CleanRoomsMLClient

Index > CleanRoomsML > CleanRoomsMLClient

Auto-generated documentation for CleanRoomsML type annotations stubs module types-boto3-cleanroomsml.

CleanRoomsMLClient

Type annotations and code completion for boto3.client("cleanroomsml"). boto3 documentation

# CleanRoomsMLClient usage example

from boto3.session import Session
from types_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.InternalServiceException,
    client.exceptions.ResourceNotFoundException,
    client.exceptions.ServiceQuotaExceededException,
    client.exceptions.ThrottlingException,
    client.exceptions.ValidationException,
) as e:
    print(e)

# Exceptions.exceptions type checking example

from types_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,
    versionIdentifier: str = ...,
) -> EmptyResponseMetadataTypeDef:  # (1)
    ...

1. See EmptyResponseMetadataTypeDef

# cancel_trained_model method usage example with argument unpacking

kwargs: CancelTrainedModelRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "trainedModelArn": ...,
}

parent.cancel_trained_model(**kwargs)

1. See CancelTrainedModelRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# cancel_trained_model_inference_job method usage example with argument unpacking

kwargs: CancelTrainedModelInferenceJobRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "trainedModelInferenceJobArn": ...,
}

parent.cancel_trained_model_inference_job(**kwargs)

1. See CancelTrainedModelInferenceJobRequestTypeDef

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)
    ...

1. See CreateAudienceModelResponseTypeDef

# create_audience_model method usage example with argument unpacking

kwargs: CreateAudienceModelRequestTypeDef = {  # (1)
    "name": ...,
    "trainingDatasetArn": ...,
}

parent.create_audience_model(**kwargs)

1. See CreateAudienceModelRequestTypeDef

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: AudienceSizeConfigUnionTypeDef = ...,  # (3)
    tags: Mapping[str, str] = ...,
    childResourceTagOnCreatePolicy: TagOnCreatePolicyType = ...,  # (4)
) -> CreateConfiguredAudienceModelResponseTypeDef:  # (5)
    ...

1. See ConfiguredAudienceModelOutputConfigTypeDef
2. See Sequence[SharedAudienceMetricsType]
3. See AudienceSizeConfigUnionTypeDef
4. See TagOnCreatePolicyType
5. See CreateConfiguredAudienceModelResponseTypeDef

# create_configured_audience_model method usage example with argument unpacking

kwargs: CreateConfiguredAudienceModelRequestTypeDef = {  # (1)
    "name": ...,
    "audienceModelArn": ...,
    "outputConfig": ...,
    "sharedAudienceMetrics": ...,
}

parent.create_configured_audience_model(**kwargs)

1. See CreateConfiguredAudienceModelRequestTypeDef

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: ContainerConfigUnionTypeDef = ...,  # (1)
    inferenceContainerConfig: InferenceContainerConfigTypeDef = ...,  # (2)
    tags: Mapping[str, str] = ...,
    kmsKeyArn: str = ...,
) -> CreateConfiguredModelAlgorithmResponseTypeDef:  # (3)
    ...

1. See ContainerConfigUnionTypeDef
2. See InferenceContainerConfigTypeDef
3. See CreateConfiguredModelAlgorithmResponseTypeDef

# create_configured_model_algorithm method usage example with argument unpacking

kwargs: CreateConfiguredModelAlgorithmRequestTypeDef = {  # (1)
    "name": ...,
    "roleArn": ...,
}

parent.create_configured_model_algorithm(**kwargs)

1. See CreateConfiguredModelAlgorithmRequestTypeDef

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: PrivacyConfigurationUnionTypeDef = ...,  # (1)
    tags: Mapping[str, str] = ...,
) -> CreateConfiguredModelAlgorithmAssociationResponseTypeDef:  # (2)
    ...

1. See PrivacyConfigurationUnionTypeDef
2. See CreateConfiguredModelAlgorithmAssociationResponseTypeDef

# create_configured_model_algorithm_association method usage example with argument unpacking

kwargs: CreateConfiguredModelAlgorithmAssociationRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "configuredModelAlgorithmArn": ...,
    "name": ...,
}

parent.create_configured_model_algorithm_association(**kwargs)

1. See CreateConfiguredModelAlgorithmAssociationRequestTypeDef

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: InputChannelUnionTypeDef,  # (1)
    name: str,
    retentionInDays: int,
    description: str = ...,
    kmsKeyArn: str = ...,
    tags: Mapping[str, str] = ...,
) -> CreateMLInputChannelResponseTypeDef:  # (2)
    ...

