CleanRoomsMLClient#
Index > CleanRoomsML > CleanRoomsMLClient
Auto-generated documentation for CleanRoomsML type annotations stubs module mypy-boto3-cleanroomsml.
CleanRoomsMLClient#
Type annotations and code completion for boto3.client("cleanroomsml")
.
boto3 documentation
# CleanRoomsMLClient usage example
from boto3.session import Session
from mypy_boto3_cleanroomsml.client import CleanRoomsMLClient
def get_cleanroomsml_client() -> CleanRoomsMLClient:
return Session().client("cleanroomsml")
Exceptions#
boto3
client exceptions are generated in runtime.
This class provides code completion for boto3.client("cleanroomsml").exceptions
structure.
# Exceptions.exceptions usage example
client = boto3.client("cleanroomsml")
try:
do_something(client)
except (
client.exceptions.AccessDeniedException,
client.exceptions.ClientError,
client.exceptions.ConflictException,
client.exceptions.ResourceNotFoundException,
client.exceptions.ServiceQuotaExceededException,
client.exceptions.ValidationException,
) as e:
print(e)
# Exceptions.exceptions type checking example
from mypy_boto3_cleanroomsml.client import Exceptions
def handle_error(exc: Exceptions.AccessDeniedException) -> None:
...
Methods#
can_paginate#
Type annotations and code completion for boto3.client("cleanroomsml").can_paginate
method.
boto3 documentation
# can_paginate method definition
def can_paginate(
self,
operation_name: str,
) -> bool:
...
generate_presigned_url#
Type annotations and code completion for boto3.client("cleanroomsml").generate_presigned_url
method.
boto3 documentation
# generate_presigned_url method definition
def generate_presigned_url(
self,
ClientMethod: str,
Params: Mapping[str, Any] = ...,
ExpiresIn: int = 3600,
HttpMethod: str = ...,
) -> str:
...
cancel_trained_model#
Submits a request to cancel the trained model job.
Type annotations and code completion for boto3.client("cleanroomsml").cancel_trained_model
method.
boto3 documentation
# cancel_trained_model method definition
def cancel_trained_model(
self,
*,
membershipIdentifier: str,
trainedModelArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# cancel_trained_model method usage example with argument unpacking
kwargs: CancelTrainedModelRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"trainedModelArn": ...,
}
parent.cancel_trained_model(**kwargs)
cancel_trained_model_inference_job#
Submits a request to cancel a trained model inference job.
Type annotations and code completion for boto3.client("cleanroomsml").cancel_trained_model_inference_job
method.
boto3 documentation
# cancel_trained_model_inference_job method definition
def cancel_trained_model_inference_job(
self,
*,
membershipIdentifier: str,
trainedModelInferenceJobArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# cancel_trained_model_inference_job method usage example with argument unpacking
kwargs: CancelTrainedModelInferenceJobRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"trainedModelInferenceJobArn": ...,
}
parent.cancel_trained_model_inference_job(**kwargs)
create_audience_model#
Defines the information necessary to create an audience model.
Type annotations and code completion for boto3.client("cleanroomsml").create_audience_model
method.
boto3 documentation
# create_audience_model method definition
def create_audience_model(
self,
*,
name: str,
trainingDatasetArn: str,
trainingDataStartTime: TimestampTypeDef = ...,
trainingDataEndTime: TimestampTypeDef = ...,
kmsKeyArn: str = ...,
tags: Mapping[str, str] = ...,
description: str = ...,
) -> CreateAudienceModelResponseTypeDef: # (1)
...
# create_audience_model method usage example with argument unpacking
kwargs: CreateAudienceModelRequestRequestTypeDef = { # (1)
"name": ...,
"trainingDatasetArn": ...,
}
parent.create_audience_model(**kwargs)
create_configured_audience_model#
Defines the information necessary to create a configured audience model.
Type annotations and code completion for boto3.client("cleanroomsml").create_configured_audience_model
method.
boto3 documentation
# create_configured_audience_model method definition
def create_configured_audience_model(
self,
*,
name: str,
audienceModelArn: str,
outputConfig: ConfiguredAudienceModelOutputConfigTypeDef, # (1)
sharedAudienceMetrics: Sequence[SharedAudienceMetricsType], # (2)
description: str = ...,
minMatchingSeedSize: int = ...,
audienceSizeConfig: AudienceSizeConfigTypeDef = ..., # (3)
tags: Mapping[str, str] = ...,
childResourceTagOnCreatePolicy: TagOnCreatePolicyType = ..., # (4)
) -> CreateConfiguredAudienceModelResponseTypeDef: # (5)
...
- See ConfiguredAudienceModelOutputConfigTypeDef
- See SharedAudienceMetricsType
- See AudienceSizeConfigTypeDef
- See TagOnCreatePolicyType
- See CreateConfiguredAudienceModelResponseTypeDef
# create_configured_audience_model method usage example with argument unpacking
kwargs: CreateConfiguredAudienceModelRequestRequestTypeDef = { # (1)
"name": ...,
"audienceModelArn": ...,
"outputConfig": ...,
"sharedAudienceMetrics": ...,
}
parent.create_configured_audience_model(**kwargs)
create_configured_model_algorithm#
Creates a configured model algorithm using a container image stored in an ECR repository.
