Class DatasetServiceAsyncClient (1.13.0) 

DatasetServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.dataset_service.transports.base.DatasetServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

The service that handles the CRUD of Vertex AI Dataset and its child resources.

Inheritance

builtins.object > DatasetServiceAsyncClient

Properties

transport

Returns the transport used by the client instance.

Returns
TypeDescription
DatasetServiceTransportThe transport used by the client instance.

Methods

DatasetServiceAsyncClient

DatasetServiceAsyncClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.dataset_service.transports.base.DatasetServiceTransport] = 'grpc_asyncio', client_options: Optional[google.api_core.client_options.ClientOptions] = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates the dataset service client.

Parameters
NameDescription
credentials Optional[google.auth.credentials.Credentials]

The authorization credentials to attach to requests. These credentials identify the application to the service; if none are specified, the client will attempt to ascertain the credentials from the environment.

transport Union[str, `.DatasetServiceTransport`]

The transport to use. If set to None, a transport is chosen automatically.

client_options ClientOptions

Custom options for the client. It won't take effect if a transport instance is provided. (1) The api_endpoint property can be used to override the default endpoint provided by the client. GOOGLE_API_USE_MTLS_ENDPOINT environment variable can also be used to override the endpoint: "always" (always use the default mTLS endpoint), "never" (always use the default regular endpoint) and "auto" (auto switch to the default mTLS endpoint if client certificate is present, this is the default value). However, the api_endpoint property takes precedence if provided. (2) If GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "true", then the client_cert_source property can be used to provide client certificate for mutual TLS transport. If not provided, the default SSL client certificate will be used if present. If GOOGLE_API_USE_CLIENT_CERTIFICATE is "false" or not set, no client certificate will be used.

Exceptions
TypeDescription
google.auth.exceptions.MutualTlsChannelErrorIf mutual TLS transport creation failed for any reason.

annotation_path

annotation_path(
    project: str, location: str, dataset: str, data_item: str, annotation: str
)

Returns a fully-qualified annotation string.

annotation_spec_path

annotation_spec_path(
    project: str, location: str, dataset: str, annotation_spec: str
)

Returns a fully-qualified annotation_spec string.

common_billing_account_path

common_billing_account_path(billing_account: str)

Returns a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Returns a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Returns a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Returns a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Returns a fully-qualified project string.

create_dataset

create_dataset(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.CreateDatasetRequest, dict]] = None, *, parent: Optional[str] = None, dataset: Optional[google.cloud.aiplatform_v1beta1.types.dataset.Dataset] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Creates a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_create_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1beta1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.CreateDatasetRequest(
        parent="parent_value",
        dataset=dataset,
    )

    # Make the request
    operation = client.create_dataset(request=request)

    print("Waiting for operation to complete...")

    response = await operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.CreateDatasetRequest, dict]

The request object. Request message for DatasetService.CreateDataset.

parent `str`

Required. The resource name of the Location to create the Dataset in. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.

dataset Dataset

Required. The Dataset to create. This corresponds to the dataset field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be Dataset A collection of DataItems and Annotations on them.

data_item_path

data_item_path(project: str, location: str, dataset: str, data_item: str)

Returns a fully-qualified data_item string.

dataset_path

dataset_path(project: str, location: str, dataset: str)

Returns a fully-qualified dataset string.

delete_dataset

delete_dataset(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.DeleteDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_delete_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.DeleteDatasetRequest(
        name="name_value",
    )

    # Make the request
    operation = client.delete_dataset(request=request)

    print("Waiting for operation to complete...")

    response = await operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.DeleteDatasetRequest, dict]

The request object. Request message for DatasetService.DeleteDataset.

name `str`

Required. The resource name of the Dataset to delete. Format: projects/{project}/locations/{location}/datasets/{dataset} This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be `google.protobuf.empty_pb2.Empty` A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); } The JSON representation for Empty is empty JSON object {}.

export_data

export_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.ExportDataRequest, dict]] = None, *, name: Optional[str] = None, export_config: Optional[google.cloud.aiplatform_v1beta1.types.dataset.ExportDataConfig] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Exports data from a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_export_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    export_config = aiplatform_v1beta1.ExportDataConfig()
    export_config.gcs_destination.output_uri_prefix = "output_uri_prefix_value"

    request = aiplatform_v1beta1.ExportDataRequest(
        name="name_value",
        export_config=export_config,
    )

    # Make the request
    operation = client.export_data(request=request)

    print("Waiting for operation to complete...")

    response = await operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.ExportDataRequest, dict]

The request object. Request message for DatasetService.ExportData.

name `str`

Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset} This corresponds to the name field on the request instance; if request is provided, this should not be set.

export_config ExportDataConfig

Required. The desired output location. This corresponds to the export_config field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be ExportDataResponse Response message for DatasetService.ExportData.

from_service_account_file

from_service_account_file(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
DatasetServiceAsyncClientThe constructed client.

from_service_account_info

from_service_account_info(info: dict, *args, **kwargs)

Creates an instance of this client using the provided credentials info.