1. See InputChannelUnionTypeDef
2. See CreateMLInputChannelResponseTypeDef

# create_ml_input_channel method usage example with argument unpacking

kwargs: CreateMLInputChannelRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "configuredModelAlgorithmAssociations": ...,
    "inputChannel": ...,
    "name": ...,
    "retentionInDays": ...,
}

parent.create_ml_input_channel(**kwargs)

1. See CreateMLInputChannelRequestTypeDef

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)
    incrementalTrainingDataChannels: Sequence[IncrementalTrainingDataChannelTypeDef] = ...,  # (4)
    trainingInputMode: TrainingInputModeType = ...,  # (5)
    description: str = ...,
    kmsKeyArn: str = ...,
    tags: Mapping[str, str] = ...,
) -> CreateTrainedModelResponseTypeDef:  # (6)
    ...

1. See ResourceConfigTypeDef
2. See Sequence[ModelTrainingDataChannelTypeDef]
3. See StoppingConditionTypeDef
4. See Sequence[IncrementalTrainingDataChannelTypeDef]
5. See TrainingInputModeType
6. See CreateTrainedModelResponseTypeDef

# create_trained_model method usage example with argument unpacking

kwargs: CreateTrainedModelRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "name": ...,
    "configuredModelAlgorithmAssociationArn": ...,
    "resourceConfig": ...,
    "dataChannels": ...,
}

parent.create_trained_model(**kwargs)

1. See CreateTrainedModelRequestTypeDef

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)
    ...

1. See Sequence[DatasetUnionTypeDef]
2. See CreateTrainingDatasetResponseTypeDef

# create_training_dataset method usage example with argument unpacking

kwargs: CreateTrainingDatasetRequestTypeDef = {  # (1)
    "name": ...,
    "roleArn": ...,
    "trainingData": ...,
}

parent.create_training_dataset(**kwargs)

1. See CreateTrainingDatasetRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_audience_generation_job method usage example with argument unpacking

kwargs: DeleteAudienceGenerationJobRequestTypeDef = {  # (1)
    "audienceGenerationJobArn": ...,
}

parent.delete_audience_generation_job(**kwargs)

1. See DeleteAudienceGenerationJobRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_audience_model method usage example with argument unpacking

kwargs: DeleteAudienceModelRequestTypeDef = {  # (1)
    "audienceModelArn": ...,
}

parent.delete_audience_model(**kwargs)

1. See DeleteAudienceModelRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_configured_audience_model method usage example with argument unpacking

kwargs: DeleteConfiguredAudienceModelRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
}

parent.delete_configured_audience_model(**kwargs)

1. See DeleteConfiguredAudienceModelRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_configured_audience_model_policy method usage example with argument unpacking

kwargs: DeleteConfiguredAudienceModelPolicyRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
}

parent.delete_configured_audience_model_policy(**kwargs)

1. See DeleteConfiguredAudienceModelPolicyRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_configured_model_algorithm method usage example with argument unpacking

kwargs: DeleteConfiguredModelAlgorithmRequestTypeDef = {  # (1)
    "configuredModelAlgorithmArn": ...,
}

parent.delete_configured_model_algorithm(**kwargs)

1. See DeleteConfiguredModelAlgorithmRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_configured_model_algorithm_association method usage example with argument unpacking

kwargs: DeleteConfiguredModelAlgorithmAssociationRequestTypeDef = {  # (1)
    "configuredModelAlgorithmAssociationArn": ...,
    "membershipIdentifier": ...,
}

parent.delete_configured_model_algorithm_association(**kwargs)

1. See DeleteConfiguredModelAlgorithmAssociationRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_ml_configuration method usage example with argument unpacking

kwargs: DeleteMLConfigurationRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.delete_ml_configuration(**kwargs)

1. See DeleteMLConfigurationRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_ml_input_channel_data method usage example with argument unpacking

kwargs: DeleteMLInputChannelDataRequestTypeDef = {  # (1)
    "mlInputChannelArn": ...,
    "membershipIdentifier": ...,
}

parent.delete_ml_input_channel_data(**kwargs)

1. See DeleteMLInputChannelDataRequestTypeDef

delete_trained_model_output

Deletes the model artifacts stored by the service.