Type annotations and code completion for boto3.client("cleanroomsml").create_configured_model_algorithm
method.
boto3 documentation
# create_configured_model_algorithm method definition
def create_configured_model_algorithm(
self,
*,
name: str,
roleArn: str,
description: str = ...,
trainingContainerConfig: ContainerConfigTypeDef = ..., # (1)
inferenceContainerConfig: InferenceContainerConfigTypeDef = ..., # (2)
tags: Mapping[str, str] = ...,
kmsKeyArn: str = ...,
) -> CreateConfiguredModelAlgorithmResponseTypeDef: # (3)
...
- See ContainerConfigTypeDef
- See InferenceContainerConfigTypeDef
- See CreateConfiguredModelAlgorithmResponseTypeDef
# create_configured_model_algorithm method usage example with argument unpacking
kwargs: CreateConfiguredModelAlgorithmRequestRequestTypeDef = { # (1)
"name": ...,
"roleArn": ...,
}
parent.create_configured_model_algorithm(**kwargs)
create_configured_model_algorithm_association#
Associates a configured model algorithm to a collaboration for use by any member of the collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").create_configured_model_algorithm_association
method.
boto3 documentation
# create_configured_model_algorithm_association method definition
def create_configured_model_algorithm_association(
self,
*,
membershipIdentifier: str,
configuredModelAlgorithmArn: str,
name: str,
description: str = ...,
privacyConfiguration: PrivacyConfigurationTypeDef = ..., # (1)
tags: Mapping[str, str] = ...,
) -> CreateConfiguredModelAlgorithmAssociationResponseTypeDef: # (2)
...
# create_configured_model_algorithm_association method usage example with argument unpacking
kwargs: CreateConfiguredModelAlgorithmAssociationRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"configuredModelAlgorithmArn": ...,
"name": ...,
}
parent.create_configured_model_algorithm_association(**kwargs)
create_ml_input_channel#
Provides the information to create an ML input channel.
Type annotations and code completion for boto3.client("cleanroomsml").create_ml_input_channel
method.
boto3 documentation
# create_ml_input_channel method definition
def create_ml_input_channel(
self,
*,
membershipIdentifier: str,
configuredModelAlgorithmAssociations: Sequence[str],
inputChannel: InputChannelTypeDef, # (1)
name: str,
retentionInDays: int,
description: str = ...,
kmsKeyArn: str = ...,
tags: Mapping[str, str] = ...,
) -> CreateMLInputChannelResponseTypeDef: # (2)
...
# create_ml_input_channel method usage example with argument unpacking
kwargs: CreateMLInputChannelRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"configuredModelAlgorithmAssociations": ...,
"inputChannel": ...,
"name": ...,
"retentionInDays": ...,
}
parent.create_ml_input_channel(**kwargs)
create_trained_model#
Creates a trained model from an associated configured model algorithm using data from any member of the collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").create_trained_model
method.
boto3 documentation
# create_trained_model method definition
def create_trained_model(
self,
*,
membershipIdentifier: str,
name: str,
configuredModelAlgorithmAssociationArn: str,
resourceConfig: ResourceConfigTypeDef, # (1)
dataChannels: Sequence[ModelTrainingDataChannelTypeDef], # (2)
hyperparameters: Mapping[str, str] = ...,
environment: Mapping[str, str] = ...,
stoppingCondition: StoppingConditionTypeDef = ..., # (3)
description: str = ...,
kmsKeyArn: str = ...,
tags: Mapping[str, str] = ...,
) -> CreateTrainedModelResponseTypeDef: # (4)
...
- See ResourceConfigTypeDef
- See ModelTrainingDataChannelTypeDef
- See StoppingConditionTypeDef
- See CreateTrainedModelResponseTypeDef
# create_trained_model method usage example with argument unpacking
kwargs: CreateTrainedModelRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"name": ...,
"configuredModelAlgorithmAssociationArn": ...,
"resourceConfig": ...,
"dataChannels": ...,
}
parent.create_trained_model(**kwargs)
create_training_dataset#
Defines the information necessary to create a training dataset.
Type annotations and code completion for boto3.client("cleanroomsml").create_training_dataset
method.
boto3 documentation
# create_training_dataset method definition
def create_training_dataset(
self,
*,
name: str,
roleArn: str,
trainingData: Sequence[DatasetUnionTypeDef], # (1)
tags: Mapping[str, str] = ...,
description: str = ...,
) -> CreateTrainingDatasetResponseTypeDef: # (2)
...
# create_training_dataset method usage example with argument unpacking
kwargs: CreateTrainingDatasetRequestRequestTypeDef = { # (1)
"name": ...,
"roleArn": ...,
"trainingData": ...,
}
parent.create_training_dataset(**kwargs)
delete_audience_generation_job#
Deletes the specified audience generation job, and removes all data associated with the job.
Type annotations and code completion for boto3.client("cleanroomsml").delete_audience_generation_job
method.
boto3 documentation
# delete_audience_generation_job method definition
def delete_audience_generation_job(
self,
*,
audienceGenerationJobArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_audience_generation_job method usage example with argument unpacking
kwargs: DeleteAudienceGenerationJobRequestRequestTypeDef = { # (1)
"audienceGenerationJobArn": ...,
}
parent.delete_audience_generation_job(**kwargs)
delete_audience_model#
Specifies an audience model that you want to delete.