Parameter
NameDescription
info dict

The service account private key info.

Returns
TypeDescription
DatasetServiceAsyncClientThe constructed client.

from_service_account_json

from_service_account_json(filename: str, *args, **kwargs)

Creates an instance of this client using the provided credentials file.

Parameter
NameDescription
filename str

The path to the service account private key json file.

Returns
TypeDescription
DatasetServiceAsyncClientThe constructed client.

get_annotation_spec

get_annotation_spec(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.GetAnnotationSpecRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets an AnnotationSpec.

from google.cloud import aiplatform_v1beta1

async def sample_get_annotation_spec():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetAnnotationSpecRequest(
        name="name_value",
    )

    # Make the request
    response = await client.get_annotation_spec(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.GetAnnotationSpecRequest, dict]

The request object. Request message for DatasetService.GetAnnotationSpec.

name `str`

Required. The name of the AnnotationSpec resource. Format: projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec} This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.types.AnnotationSpecIdentifies a concept with which DataItems may be annotated with.

get_dataset

get_dataset(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.GetDatasetRequest, dict]] = None, *, name: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_get_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.GetDatasetRequest(
        name="name_value",
    )

    # Make the request
    response = await client.get_dataset(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.GetDatasetRequest, dict]

The request object. Request message for DatasetService.GetDataset.

name `str`

Required. The name of the Dataset resource. This corresponds to the name field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.types.DatasetA collection of DataItems and Annotations on them.

get_mtls_endpoint_and_cert_source

get_mtls_endpoint_and_cert_source(
    client_options: Optional[google.api_core.client_options.ClientOptions] = None,
)

Return the API endpoint and client cert source for mutual TLS.

The client cert source is determined in the following order: (1) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is not "true", the client cert source is None. (2) if client_options.client_cert_source is provided, use the provided one; if the default client cert source exists, use the default one; otherwise the client cert source is None.

The API endpoint is determined in the following order: (1) if client_options.api_endpoint if provided, use the provided one. (2) if GOOGLE_API_USE_CLIENT_CERTIFICATE environment variable is "always", use the default mTLS endpoint; if the environment variabel is "never", use the default API endpoint; otherwise if client cert source exists, use the default mTLS endpoint, otherwise use the default API endpoint.

More details can be found at https://google.aip.dev/auth/4114.

Parameter
NameDescription
client_options google.api_core.client_options.ClientOptions

Custom options for the client. Only the api_endpoint and client_cert_source properties may be used in this method.

Exceptions
TypeDescription
google.auth.exceptions.MutualTLSChannelErrorIf any errors happen.
Returns
TypeDescription
Tuple[str, Callable[[], Tuple[bytes, bytes]]]returns the API endpoint and the client cert source to use.

get_transport_class

get_transport_class()

Returns an appropriate transport class.

import_data

import_data(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.ImportDataRequest, dict]] = None, *, name: Optional[str] = None, import_configs: Optional[Sequence[google.cloud.aiplatform_v1beta1.types.dataset.ImportDataConfig]] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Imports data into a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_import_data():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    import_configs = aiplatform_v1beta1.ImportDataConfig()
    import_configs.gcs_source.uris = ['uris_value_1', 'uris_value_2']
    import_configs.import_schema_uri = "import_schema_uri_value"

    request = aiplatform_v1beta1.ImportDataRequest(
        name="name_value",
        import_configs=import_configs,
    )

    # Make the request
    operation = client.import_data(request=request)

    print("Waiting for operation to complete...")

    response = await operation.result()

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.ImportDataRequest, dict]

The request object. Request message for DatasetService.ImportData.

name `str`

Required. The name of the Dataset resource. Format: projects/{project}/locations/{location}/datasets/{dataset} This corresponds to the name field on the request instance; if request is provided, this should not be set.

import_configs :class:`Sequence[google.cloud.aiplatform_v1beta1.types.ImportDataConfig]`

Required. The desired input locations. The contents of all input locations will be imported in one batch. This corresponds to the import_configs field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.api_core.operation_async.AsyncOperationAn object representing a long-running operation. The result type for the operation will be ImportDataResponse Response message for DatasetService.ImportData.

list_annotations

list_annotations(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.ListAnnotationsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists Annotations belongs to a dataitem

from google.cloud import aiplatform_v1beta1

async def sample_list_annotations():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListAnnotationsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_annotations(request=request)