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,
    versionIdentifier: str = ...,
) -> EmptyResponseMetadataTypeDef:  # (1)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_trained_model_output method usage example with argument unpacking

kwargs: DeleteTrainedModelOutputRequestTypeDef = {  # (1)
    "trainedModelArn": ...,
    "membershipIdentifier": ...,
}

parent.delete_trained_model_output(**kwargs)

1. See DeleteTrainedModelOutputRequestTypeDef

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)
    ...

1. See EmptyResponseMetadataTypeDef

# delete_training_dataset method usage example with argument unpacking

kwargs: DeleteTrainingDatasetRequestTypeDef = {  # (1)
    "trainingDatasetArn": ...,
}

parent.delete_training_dataset(**kwargs)

1. See DeleteTrainingDatasetRequestTypeDef

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)
    ...

1. See GetAudienceGenerationJobResponseTypeDef

# get_audience_generation_job method usage example with argument unpacking

kwargs: GetAudienceGenerationJobRequestTypeDef = {  # (1)
    "audienceGenerationJobArn": ...,
}

parent.get_audience_generation_job(**kwargs)

1. See GetAudienceGenerationJobRequestTypeDef

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)
    ...

1. See GetAudienceModelResponseTypeDef

# get_audience_model method usage example with argument unpacking

kwargs: GetAudienceModelRequestTypeDef = {  # (1)
    "audienceModelArn": ...,
}

parent.get_audience_model(**kwargs)

1. See GetAudienceModelRequestTypeDef

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)
    ...

1. See GetCollaborationConfiguredModelAlgorithmAssociationResponseTypeDef

# get_collaboration_configured_model_algorithm_association method usage example with argument unpacking

kwargs: GetCollaborationConfiguredModelAlgorithmAssociationRequestTypeDef = {  # (1)
    "configuredModelAlgorithmAssociationArn": ...,
    "collaborationIdentifier": ...,
}

parent.get_collaboration_configured_model_algorithm_association(**kwargs)

1. See GetCollaborationConfiguredModelAlgorithmAssociationRequestTypeDef

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)
    ...

1. See GetCollaborationMLInputChannelResponseTypeDef

# get_collaboration_ml_input_channel method usage example with argument unpacking

kwargs: GetCollaborationMLInputChannelRequestTypeDef = {  # (1)
    "mlInputChannelArn": ...,
    "collaborationIdentifier": ...,
}

parent.get_collaboration_ml_input_channel(**kwargs)

1. See GetCollaborationMLInputChannelRequestTypeDef

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,
    versionIdentifier: str = ...,
) -> GetCollaborationTrainedModelResponseTypeDef:  # (1)
    ...

1. See GetCollaborationTrainedModelResponseTypeDef

# get_collaboration_trained_model method usage example with argument unpacking

kwargs: GetCollaborationTrainedModelRequestTypeDef = {  # (1)
    "trainedModelArn": ...,
    "collaborationIdentifier": ...,
}

parent.get_collaboration_trained_model(**kwargs)

1. See GetCollaborationTrainedModelRequestTypeDef

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)
    ...

1. See GetConfiguredAudienceModelResponseTypeDef

# get_configured_audience_model method usage example with argument unpacking

kwargs: GetConfiguredAudienceModelRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
}

parent.get_configured_audience_model(**kwargs)

1. See GetConfiguredAudienceModelRequestTypeDef

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)
    ...

1. See GetConfiguredAudienceModelPolicyResponseTypeDef

# get_configured_audience_model_policy method usage example with argument unpacking

kwargs: GetConfiguredAudienceModelPolicyRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
}

parent.get_configured_audience_model_policy(**kwargs)

1. See GetConfiguredAudienceModelPolicyRequestTypeDef

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)
    ...