Type annotations and code completion for boto3.client("cleanroomsml").delete_audience_model
method.
boto3 documentation
# delete_audience_model method definition
def delete_audience_model(
self,
*,
audienceModelArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_audience_model method usage example with argument unpacking
kwargs: DeleteAudienceModelRequestRequestTypeDef = { # (1)
"audienceModelArn": ...,
}
parent.delete_audience_model(**kwargs)
delete_configured_audience_model#
Deletes the specified configured audience model.
Type annotations and code completion for boto3.client("cleanroomsml").delete_configured_audience_model
method.
boto3 documentation
# delete_configured_audience_model method definition
def delete_configured_audience_model(
self,
*,
configuredAudienceModelArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_configured_audience_model method usage example with argument unpacking
kwargs: DeleteConfiguredAudienceModelRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
}
parent.delete_configured_audience_model(**kwargs)
delete_configured_audience_model_policy#
Deletes the specified configured audience model policy.
Type annotations and code completion for boto3.client("cleanroomsml").delete_configured_audience_model_policy
method.
boto3 documentation
# delete_configured_audience_model_policy method definition
def delete_configured_audience_model_policy(
self,
*,
configuredAudienceModelArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_configured_audience_model_policy method usage example with argument unpacking
kwargs: DeleteConfiguredAudienceModelPolicyRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
}
parent.delete_configured_audience_model_policy(**kwargs)
delete_configured_model_algorithm#
Deletes a configured model algorithm.
Type annotations and code completion for boto3.client("cleanroomsml").delete_configured_model_algorithm
method.
boto3 documentation
# delete_configured_model_algorithm method definition
def delete_configured_model_algorithm(
self,
*,
configuredModelAlgorithmArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_configured_model_algorithm method usage example with argument unpacking
kwargs: DeleteConfiguredModelAlgorithmRequestRequestTypeDef = { # (1)
"configuredModelAlgorithmArn": ...,
}
parent.delete_configured_model_algorithm(**kwargs)
delete_configured_model_algorithm_association#
Deletes a configured model algorithm association.
Type annotations and code completion for boto3.client("cleanroomsml").delete_configured_model_algorithm_association
method.
boto3 documentation
# delete_configured_model_algorithm_association method definition
def delete_configured_model_algorithm_association(
self,
*,
configuredModelAlgorithmAssociationArn: str,
membershipIdentifier: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_configured_model_algorithm_association method usage example with argument unpacking
kwargs: DeleteConfiguredModelAlgorithmAssociationRequestRequestTypeDef = { # (1)
"configuredModelAlgorithmAssociationArn": ...,
"membershipIdentifier": ...,
}
parent.delete_configured_model_algorithm_association(**kwargs)
delete_ml_configuration#
Deletes a ML modeling configuration.
Type annotations and code completion for boto3.client("cleanroomsml").delete_ml_configuration
method.
boto3 documentation
# delete_ml_configuration method definition
def delete_ml_configuration(
self,
*,
membershipIdentifier: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_ml_configuration method usage example with argument unpacking
kwargs: DeleteMLConfigurationRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.delete_ml_configuration(**kwargs)
delete_ml_input_channel_data#
Provides the information necessary to delete an ML input channel.
Type annotations and code completion for boto3.client("cleanroomsml").delete_ml_input_channel_data
method.
boto3 documentation
# delete_ml_input_channel_data method definition
def delete_ml_input_channel_data(
self,
*,
mlInputChannelArn: str,
membershipIdentifier: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_ml_input_channel_data method usage example with argument unpacking
kwargs: DeleteMLInputChannelDataRequestRequestTypeDef = { # (1)
"mlInputChannelArn": ...,
"membershipIdentifier": ...,
}
parent.delete_ml_input_channel_data(**kwargs)
delete_trained_model_output#
Deletes the output of a trained model.
Type annotations and code completion for boto3.client("cleanroomsml").delete_trained_model_output
method.
boto3 documentation
# delete_trained_model_output method definition
def delete_trained_model_output(
self,
*,
trainedModelArn: str,
membershipIdentifier: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_trained_model_output method usage example with argument unpacking
kwargs: DeleteTrainedModelOutputRequestRequestTypeDef = { # (1)
"trainedModelArn": ...,
"membershipIdentifier": ...,
}
parent.delete_trained_model_output(**kwargs)
delete_training_dataset#
Specifies a training dataset that you want to delete.
Type annotations and code completion for boto3.client("cleanroomsml").delete_training_dataset
method.
boto3 documentation
# delete_training_dataset method definition
def delete_training_dataset(
self,
*,
trainingDatasetArn: str,
) -> EmptyResponseMetadataTypeDef: # (1)
...
# delete_training_dataset method usage example with argument unpacking
kwargs: DeleteTrainingDatasetRequestRequestTypeDef = { # (1)
"trainingDatasetArn": ...,
}
parent.delete_training_dataset(**kwargs)
get_audience_generation_job#
Returns information about an audience generation job.
Type annotations and code completion for boto3.client("cleanroomsml").get_audience_generation_job
method.
boto3 documentation
# get_audience_generation_job method definition
def get_audience_generation_job(
self,
*,
audienceGenerationJobArn: str,
) -> GetAudienceGenerationJobResponseTypeDef: # (1)
...
# get_audience_generation_job method usage example with argument unpacking
kwargs: GetAudienceGenerationJobRequestRequestTypeDef = { # (1)
"audienceGenerationJobArn": ...,
}
parent.get_audience_generation_job(**kwargs)
get_audience_model#
Returns information about an audience model.
