.24xlarge'|'ml.g4dn.2xlarge'|'ml.c7i.24xlarge'|'ml.c7i.2xlarge'|'ml.c4.8xlarge'|'ml.c6i.2xlarge'|'ml.g4dn.4xlarge'|'ml.c7i.48xlarge'|'ml.c7i.4xlarge'|'ml.c6i.16xlarge'|'ml.c5.9xlarge'|'ml.g4dn.16xlarge'|'ml.c7i.16xlarge'|'ml.c6i.4xlarge'|'ml.c5.xlarge'|'ml.c4.xlarge'|'ml.g4dn.8xlarge'|'ml.c7i.8xlarge'|'ml.c7i.large'|'ml.g5.xlarge'|'ml.c6i.8xlarge'|'ml.c6i.large'|'ml.g5.12xlarge'|'ml.g5.24xlarge'|'ml.m7i.2xlarge'|'ml.c5.18xlarge'|'ml.g5.48xlarge'|'ml.m6i.2xlarge'|'ml.g5.16xlarge'|'ml.m7i.4xlarge'|'ml.p3.2xlarge'|'ml.r6i.32xlarge'|'ml.m6i.4xlarge'|'ml.m5.xlarge'|'ml.m4.10xlarge'|'ml.r6i.xlarge'|'ml.m5.12xlarge'|'ml.m4.xlarge'|'ml.r7i.2xlarge'|'ml.r7i.xlarge'|'ml.r6i.12xlarge'|'ml.m5.24xlarge'|'ml.r7i.12xlarge'|'ml.m7i.8xlarge'|'ml.m7i.large'|'ml.r6i.24xlarge'|'ml.r6i.2xlarge'|'ml.m4.2xlarge'|'ml.r7i.24xlarge'|'ml.r7i.4xlarge'|'ml.m6i.8xlarge'|'ml.m6i.large'|'ml.m5.2xlarge'|'ml.p2.8xlarge'|'ml.r6i.4xlarge'|'ml.m6i.32xlarge'|'ml.p3.8xlarge'|'ml.m4.4xlarge',
'instanceCount': 123
},
'outputConfiguration': {
'accept': 'string',
'members': [
{
'accountId': 'string'
},
]
},
'membershipIdentifier': 'string',
'dataSource': {
'mlInputChannelArn': 'string'
},
'containerExecutionParameters': {
'maxPayloadInMB': 123
},
'statusDetails': {
'statusCode': 'string',
'message': 'string'
},
'description': 'string',
'inferenceContainerImageDigest': 'string',
'environment': {
'string': 'string'
},
'kmsKeyArn': 'string',
'metricsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'metricsStatusDetails': 'string',
'logsStatus': 'PUBLISH_SUCCEEDED'|'PUBLISH_FAILED',
'logsStatusDetails': 'string',
'tags': {
'string': 'string'
}
}
Response Structure
(dict) --
createTime (datetime) --
The time at which the trained model inference job was created.
updateTime (datetime) --
The most recent time at which the trained model inference job was updated.
trainedModelInferenceJobArn (string) --
The Amazon Resource Name (ARN) of the trained model inference job.
configuredModelAlgorithmAssociationArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm association that was used for the trained model inference job.
name (string) --
The name of the trained model inference job.
status (string) --
The status of the trained model inference job.
trainedModelArn (string) --
The Amazon Resource Name (ARN) for the trained model that was used for the trained model inference job.
resourceConfig (dict) --
The resource configuration information for the trained model inference job.
instanceType (string) --
The type of instance that is used to perform model inference.
instanceCount (integer) --
The number of instances to use.
outputConfiguration (dict) --
The output configuration information for the trained model inference job.
accept (string) --
The MIME type used to specify the output data.
members (list) --
Defines the members that can receive inference output.
(dict) --
Defines who will receive inference results.
accountId (string) --
The account ID of the member that can receive inference results.
membershipIdentifier (string) --
The membership ID of the membership that contains the trained model inference job.
dataSource (dict) --
The data source that was used for the trained model inference job.