1. See GetConfiguredModelAlgorithmResponseTypeDef

# get_configured_model_algorithm method usage example with argument unpacking

kwargs: GetConfiguredModelAlgorithmRequestTypeDef = {  # (1)
    "configuredModelAlgorithmArn": ...,
}

parent.get_configured_model_algorithm(**kwargs)

1. See GetConfiguredModelAlgorithmRequestTypeDef

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)
    ...

1. See GetConfiguredModelAlgorithmAssociationResponseTypeDef

# get_configured_model_algorithm_association method usage example with argument unpacking

kwargs: GetConfiguredModelAlgorithmAssociationRequestTypeDef = {  # (1)
    "configuredModelAlgorithmAssociationArn": ...,
    "membershipIdentifier": ...,
}

parent.get_configured_model_algorithm_association(**kwargs)

1. See GetConfiguredModelAlgorithmAssociationRequestTypeDef

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)
    ...

1. See GetMLConfigurationResponseTypeDef

# get_ml_configuration method usage example with argument unpacking

kwargs: GetMLConfigurationRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.get_ml_configuration(**kwargs)

1. See GetMLConfigurationRequestTypeDef

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)
    ...

1. See GetMLInputChannelResponseTypeDef

# get_ml_input_channel method usage example with argument unpacking

kwargs: GetMLInputChannelRequestTypeDef = {  # (1)
    "mlInputChannelArn": ...,
    "membershipIdentifier": ...,
}

parent.get_ml_input_channel(**kwargs)

1. See GetMLInputChannelRequestTypeDef

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,
    versionIdentifier: str = ...,
) -> GetTrainedModelResponseTypeDef:  # (1)
    ...

1. See GetTrainedModelResponseTypeDef

# get_trained_model method usage example with argument unpacking

kwargs: GetTrainedModelRequestTypeDef = {  # (1)
    "trainedModelArn": ...,
    "membershipIdentifier": ...,
}

parent.get_trained_model(**kwargs)

1. See GetTrainedModelRequestTypeDef

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)
    ...

1. See GetTrainedModelInferenceJobResponseTypeDef

# get_trained_model_inference_job method usage example with argument unpacking

kwargs: GetTrainedModelInferenceJobRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "trainedModelInferenceJobArn": ...,
}

parent.get_trained_model_inference_job(**kwargs)

1. See GetTrainedModelInferenceJobRequestTypeDef

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)
    ...

1. See GetTrainingDatasetResponseTypeDef

# get_training_dataset method usage example with argument unpacking

kwargs: GetTrainingDatasetRequestTypeDef = {  # (1)
    "trainingDatasetArn": ...,
}

parent.get_training_dataset(**kwargs)

1. See GetTrainingDatasetRequestTypeDef

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)
    ...

1. See ListAudienceExportJobsResponseTypeDef

# list_audience_export_jobs method usage example with argument unpacking

kwargs: ListAudienceExportJobsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_audience_export_jobs(**kwargs)

1. See ListAudienceExportJobsRequestTypeDef

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)
    ...

1. See ListAudienceGenerationJobsResponseTypeDef

# list_audience_generation_jobs method usage example with argument unpacking

kwargs: ListAudienceGenerationJobsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_audience_generation_jobs(**kwargs)

1. See ListAudienceGenerationJobsRequestTypeDef

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)
    ...

1. See ListAudienceModelsResponseTypeDef

# list_audience_models method usage example with argument unpacking

kwargs: ListAudienceModelsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_audience_models(**kwargs)

1. See ListAudienceModelsRequestTypeDef

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)
    ...

1. See ListCollaborationConfiguredModelAlgorithmAssociationsResponseTypeDef

# list_collaboration_configured_model_algorithm_associations method usage example with argument unpacking

kwargs: ListCollaborationConfiguredModelAlgorithmAssociationsRequestTypeDef = {  # (1)
    "collaborationIdentifier": ...,
}

parent.list_collaboration_configured_model_algorithm_associations(**kwargs)

1. See ListCollaborationConfiguredModelAlgorithmAssociationsRequestTypeDef

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)
    ...