Type annotations and code completion for boto3.client("cleanroomsml").get_audience_model
method.
boto3 documentation
# get_audience_model method definition
def get_audience_model(
self,
*,
audienceModelArn: str,
) -> GetAudienceModelResponseTypeDef: # (1)
...
# get_audience_model method usage example with argument unpacking
kwargs: GetAudienceModelRequestRequestTypeDef = { # (1)
"audienceModelArn": ...,
}
parent.get_audience_model(**kwargs)
get_collaboration_configured_model_algorithm_association#
Returns information about the configured model algorithm association in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").get_collaboration_configured_model_algorithm_association
method.
boto3 documentation
# get_collaboration_configured_model_algorithm_association method definition
def get_collaboration_configured_model_algorithm_association(
self,
*,
configuredModelAlgorithmAssociationArn: str,
collaborationIdentifier: str,
) -> GetCollaborationConfiguredModelAlgorithmAssociationResponseTypeDef: # (1)
...
# get_collaboration_configured_model_algorithm_association method usage example with argument unpacking
kwargs: GetCollaborationConfiguredModelAlgorithmAssociationRequestRequestTypeDef = { # (1)
"configuredModelAlgorithmAssociationArn": ...,
"collaborationIdentifier": ...,
}
parent.get_collaboration_configured_model_algorithm_association(**kwargs)
get_collaboration_ml_input_channel#
Returns information about a specific ML input channel in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").get_collaboration_ml_input_channel
method.
boto3 documentation
# get_collaboration_ml_input_channel method definition
def get_collaboration_ml_input_channel(
self,
*,
mlInputChannelArn: str,
collaborationIdentifier: str,
) -> GetCollaborationMLInputChannelResponseTypeDef: # (1)
...
# get_collaboration_ml_input_channel method usage example with argument unpacking
kwargs: GetCollaborationMLInputChannelRequestRequestTypeDef = { # (1)
"mlInputChannelArn": ...,
"collaborationIdentifier": ...,
}
parent.get_collaboration_ml_input_channel(**kwargs)
get_collaboration_trained_model#
Returns information about a trained model in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").get_collaboration_trained_model
method.
boto3 documentation
# get_collaboration_trained_model method definition
def get_collaboration_trained_model(
self,
*,
trainedModelArn: str,
collaborationIdentifier: str,
) -> GetCollaborationTrainedModelResponseTypeDef: # (1)
...
# get_collaboration_trained_model method usage example with argument unpacking
kwargs: GetCollaborationTrainedModelRequestRequestTypeDef = { # (1)
"trainedModelArn": ...,
"collaborationIdentifier": ...,
}
parent.get_collaboration_trained_model(**kwargs)
get_configured_audience_model#
Returns information about a specified configured audience model.
Type annotations and code completion for boto3.client("cleanroomsml").get_configured_audience_model
method.
boto3 documentation
# get_configured_audience_model method definition
def get_configured_audience_model(
self,
*,
configuredAudienceModelArn: str,
) -> GetConfiguredAudienceModelResponseTypeDef: # (1)
...
# get_configured_audience_model method usage example with argument unpacking
kwargs: GetConfiguredAudienceModelRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
}
parent.get_configured_audience_model(**kwargs)
get_configured_audience_model_policy#
Returns information about a configured audience model policy.
Type annotations and code completion for boto3.client("cleanroomsml").get_configured_audience_model_policy
method.
boto3 documentation
# get_configured_audience_model_policy method definition
def get_configured_audience_model_policy(
self,
*,
configuredAudienceModelArn: str,
) -> GetConfiguredAudienceModelPolicyResponseTypeDef: # (1)
...
# get_configured_audience_model_policy method usage example with argument unpacking
kwargs: GetConfiguredAudienceModelPolicyRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
}
parent.get_configured_audience_model_policy(**kwargs)
get_configured_model_algorithm#
Returns information about a configured model algorithm.
Type annotations and code completion for boto3.client("cleanroomsml").get_configured_model_algorithm
method.
boto3 documentation
# get_configured_model_algorithm method definition
def get_configured_model_algorithm(
self,
*,
configuredModelAlgorithmArn: str,
) -> GetConfiguredModelAlgorithmResponseTypeDef: # (1)
...
# get_configured_model_algorithm method usage example with argument unpacking
kwargs: GetConfiguredModelAlgorithmRequestRequestTypeDef = { # (1)
"configuredModelAlgorithmArn": ...,
}
parent.get_configured_model_algorithm(**kwargs)
get_configured_model_algorithm_association#
Returns information about a configured model algorithm association.
Type annotations and code completion for boto3.client("cleanroomsml").get_configured_model_algorithm_association
method.
boto3 documentation
# get_configured_model_algorithm_association method definition
def get_configured_model_algorithm_association(
self,
*,
configuredModelAlgorithmAssociationArn: str,
membershipIdentifier: str,
) -> GetConfiguredModelAlgorithmAssociationResponseTypeDef: # (1)
...
# get_configured_model_algorithm_association method usage example with argument unpacking
kwargs: GetConfiguredModelAlgorithmAssociationRequestRequestTypeDef = { # (1)
"configuredModelAlgorithmAssociationArn": ...,
"membershipIdentifier": ...,
}
parent.get_configured_model_algorithm_association(**kwargs)
get_ml_configuration#
Returns information about a specific ML configuration.