    # Handle the response
    async for response in page_result:
        print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.ListAnnotationsRequest, dict]

The request object. Request message for DatasetService.ListAnnotations.

parent `str`

Required. The resource name of the DataItem to list Annotations from. Format: projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item} This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListAnnotationsAsyncPagerResponse message for DatasetService.ListAnnotations. Iterating over this object will yield results and resolve additional pages automatically.

list_data_items

list_data_items(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.ListDataItemsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists DataItems in a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_list_data_items():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListDataItemsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_data_items(request=request)

    # Handle the response
    async for response in page_result:
        print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.ListDataItemsRequest, dict]

The request object. Request message for DatasetService.ListDataItems.

parent `str`

Required. The resource name of the Dataset to list DataItems from. Format: projects/{project}/locations/{location}/datasets/{dataset} This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDataItemsAsyncPagerResponse message for DatasetService.ListDataItems. Iterating over this object will yield results and resolve additional pages automatically.

list_datasets

list_datasets(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.ListDatasetsRequest, dict]] = None, *, parent: Optional[str] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists Datasets in a Location.

from google.cloud import aiplatform_v1beta1

async def sample_list_datasets():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    request = aiplatform_v1beta1.ListDatasetsRequest(
        parent="parent_value",
    )

    # Make the request
    page_result = client.list_datasets(request=request)

    # Handle the response
    async for response in page_result:
        print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.ListDatasetsRequest, dict]

The request object. Request message for DatasetService.ListDatasets.

parent `str`

Required. The name of the Dataset's parent resource. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.services.dataset_service.pagers.ListDatasetsAsyncPagerResponse message for DatasetService.ListDatasets. Iterating over this object will yield results and resolve additional pages automatically.

parse_annotation_path

parse_annotation_path(path: str)

Parses a annotation path into its component segments.

parse_annotation_spec_path

parse_annotation_spec_path(path: str)

Parses a annotation_spec path into its component segments.

parse_common_billing_account_path

parse_common_billing_account_path(path: str)

Parse a billing_account path into its component segments.

parse_common_folder_path

parse_common_folder_path(path: str)

Parse a folder path into its component segments.

parse_common_location_path

parse_common_location_path(path: str)

Parse a location path into its component segments.

parse_common_organization_path

parse_common_organization_path(path: str)

Parse a organization path into its component segments.

parse_common_project_path

parse_common_project_path(path: str)

Parse a project path into its component segments.

parse_data_item_path

parse_data_item_path(path: str)

Parses a data_item path into its component segments.

parse_dataset_path

parse_dataset_path(path: str)

Parses a dataset path into its component segments.

update_dataset

update_dataset(request: Optional[Union[google.cloud.aiplatform_v1beta1.types.dataset_service.UpdateDatasetRequest, dict]] = None, *, dataset: Optional[google.cloud.aiplatform_v1beta1.types.dataset.Dataset] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: Union[google.api_core.retry.Retry, google.api_core.gapic_v1.method._MethodDefault] = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates a Dataset.

from google.cloud import aiplatform_v1beta1

async def sample_update_dataset():
    # Create a client
    client = aiplatform_v1beta1.DatasetServiceAsyncClient()

    # Initialize request argument(s)
    dataset = aiplatform_v1beta1.Dataset()
    dataset.display_name = "display_name_value"
    dataset.metadata_schema_uri = "metadata_schema_uri_value"
    dataset.metadata.null_value = "NULL_VALUE"

    request = aiplatform_v1beta1.UpdateDatasetRequest(
        dataset=dataset,
    )

    # Make the request
    response = await client.update_dataset(request=request)

    # Handle the response
    print(response)
Parameters
NameDescription
request Union[google.cloud.aiplatform_v1beta1.types.UpdateDatasetRequest, dict]

The request object. Request message for DatasetService.UpdateDataset.

dataset Dataset

Required. The Dataset which replaces the resource on the server. This corresponds to the dataset field on the request instance; if request is provided, this should not be set.

update_mask `google.protobuf.field_mask_pb2.FieldMask`

Required. The update mask applies to the resource. For the FieldMask definition, see google.protobuf.FieldMask][google.protobuf.FieldMask]. Updatable fields: - display_name - description - labels This corresponds to the update_mask field on the request instance; if request is provided, this should not be set.

retry google.api_core.retry.Retry

Designation of what errors, if any, should be retried.

timeout float

The timeout for this request.

metadata Sequence[Tuple[str, str]]

Strings which should be sent along with the request as metadata.

Returns
TypeDescription
google.cloud.aiplatform_v1beta1.types.DatasetA collection of DataItems and Annotations on them.