1. See ListCollaborationMLInputChannelsResponseTypeDef

# list_collaboration_ml_input_channels method usage example with argument unpacking

kwargs: ListCollaborationMLInputChannelsRequestTypeDef = {  # (1)
    "collaborationIdentifier": ...,
}

parent.list_collaboration_ml_input_channels(**kwargs)

1. See ListCollaborationMLInputChannelsRequestTypeDef

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 = ...,
    trainedModelVersionIdentifier: str = ...,
) -> ListCollaborationTrainedModelExportJobsResponseTypeDef:  # (1)
    ...

1. See ListCollaborationTrainedModelExportJobsResponseTypeDef

# list_collaboration_trained_model_export_jobs method usage example with argument unpacking

kwargs: ListCollaborationTrainedModelExportJobsRequestTypeDef = {  # (1)
    "collaborationIdentifier": ...,
    "trainedModelArn": ...,
}

parent.list_collaboration_trained_model_export_jobs(**kwargs)

1. See ListCollaborationTrainedModelExportJobsRequestTypeDef

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 = ...,
    trainedModelVersionIdentifier: str = ...,
) -> ListCollaborationTrainedModelInferenceJobsResponseTypeDef:  # (1)
    ...

1. See ListCollaborationTrainedModelInferenceJobsResponseTypeDef

# list_collaboration_trained_model_inference_jobs method usage example with argument unpacking

kwargs: ListCollaborationTrainedModelInferenceJobsRequestTypeDef = {  # (1)
    "collaborationIdentifier": ...,
}

parent.list_collaboration_trained_model_inference_jobs(**kwargs)

1. See ListCollaborationTrainedModelInferenceJobsRequestTypeDef

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)
    ...

1. See ListCollaborationTrainedModelsResponseTypeDef

# list_collaboration_trained_models method usage example with argument unpacking

kwargs: ListCollaborationTrainedModelsRequestTypeDef = {  # (1)
    "collaborationIdentifier": ...,
}

parent.list_collaboration_trained_models(**kwargs)

1. See ListCollaborationTrainedModelsRequestTypeDef

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)
    ...

1. See ListConfiguredAudienceModelsResponseTypeDef

# list_configured_audience_models method usage example with argument unpacking

kwargs: ListConfiguredAudienceModelsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_configured_audience_models(**kwargs)

1. See ListConfiguredAudienceModelsRequestTypeDef

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)
    ...

1. See ListConfiguredModelAlgorithmAssociationsResponseTypeDef

# list_configured_model_algorithm_associations method usage example with argument unpacking

kwargs: ListConfiguredModelAlgorithmAssociationsRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.list_configured_model_algorithm_associations(**kwargs)

1. See ListConfiguredModelAlgorithmAssociationsRequestTypeDef

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)
    ...

1. See ListConfiguredModelAlgorithmsResponseTypeDef

# list_configured_model_algorithms method usage example with argument unpacking

kwargs: ListConfiguredModelAlgorithmsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_configured_model_algorithms(**kwargs)

1. See ListConfiguredModelAlgorithmsRequestTypeDef

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)
    ...

1. See ListMLInputChannelsResponseTypeDef

# list_ml_input_channels method usage example with argument unpacking

kwargs: ListMLInputChannelsRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.list_ml_input_channels(**kwargs)

1. See ListMLInputChannelsRequestTypeDef

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)
    ...

1. See ListTagsForResourceResponseTypeDef

# list_tags_for_resource method usage example with argument unpacking

kwargs: ListTagsForResourceRequestTypeDef = {  # (1)
    "resourceArn": ...,
}

parent.list_tags_for_resource(**kwargs)

1. See ListTagsForResourceRequestTypeDef

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 = ...,
    trainedModelVersionIdentifier: str = ...,
) -> ListTrainedModelInferenceJobsResponseTypeDef:  # (1)
    ...

1. See ListTrainedModelInferenceJobsResponseTypeDef

# list_trained_model_inference_jobs method usage example with argument unpacking

kwargs: ListTrainedModelInferenceJobsRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.list_trained_model_inference_jobs(**kwargs)

1. See ListTrainedModelInferenceJobsRequestTypeDef

list_trained_model_versions

Returns a list of trained model versions for a specified trained model.