Type annotations and code completion for boto3.client("cleanroomsml").get_ml_configuration
method.
boto3 documentation
# get_ml_configuration method definition
def get_ml_configuration(
self,
*,
membershipIdentifier: str,
) -> GetMLConfigurationResponseTypeDef: # (1)
...
# get_ml_configuration method usage example with argument unpacking
kwargs: GetMLConfigurationRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.get_ml_configuration(**kwargs)
get_ml_input_channel#
Returns information about an ML input channel.
Type annotations and code completion for boto3.client("cleanroomsml").get_ml_input_channel
method.
boto3 documentation
# get_ml_input_channel method definition
def get_ml_input_channel(
self,
*,
mlInputChannelArn: str,
membershipIdentifier: str,
) -> GetMLInputChannelResponseTypeDef: # (1)
...
# get_ml_input_channel method usage example with argument unpacking
kwargs: GetMLInputChannelRequestRequestTypeDef = { # (1)
"mlInputChannelArn": ...,
"membershipIdentifier": ...,
}
parent.get_ml_input_channel(**kwargs)
get_trained_model#
Returns information about a trained model.
Type annotations and code completion for boto3.client("cleanroomsml").get_trained_model
method.
boto3 documentation
# get_trained_model method definition
def get_trained_model(
self,
*,
trainedModelArn: str,
membershipIdentifier: str,
) -> GetTrainedModelResponseTypeDef: # (1)
...
# get_trained_model method usage example with argument unpacking
kwargs: GetTrainedModelRequestRequestTypeDef = { # (1)
"trainedModelArn": ...,
"membershipIdentifier": ...,
}
parent.get_trained_model(**kwargs)
get_trained_model_inference_job#
Returns information about a trained model inference job.
Type annotations and code completion for boto3.client("cleanroomsml").get_trained_model_inference_job
method.
boto3 documentation
# get_trained_model_inference_job method definition
def get_trained_model_inference_job(
self,
*,
membershipIdentifier: str,
trainedModelInferenceJobArn: str,
) -> GetTrainedModelInferenceJobResponseTypeDef: # (1)
...
# get_trained_model_inference_job method usage example with argument unpacking
kwargs: GetTrainedModelInferenceJobRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"trainedModelInferenceJobArn": ...,
}
parent.get_trained_model_inference_job(**kwargs)
get_training_dataset#
Returns information about a training dataset.
Type annotations and code completion for boto3.client("cleanroomsml").get_training_dataset
method.
boto3 documentation
# get_training_dataset method definition
def get_training_dataset(
self,
*,
trainingDatasetArn: str,
) -> GetTrainingDatasetResponseTypeDef: # (1)
...
# get_training_dataset method usage example with argument unpacking
kwargs: GetTrainingDatasetRequestRequestTypeDef = { # (1)
"trainingDatasetArn": ...,
}
parent.get_training_dataset(**kwargs)
list_audience_export_jobs#
Returns a list of the audience export jobs.
Type annotations and code completion for boto3.client("cleanroomsml").list_audience_export_jobs
method.
boto3 documentation
# list_audience_export_jobs method definition
def list_audience_export_jobs(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
audienceGenerationJobArn: str = ...,
) -> ListAudienceExportJobsResponseTypeDef: # (1)
...
# list_audience_export_jobs method usage example with argument unpacking
kwargs: ListAudienceExportJobsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_audience_export_jobs(**kwargs)
list_audience_generation_jobs#
Returns a list of audience generation jobs.
Type annotations and code completion for boto3.client("cleanroomsml").list_audience_generation_jobs
method.
boto3 documentation
# list_audience_generation_jobs method definition
def list_audience_generation_jobs(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
configuredAudienceModelArn: str = ...,
collaborationId: str = ...,
) -> ListAudienceGenerationJobsResponseTypeDef: # (1)
...
# list_audience_generation_jobs method usage example with argument unpacking
kwargs: ListAudienceGenerationJobsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_audience_generation_jobs(**kwargs)
list_audience_models#
Returns a list of audience models.
Type annotations and code completion for boto3.client("cleanroomsml").list_audience_models
method.
boto3 documentation
# list_audience_models method definition
def list_audience_models(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
) -> ListAudienceModelsResponseTypeDef: # (1)
...
# list_audience_models method usage example with argument unpacking
kwargs: ListAudienceModelsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_audience_models(**kwargs)
list_collaboration_configured_model_algorithm_associations#
Returns a list of the configured model algorithm associations in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").list_collaboration_configured_model_algorithm_associations
method.
boto3 documentation
# list_collaboration_configured_model_algorithm_associations method definition
def list_collaboration_configured_model_algorithm_associations(
self,
*,
collaborationIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListCollaborationConfiguredModelAlgorithmAssociationsResponseTypeDef: # (1)
...
# list_collaboration_configured_model_algorithm_associations method usage example with argument unpacking
kwargs: ListCollaborationConfiguredModelAlgorithmAssociationsRequestRequestTypeDef = { # (1)
"collaborationIdentifier": ...,
}
parent.list_collaboration_configured_model_algorithm_associations(**kwargs)
list_collaboration_ml_input_channels#
Returns a list of the ML input channels in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").list_collaboration_ml_input_channels
method.
boto3 documentation
# list_collaboration_ml_input_channels method definition
def list_collaboration_ml_input_channels(
self,
*,
collaborationIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListCollaborationMLInputChannelsResponseTypeDef: # (1)
...