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel for this model inference data source.
containerExecutionParameters (dict) --
The execution parameters for the model inference job container.
maxPayloadInMB (integer) --
The maximum size of the inference container payload, specified in MB.
statusDetails (dict) --
Details about the status of a resource.
statusCode (string) --
The status code that was returned. The status code is intended for programmatic error handling. Clean Rooms ML will not change the status code for existing error conditions.
message (string) --
The error message that was returned. The message is intended for human consumption and can change at any time. Use the statusCode for programmatic error handling.
description (string) --
The description of the trained model inference job.
inferenceContainerImageDigest (string) --
Information about the training container image.
environment (dict) --
The environment variables to set in the Docker container.
(string) --
(string) --
kmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key. This key is used to encrypt and decrypt customer-owned data in the ML inference job and associated data.
metricsStatus (string) --
The metrics status for the trained model inference job.
metricsStatusDetails (string) --
Details about the metrics status for the trained model inference job.
logsStatus (string) --
The logs status for the trained model inference job.
logsStatusDetails (string) --
Details about the logs status for the trained model inference job.
tags (dict) --
The optional metadata that you applied to the resource to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define.
The following basic restrictions apply to tags:
Maximum number of tags per resource - 50.
For each resource, each tag key must be unique, and each tag key can have only one value.
Maximum key length - 128 Unicode characters in UTF-8.
Maximum value length - 256 Unicode characters in UTF-8.
If your tagging schema is used across multiple services and resources, remember that other services may have restrictions on allowed characters. Generally allowed characters are: letters, numbers, and spaces representable in UTF-8, and the following characters: + - = . _ : / @.
Tag keys and values are case sensitive.
Do not use aws:, AWS:, or any upper or lowercase combination of such as a prefix for keys as it is reserved for AWS use. You cannot edit or delete tag keys with this prefix. Values can have this prefix. If a tag value has aws as its prefix but the key does not, then Clean Rooms ML considers it to be a user tag and will count against the limit of 50 tags. Tags with only the key prefix of aws do not count against your tags per resource limit.
(string) --
(string) --
Deletes a ML modeling configuration.
See also: AWS API Documentation
Request Syntax
client.delete_ml_configuration(
membershipIdentifier='string'
)
string
[REQUIRED]
The membership ID of the of the member that is deleting the ML modeling configuration.
None
Returns information about a specific ML input channel in a collaboration.
See also: AWS API Documentation
Request Syntax
client.get_collaboration_ml_input_channel(
mlInputChannelArn='string',
collaborationIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the ML input channel that you want to get.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the ML input channel that you want to get.
dict
Response Syntax
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'creatorAccountId': 'string',
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'mlInputChannelArn': 'string',
'name': 'string',
'configuredModelAlgorithmAssociations': [
'string',
],
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE',
'statusDetails': {
'statusCode': 'string',
'message': 'string'
},
'retentionInDays': 123,
'numberOfRecords': 123,
'description': 'string'
}
Response Structure
(dict) --
createTime (datetime) --
The time at which the ML input channel was created.
updateTime (datetime) --
The most recent time at which the ML input channel was updated.
creatorAccountId (string) --
The account ID of the member who created the ML input channel.
membershipIdentifier (string) --
The membership ID of the membership that contains the ML input channel.
collaborationIdentifier (string) --
The collaboration ID of the collaboration that contains the ML input channel.
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel.
name (string) --
The name of the ML input channel.
configuredModelAlgorithmAssociations (list) --
The configured model algorithm associations that were used to create the ML input channel.
(string) --
status (string) --
The status of the ML input channel.
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.
retentionInDays (integer) --
The number of days to retain the data for the ML input channel.
numberOfRecords (integer) --
The number of records in the ML input channel.
description (string) --
The description of the ML input channel.
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',
membershipIdentifier='string',
outputConfiguration={
'members': [
{
'accountId': 'string'
},
]
},
description='string'
)
string
[REQUIRED]
The name of the trained model export job.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model that you want to export.
string
[REQUIRED]
The membership ID of the member that is receiving the exported trained model artifacts.
dict
[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.
string
The description of the trained model export job.