Type annotations and code completion for boto3.client("cleanroomsml").list_trained_model_versions method. boto3 documentation

# list_trained_model_versions method definition

def list_trained_model_versions(
    self,
    *,
    membershipIdentifier: str,
    trainedModelArn: str,
    nextToken: str = ...,
    maxResults: int = ...,
    status: TrainedModelStatusType = ...,  # (1)
) -> ListTrainedModelVersionsResponseTypeDef:  # (2)
    ...

1. See TrainedModelStatusType
2. See ListTrainedModelVersionsResponseTypeDef

# list_trained_model_versions method usage example with argument unpacking

kwargs: ListTrainedModelVersionsRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "trainedModelArn": ...,
}

parent.list_trained_model_versions(**kwargs)

1. See ListTrainedModelVersionsRequestTypeDef

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)
    ...

1. See ListTrainedModelsResponseTypeDef

# list_trained_models method usage example with argument unpacking

kwargs: ListTrainedModelsRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
}

parent.list_trained_models(**kwargs)

1. See ListTrainedModelsRequestTypeDef

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)
    ...

1. See ListTrainingDatasetsResponseTypeDef

# list_training_datasets method usage example with argument unpacking

kwargs: ListTrainingDatasetsRequestTypeDef = {  # (1)
    "nextToken": ...,
}

parent.list_training_datasets(**kwargs)

1. See ListTrainingDatasetsRequestTypeDef

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)
    ...

1. See PolicyExistenceConditionType
2. See PutConfiguredAudienceModelPolicyResponseTypeDef

# put_configured_audience_model_policy method usage example with argument unpacking

kwargs: PutConfiguredAudienceModelPolicyRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
    "configuredAudienceModelPolicy": ...,
}

parent.put_configured_audience_model_policy(**kwargs)

1. See PutConfiguredAudienceModelPolicyRequestTypeDef

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)
    ...

1. See MLOutputConfigurationTypeDef
2. See EmptyResponseMetadataTypeDef

# put_ml_configuration method usage example with argument unpacking

kwargs: PutMLConfigurationRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "defaultOutputLocation": ...,
}

parent.put_ml_configuration(**kwargs)

1. See PutMLConfigurationRequestTypeDef

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)
    ...

1. See AudienceSizeTypeDef
2. See EmptyResponseMetadataTypeDef

# start_audience_export_job method usage example with argument unpacking

kwargs: StartAudienceExportJobRequestTypeDef = {  # (1)
    "name": ...,
    "audienceGenerationJobArn": ...,
    "audienceSize": ...,
}

parent.start_audience_export_job(**kwargs)

1. See StartAudienceExportJobRequestTypeDef

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: AudienceGenerationJobDataSourceUnionTypeDef,  # (1)
    includeSeedInOutput: bool = ...,
    collaborationId: str = ...,
    description: str = ...,
    tags: Mapping[str, str] = ...,
) -> StartAudienceGenerationJobResponseTypeDef:  # (2)
    ...

1. See AudienceGenerationJobDataSourceUnionTypeDef
2. See StartAudienceGenerationJobResponseTypeDef

# start_audience_generation_job method usage example with argument unpacking

kwargs: StartAudienceGenerationJobRequestTypeDef = {  # (1)
    "name": ...,
    "configuredAudienceModelArn": ...,
    "seedAudience": ...,
}

parent.start_audience_generation_job(**kwargs)

1. See StartAudienceGenerationJobRequestTypeDef

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: TrainedModelExportOutputConfigurationUnionTypeDef,  # (1)
    trainedModelVersionIdentifier: str = ...,
    description: str = ...,
) -> EmptyResponseMetadataTypeDef:  # (2)
    ...

1. See TrainedModelExportOutputConfigurationUnionTypeDef
2. See EmptyResponseMetadataTypeDef

# start_trained_model_export_job method usage example with argument unpacking

kwargs: StartTrainedModelExportJobRequestTypeDef = {  # (1)
    "name": ...,
    "trainedModelArn": ...,
    "membershipIdentifier": ...,
    "outputConfiguration": ...,
}

parent.start_trained_model_export_job(**kwargs)

1. See StartTrainedModelExportJobRequestTypeDef

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: InferenceOutputConfigurationUnionTypeDef,  # (2)
    dataSource: ModelInferenceDataSourceTypeDef,  # (3)
    trainedModelVersionIdentifier: str = ...,
    configuredModelAlgorithmAssociationArn: str = ...,
    description: str = ...,
    containerExecutionParameters: InferenceContainerExecutionParametersTypeDef = ...,  # (4)
    environment: Mapping[str, str] = ...,
    kmsKeyArn: str = ...,
    tags: Mapping[str, str] = ...,
) -> StartTrainedModelInferenceJobResponseTypeDef:  # (5)
    ...