# list_collaboration_ml_input_channels method usage example with argument unpacking
kwargs: ListCollaborationMLInputChannelsRequestRequestTypeDef = { # (1)
"collaborationIdentifier": ...,
}
parent.list_collaboration_ml_input_channels(**kwargs)
list_collaboration_trained_model_export_jobs#
Returns a list of the export jobs for a trained model in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").list_collaboration_trained_model_export_jobs
method.
boto3 documentation
# list_collaboration_trained_model_export_jobs method definition
def list_collaboration_trained_model_export_jobs(
self,
*,
collaborationIdentifier: str,
trainedModelArn: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListCollaborationTrainedModelExportJobsResponseTypeDef: # (1)
...
# list_collaboration_trained_model_export_jobs method usage example with argument unpacking
kwargs: ListCollaborationTrainedModelExportJobsRequestRequestTypeDef = { # (1)
"collaborationIdentifier": ...,
"trainedModelArn": ...,
}
parent.list_collaboration_trained_model_export_jobs(**kwargs)
list_collaboration_trained_model_inference_jobs#
Returns a list of trained model inference jobs in a specified collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").list_collaboration_trained_model_inference_jobs
method.
boto3 documentation
# list_collaboration_trained_model_inference_jobs method definition
def list_collaboration_trained_model_inference_jobs(
self,
*,
collaborationIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
trainedModelArn: str = ...,
) -> ListCollaborationTrainedModelInferenceJobsResponseTypeDef: # (1)
...
# list_collaboration_trained_model_inference_jobs method usage example with argument unpacking
kwargs: ListCollaborationTrainedModelInferenceJobsRequestRequestTypeDef = { # (1)
"collaborationIdentifier": ...,
}
parent.list_collaboration_trained_model_inference_jobs(**kwargs)
list_collaboration_trained_models#
Returns a list of the trained models in a collaboration.
Type annotations and code completion for boto3.client("cleanroomsml").list_collaboration_trained_models
method.
boto3 documentation
# list_collaboration_trained_models method definition
def list_collaboration_trained_models(
self,
*,
collaborationIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListCollaborationTrainedModelsResponseTypeDef: # (1)
...
# list_collaboration_trained_models method usage example with argument unpacking
kwargs: ListCollaborationTrainedModelsRequestRequestTypeDef = { # (1)
"collaborationIdentifier": ...,
}
parent.list_collaboration_trained_models(**kwargs)
list_configured_audience_models#
Returns a list of the configured audience models.
Type annotations and code completion for boto3.client("cleanroomsml").list_configured_audience_models
method.
boto3 documentation
# list_configured_audience_models method definition
def list_configured_audience_models(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
) -> ListConfiguredAudienceModelsResponseTypeDef: # (1)
...
# list_configured_audience_models method usage example with argument unpacking
kwargs: ListConfiguredAudienceModelsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_configured_audience_models(**kwargs)
list_configured_model_algorithm_associations#
Returns a list of configured model algorithm associations.
Type annotations and code completion for boto3.client("cleanroomsml").list_configured_model_algorithm_associations
method.
boto3 documentation
# list_configured_model_algorithm_associations method definition
def list_configured_model_algorithm_associations(
self,
*,
membershipIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListConfiguredModelAlgorithmAssociationsResponseTypeDef: # (1)
...
# list_configured_model_algorithm_associations method usage example with argument unpacking
kwargs: ListConfiguredModelAlgorithmAssociationsRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.list_configured_model_algorithm_associations(**kwargs)
list_configured_model_algorithms#
Returns a list of configured model algorithms.
Type annotations and code completion for boto3.client("cleanroomsml").list_configured_model_algorithms
method.
boto3 documentation
# list_configured_model_algorithms method definition
def list_configured_model_algorithms(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
) -> ListConfiguredModelAlgorithmsResponseTypeDef: # (1)
...
# list_configured_model_algorithms method usage example with argument unpacking
kwargs: ListConfiguredModelAlgorithmsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_configured_model_algorithms(**kwargs)
list_ml_input_channels#
Returns a list of ML input channels.
Type annotations and code completion for boto3.client("cleanroomsml").list_ml_input_channels
method.
boto3 documentation
# list_ml_input_channels method definition
def list_ml_input_channels(
self,
*,
membershipIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListMLInputChannelsResponseTypeDef: # (1)
...
# list_ml_input_channels method usage example with argument unpacking
kwargs: ListMLInputChannelsRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.list_ml_input_channels(**kwargs)
list_tags_for_resource#
Returns a list of tags for a provided resource.
Type annotations and code completion for boto3.client("cleanroomsml").list_tags_for_resource
method.
boto3 documentation
# list_tags_for_resource method definition
def list_tags_for_resource(
self,
*,
resourceArn: str,
) -> ListTagsForResourceResponseTypeDef: # (1)
...
# list_tags_for_resource method usage example with argument unpacking
kwargs: ListTagsForResourceRequestRequestTypeDef = { # (1)
"resourceArn": ...,
}
parent.list_tags_for_resource(**kwargs)
list_trained_model_inference_jobs#
Returns a list of trained model inference jobs that match the request parameters.
Type annotations and code completion for boto3.client("cleanroomsml").list_trained_model_inference_jobs
method.
boto3 documentation
# list_trained_model_inference_jobs method definition
def list_trained_model_inference_jobs(
self,
*,
membershipIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
trainedModelArn: str = ...,
) -> ListTrainedModelInferenceJobsResponseTypeDef: # (1)
...