None
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'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.
string
[REQUIRED]
The membership ID of the member that created the configured model algorithm association.
dict
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'
}
},
'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.
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) --
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'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the trained model inference jobs that you are interested in.
string
The Amazon Resource Name (ARN) of the trained model that was used to create the trained model inference jobs that you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'collaborationTrainedModelInferenceJobs': [
{
'trainedModelInferenceJobArn': 'string',
'configuredModelAlgorithmAssociationArn': 'string',
'membershipIdentifier': 'string',
'trainedModelArn': '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.
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.
Deletes a configured model algorithm association.
See also: AWS API Documentation
Request Syntax
client.delete_configured_model_algorithm_association(
configuredModelAlgorithmAssociationArn='string',
membershipIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm association that you want to delete.
string
[REQUIRED]
The membership ID of the member that is deleting the configured model algorithm association.
None
Submits a request to cancel a trained model inference job.
See also: AWS API Documentation
Request Syntax
client.cancel_trained_model_inference_job(
membershipIdentifier='string',
trainedModelInferenceJobArn='string'
)
string
[REQUIRED]
The membership ID of the trained model inference job that you want to cancel.
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model inference job that you want to cancel.
None
Returns a list of the configured model algorithm associations in a collaboration.
See also: AWS API Documentation
Request Syntax
client.list_collaboration_configured_model_algorithm_associations(
nextToken='string',
maxResults=123,
collaborationIdentifier='string'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The collaboration ID of the collaboration that contains the configured model algorithm associations that you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'collaborationConfiguredModelAlgorithmAssociations': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'configuredModelAlgorithmAssociationArn': 'string',
'name': 'string',
'description': 'string',
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'configuredModelAlgorithmArn': 'string',
'creatorAccountId': 'string'
},
]
}
Response Structure
(dict) --
nextToken (string) --
The token value used to access the next page of results.
collaborationConfiguredModelAlgorithmAssociations (list) --
The configured model algorithm associations that belong to this collaboration.
(dict) --
Provides summary information about a configured model algorithm in a collaboration.
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.
name (string) --
The name of the configured model algorithm association.
description (string) --
The description 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 is associated to the collaboration.
creatorAccountId (string) --
The account ID of the member that created the configured model algorithm association.
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'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the configured model algorithm association that you want to return information about.
string
[REQUIRED]
The collaboration ID for the collaboration that contains the configured model algorithm association that you want to return information about.
dict
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'
}
},
'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.
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.
Returns a list of configured model algorithms.
See also: AWS API Documentation
Request Syntax
client.list_configured_model_algorithms(
nextToken='string',
maxResults=123
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
dict
Response Syntax
{
'nextToken': 'string',
'configuredModelAlgorithms': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'configuredModelAlgorithmArn': 'string',
'name': 'string',
'description': 'string'
},
]
}
Response Structure
(dict) --
nextToken (string) --
The token value used to access the next page of results.
configuredModelAlgorithms (list) --
The list of configured model algorithms.
(dict) --
Provides summary information about a configured model algorithm.
createTime (datetime) --
The time at which the configured model algorithm was created.
updateTime (datetime) --
The most recent time at which the configured model algorithm was updated.
configuredModelAlgorithmArn (string) --
The Amazon Resource Name (ARN) of the configured model algorithm.
name (string) --
The name of the configured model algorithm.
description (string) --
The description of the configured model algorithm.
Deletes the output of a trained model.
See also: AWS API Documentation
Request Syntax
client.delete_trained_model_output(
trainedModelArn='string',
membershipIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the trained model whose output you want to delete.
string
[REQUIRED]
The membership ID of the member that is deleting the trained model output.
None
Returns information about an ML input channel.