1. See InferenceResourceConfigTypeDef
2. See InferenceOutputConfigurationUnionTypeDef
3. See ModelInferenceDataSourceTypeDef
4. See InferenceContainerExecutionParametersTypeDef
5. See StartTrainedModelInferenceJobResponseTypeDef

# start_trained_model_inference_job method usage example with argument unpacking

kwargs: StartTrainedModelInferenceJobRequestTypeDef = {  # (1)
    "membershipIdentifier": ...,
    "name": ...,
    "trainedModelArn": ...,
    "resourceConfig": ...,
    "outputConfiguration": ...,
    "dataSource": ...,
}

parent.start_trained_model_inference_job(**kwargs)

1. See StartTrainedModelInferenceJobRequestTypeDef

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: TagResourceRequestTypeDef = {  # (1)
    "resourceArn": ...,
    "tags": ...,
}

parent.tag_resource(**kwargs)

1. See TagResourceRequestTypeDef

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: UntagResourceRequestTypeDef = {  # (1)
    "resourceArn": ...,
    "tagKeys": ...,
}

parent.untag_resource(**kwargs)

1. See UntagResourceRequestTypeDef

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: AudienceSizeConfigUnionTypeDef = ...,  # (3)
    description: str = ...,
) -> UpdateConfiguredAudienceModelResponseTypeDef:  # (4)
    ...

1. See ConfiguredAudienceModelOutputConfigTypeDef
2. See Sequence[SharedAudienceMetricsType]
3. See AudienceSizeConfigUnionTypeDef
4. See UpdateConfiguredAudienceModelResponseTypeDef

# update_configured_audience_model method usage example with argument unpacking

kwargs: UpdateConfiguredAudienceModelRequestTypeDef = {  # (1)
    "configuredAudienceModelArn": ...,
}

parent.update_configured_audience_model(**kwargs)

1. See UpdateConfiguredAudienceModelRequestTypeDef

get_paginator

Type annotations and code completion for boto3.client("cleanroomsml").get_paginator method with overloads.

• client.get_paginator("list_audience_export_jobs") -> ListAudienceExportJobsPaginator
• client.get_paginator("list_audience_generation_jobs") -> ListAudienceGenerationJobsPaginator
• client.get_paginator("list_audience_models") -> ListAudienceModelsPaginator
• client.get_paginator("list_collaboration_configured_model_algorithm_associations") -> ListCollaborationConfiguredModelAlgorithmAssociationsPaginator
• client.get_paginator("list_collaboration_ml_input_channels") -> ListCollaborationMLInputChannelsPaginator
• client.get_paginator("list_collaboration_trained_model_export_jobs") -> ListCollaborationTrainedModelExportJobsPaginator
• client.get_paginator("list_collaboration_trained_model_inference_jobs") -> ListCollaborationTrainedModelInferenceJobsPaginator
• client.get_paginator("list_collaboration_trained_models") -> ListCollaborationTrainedModelsPaginator
• client.get_paginator("list_configured_audience_models") -> ListConfiguredAudienceModelsPaginator
• client.get_paginator("list_configured_model_algorithm_associations") -> ListConfiguredModelAlgorithmAssociationsPaginator
• client.get_paginator("list_configured_model_algorithms") -> ListConfiguredModelAlgorithmsPaginator
• client.get_paginator("list_ml_input_channels") -> ListMLInputChannelsPaginator
• client.get_paginator("list_trained_model_inference_jobs") -> ListTrainedModelInferenceJobsPaginator
• client.get_paginator("list_trained_model_versions") -> ListTrainedModelVersionsPaginator
• client.get_paginator("list_trained_models") -> ListTrainedModelsPaginator
• client.get_paginator("list_training_datasets") -> ListTrainingDatasetsPaginator