# list_trained_model_inference_jobs method usage example with argument unpacking
kwargs: ListTrainedModelInferenceJobsRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.list_trained_model_inference_jobs(**kwargs)
list_trained_models#
Returns a list of trained models.
Type annotations and code completion for boto3.client("cleanroomsml").list_trained_models
method.
boto3 documentation
# list_trained_models method definition
def list_trained_models(
self,
*,
membershipIdentifier: str,
nextToken: str = ...,
maxResults: int = ...,
) -> ListTrainedModelsResponseTypeDef: # (1)
...
# list_trained_models method usage example with argument unpacking
kwargs: ListTrainedModelsRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
}
parent.list_trained_models(**kwargs)
list_training_datasets#
Returns a list of training datasets.
Type annotations and code completion for boto3.client("cleanroomsml").list_training_datasets
method.
boto3 documentation
# list_training_datasets method definition
def list_training_datasets(
self,
*,
nextToken: str = ...,
maxResults: int = ...,
) -> ListTrainingDatasetsResponseTypeDef: # (1)
...
# list_training_datasets method usage example with argument unpacking
kwargs: ListTrainingDatasetsRequestRequestTypeDef = { # (1)
"nextToken": ...,
}
parent.list_training_datasets(**kwargs)
put_configured_audience_model_policy#
Create or update the resource policy for a configured audience model.
Type annotations and code completion for boto3.client("cleanroomsml").put_configured_audience_model_policy
method.
boto3 documentation
# put_configured_audience_model_policy method definition
def put_configured_audience_model_policy(
self,
*,
configuredAudienceModelArn: str,
configuredAudienceModelPolicy: str,
previousPolicyHash: str = ...,
policyExistenceCondition: PolicyExistenceConditionType = ..., # (1)
) -> PutConfiguredAudienceModelPolicyResponseTypeDef: # (2)
...
# put_configured_audience_model_policy method usage example with argument unpacking
kwargs: PutConfiguredAudienceModelPolicyRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
"configuredAudienceModelPolicy": ...,
}
parent.put_configured_audience_model_policy(**kwargs)
put_ml_configuration#
Assigns information about an ML configuration.
Type annotations and code completion for boto3.client("cleanroomsml").put_ml_configuration
method.
boto3 documentation
# put_ml_configuration method definition
def put_ml_configuration(
self,
*,
membershipIdentifier: str,
defaultOutputLocation: MLOutputConfigurationTypeDef, # (1)
) -> EmptyResponseMetadataTypeDef: # (2)
...
# put_ml_configuration method usage example with argument unpacking
kwargs: PutMLConfigurationRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"defaultOutputLocation": ...,
}
parent.put_ml_configuration(**kwargs)
start_audience_export_job#
Export an audience of a specified size after you have generated an audience.
Type annotations and code completion for boto3.client("cleanroomsml").start_audience_export_job
method.
boto3 documentation
# start_audience_export_job method definition
def start_audience_export_job(
self,
*,
name: str,
audienceGenerationJobArn: str,
audienceSize: AudienceSizeTypeDef, # (1)
description: str = ...,
) -> EmptyResponseMetadataTypeDef: # (2)
...
# start_audience_export_job method usage example with argument unpacking
kwargs: StartAudienceExportJobRequestRequestTypeDef = { # (1)
"name": ...,
"audienceGenerationJobArn": ...,
"audienceSize": ...,
}
parent.start_audience_export_job(**kwargs)
start_audience_generation_job#
Information necessary to start the audience generation job.
Type annotations and code completion for boto3.client("cleanroomsml").start_audience_generation_job
method.
boto3 documentation
# start_audience_generation_job method definition
def start_audience_generation_job(
self,
*,
name: str,
configuredAudienceModelArn: str,
seedAudience: AudienceGenerationJobDataSourceTypeDef, # (1)
includeSeedInOutput: bool = ...,
collaborationId: str = ...,
description: str = ...,
tags: Mapping[str, str] = ...,
) -> StartAudienceGenerationJobResponseTypeDef: # (2)
...
# start_audience_generation_job method usage example with argument unpacking
kwargs: StartAudienceGenerationJobRequestRequestTypeDef = { # (1)
"name": ...,
"configuredAudienceModelArn": ...,
"seedAudience": ...,
}
parent.start_audience_generation_job(**kwargs)
start_trained_model_export_job#
Provides the information necessary to start a trained model export job.
Type annotations and code completion for boto3.client("cleanroomsml").start_trained_model_export_job
method.
boto3 documentation
# start_trained_model_export_job method definition
def start_trained_model_export_job(
self,
*,
name: str,
trainedModelArn: str,
membershipIdentifier: str,
outputConfiguration: TrainedModelExportOutputConfigurationTypeDef, # (1)
description: str = ...,
) -> EmptyResponseMetadataTypeDef: # (2)
...
# start_trained_model_export_job method usage example with argument unpacking
kwargs: StartTrainedModelExportJobRequestRequestTypeDef = { # (1)
"name": ...,
"trainedModelArn": ...,
"membershipIdentifier": ...,
"outputConfiguration": ...,
}
parent.start_trained_model_export_job(**kwargs)
start_trained_model_inference_job#
Defines the information necessary to begin a trained model inference job.