See also: AWS API Documentation
Request Syntax
client.get_ml_input_channel(
mlInputChannelArn='string',
membershipIdentifier='string'
)
string
[REQUIRED]
The Amazon Resource Name (ARN) of the ML input channel that you want to get.
string
[REQUIRED]
The membership ID of the membership that contains the ML input channel that you want to get.
dict
Response Syntax
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'membershipIdentifier': 'string',
'collaborationIdentifier': 'string',
'inputChannel': {
'dataSource': {
'protectedQueryInputParameters': {
'sqlParameters': {
'queryString': 'string',
'analysisTemplateArn': 'string',
'parameters': {
'string': 'string'
}
},
'computeConfiguration': {
'worker': {
'type': 'CR.1X'|'CR.4X',
'number': 123
}
}
}
},
'roleArn': 'string'
},
'protectedQueryIdentifier': 'string',
'mlInputChannelArn': 'string',
'name': 'string',
'configuredModelAlgorithmAssociations': [
'string',
],
'status': 'CREATE_PENDING'|'CREATE_IN_PROGRESS'|'CREATE_FAILED'|'ACTIVE'|'DELETE_PENDING'|'DELETE_IN_PROGRESS'|'DELETE_FAILED'|'INACTIVE',
'statusDetails': {
'statusCode': 'string',
'message': 'string'
},
'retentionInDays': 123,
'numberOfRecords': 123,
'numberOfFiles': 123.0,
'sizeInGb': 123.0,
'description': 'string',
'kmsKeyArn': 'string',
'tags': {
'string': 'string'
}
}
Response Structure
(dict) --
createTime (datetime) --
The time at which the ML input channel was created.
updateTime (datetime) --
The most recent time at which the ML input channel was updated.
membershipIdentifier (string) --
The membership ID of the membership that contains the ML input channel.
collaborationIdentifier (string) --
The collaboration ID of the collaboration that contains the ML input channel.
inputChannel (dict) --
The input channel that was used to create the ML input channel.
dataSource (dict) --
The data source that is used to create the ML input channel.
protectedQueryInputParameters (dict) --
Provides information necessary to perform the protected query.
sqlParameters (dict) --
The parameters for the SQL type Protected Query.
queryString (string) --
The query string to be submitted.
analysisTemplateArn (string) --
The Amazon Resource Name (ARN) associated with the analysis template within a collaboration.
parameters (dict) --
The protected query SQL parameters.
(string) --
(string) --
computeConfiguration (dict) --
Provides configuration information for the workers that will perform the protected query.
worker (dict) --
The worker instances that will perform the compute work.
type (string) --
The instance type of the compute workers that are used.
number (integer) --
The number of compute workers that are used.
roleArn (string) --
The ARN of the IAM role that Clean Rooms ML can assume to read the data referred to in the dataSource field the input channel.
Passing a role across AWS accounts is not allowed. If you pass a role that isn't in your account, you get an AccessDeniedException error.
protectedQueryIdentifier (string) --
The ID of the protected query that was used to create the ML input channel.
mlInputChannelArn (string) --
The Amazon Resource Name (ARN) of the ML input channel.
name (string) --
The name of the ML input channel.
configuredModelAlgorithmAssociations (list) --
The configured model algorithm associations that were used to create the ML input channel.
(string) --
status (string) --
The status of the ML input channel.
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.
retentionInDays (integer) --
The number of days to keep the data in the ML input channel.
numberOfRecords (integer) --
The number of records in the ML input channel.
numberOfFiles (float) --
The number of files in the ML input channel.
sizeInGb (float) --
The size, in GB, of the ML input channel.
description (string) --
The description of the ML input channel.
kmsKeyArn (string) --
The Amazon Resource Name (ARN) of the KMS key that was used to create the ML input channel.
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) --
Returns a list of trained models.
See also: AWS API Documentation
Request Syntax
client.list_trained_models(
nextToken='string',
maxResults=123,
membershipIdentifier='string'
)
string
The token value retrieved from a previous call to access the next page of results.
integer
The maximum size of the results that is returned per call.
string
[REQUIRED]
The membership ID of the member that created the trained models you are interested in.
dict
Response Syntax
{
'nextToken': 'string',
'trainedModels': [
{
'createTime': datetime(2015, 1, 1),
'updateTime': datetime(2015, 1, 1),
'trainedModelArn': '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.
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.