Type annotations and code completion for boto3.client("cleanroomsml").start_trained_model_inference_job
method.
boto3 documentation
# start_trained_model_inference_job method definition
def start_trained_model_inference_job(
self,
*,
membershipIdentifier: str,
name: str,
trainedModelArn: str,
resourceConfig: InferenceResourceConfigTypeDef, # (1)
outputConfiguration: InferenceOutputConfigurationTypeDef, # (2)
dataSource: ModelInferenceDataSourceTypeDef, # (3)
configuredModelAlgorithmAssociationArn: str = ...,
description: str = ...,
containerExecutionParameters: InferenceContainerExecutionParametersTypeDef = ..., # (4)
environment: Mapping[str, str] = ...,
kmsKeyArn: str = ...,
tags: Mapping[str, str] = ...,
) -> StartTrainedModelInferenceJobResponseTypeDef: # (5)
...
- See InferenceResourceConfigTypeDef
- See InferenceOutputConfigurationTypeDef
- See ModelInferenceDataSourceTypeDef
- See InferenceContainerExecutionParametersTypeDef
- See StartTrainedModelInferenceJobResponseTypeDef
# start_trained_model_inference_job method usage example with argument unpacking
kwargs: StartTrainedModelInferenceJobRequestRequestTypeDef = { # (1)
"membershipIdentifier": ...,
"name": ...,
"trainedModelArn": ...,
"resourceConfig": ...,
"outputConfiguration": ...,
"dataSource": ...,
}
parent.start_trained_model_inference_job(**kwargs)
tag_resource#
Adds metadata tags to a specified resource.
Type annotations and code completion for boto3.client("cleanroomsml").tag_resource
method.
boto3 documentation
# tag_resource method definition
def tag_resource(
self,
*,
resourceArn: str,
tags: Mapping[str, str],
) -> dict[str, Any]:
...
# tag_resource method usage example with argument unpacking
kwargs: TagResourceRequestRequestTypeDef = { # (1)
"resourceArn": ...,
"tags": ...,
}
parent.tag_resource(**kwargs)
untag_resource#
Removes metadata tags from a specified resource.
Type annotations and code completion for boto3.client("cleanroomsml").untag_resource
method.
boto3 documentation
# untag_resource method definition
def untag_resource(
self,
*,
resourceArn: str,
tagKeys: Sequence[str],
) -> dict[str, Any]:
...
# untag_resource method usage example with argument unpacking
kwargs: UntagResourceRequestRequestTypeDef = { # (1)
"resourceArn": ...,
"tagKeys": ...,
}
parent.untag_resource(**kwargs)
update_configured_audience_model#
Provides the information necessary to update a configured audience model.
Type annotations and code completion for boto3.client("cleanroomsml").update_configured_audience_model
method.
boto3 documentation
# update_configured_audience_model method definition
def update_configured_audience_model(
self,
*,
configuredAudienceModelArn: str,
outputConfig: ConfiguredAudienceModelOutputConfigTypeDef = ..., # (1)
audienceModelArn: str = ...,
sharedAudienceMetrics: Sequence[SharedAudienceMetricsType] = ..., # (2)
minMatchingSeedSize: int = ...,
audienceSizeConfig: AudienceSizeConfigTypeDef = ..., # (3)
description: str = ...,
) -> UpdateConfiguredAudienceModelResponseTypeDef: # (4)
...
- See ConfiguredAudienceModelOutputConfigTypeDef
- See SharedAudienceMetricsType
- See AudienceSizeConfigTypeDef
- See UpdateConfiguredAudienceModelResponseTypeDef
# update_configured_audience_model method usage example with argument unpacking
kwargs: UpdateConfiguredAudienceModelRequestRequestTypeDef = { # (1)
"configuredAudienceModelArn": ...,
}
parent.update_configured_audience_model(**kwargs)
get_paginator#
Type annotations and code completion for boto3.client("cleanroomsml").get_paginator
method with overloads.
client.get_paginator("list_audience_export_jobs")
-> ListAudienceExportJobsPaginatorclient.get_paginator("list_audience_generation_jobs")
-> ListAudienceGenerationJobsPaginatorclient.get_paginator("list_audience_models")
-> ListAudienceModelsPaginatorclient.get_paginator("list_collaboration_configured_model_algorithm_associations")
-> ListCollaborationConfiguredModelAlgorithmAssociationsPaginatorclient.get_paginator("list_collaboration_ml_input_channels")
-> ListCollaborationMLInputChannelsPaginatorclient.get_paginator("list_collaboration_trained_model_export_jobs")
-> ListCollaborationTrainedModelExportJobsPaginatorclient.get_paginator("list_collaboration_trained_model_inference_jobs")
-> ListCollaborationTrainedModelInferenceJobsPaginatorclient.get_paginator("list_collaboration_trained_models")
-> ListCollaborationTrainedModelsPaginatorclient.get_paginator("list_configured_audience_models")
-> ListConfiguredAudienceModelsPaginatorclient.get_paginator("list_configured_model_algorithm_associations")
-> ListConfiguredModelAlgorithmAssociationsPaginatorclient.get_paginator("list_configured_model_algorithms")
-> ListConfiguredModelAlgorithmsPaginatorclient.get_paginator("list_ml_input_channels")
-> ListMLInputChannelsPaginatorclient.get_paginator("list_trained_model_inference_jobs")
-> ListTrainedModelInferenceJobsPaginatorclient.get_paginator("list_trained_models")
-> ListTrainedModelsPaginatorclient.get_paginator("list_training_datasets")
-> ListTrainingDatasetsPaginator