Class ModelServiceClient (0.8.0)

ModelServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1beta1.services.model_service.transports.base.ModelServiceTransport]] = None, 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>)

A service for managing AI Platform's machine learning Models.

Inheritance

builtins.object > ModelServiceClient

Properties

transport

Return the transport used by the client instance.

Returns
Type Description
ModelServiceTransport The transport used by the client instance.

Methods

ModelServiceClient

ModelServiceClient(*, credentials: Optional[google.auth.credentials.Credentials] = None, transport: Optional[Union[str, google.cloud.aiplatform_v1beta1.services.model_service.transports.base.ModelServiceTransport]] = None, 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>)

Instantiate the model service client.

Parameters
Name Description
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, ModelServiceTransport]

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

client_options google.api_core.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.

client_info google.api_core.gapic_v1.client_info.ClientInfo

The client info used to send a user-agent string along with API requests. If None, then default info will be used. Generally, you only need to set this if you're developing your own client library.

Exceptions
Type Description
google.auth.exceptions.MutualTLSChannelError If mutual TLS transport creation failed for any reason.

common_billing_account_path

common_billing_account_path(billing_account: str)

Return a fully-qualified billing_account string.

common_folder_path

common_folder_path(folder: str)

Return a fully-qualified folder string.

common_location_path

common_location_path(project: str, location: str)

Return a fully-qualified location string.

common_organization_path

common_organization_path(organization: str)

Return a fully-qualified organization string.

common_project_path

common_project_path(project: str)

Return a fully-qualified project string.

delete_model

delete_model(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.DeleteModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Deletes a Model. Note: Model can only be deleted if there are no DeployedModels created from it.

Parameters
Name Description
request google.cloud.aiplatform_v1beta1.types.DeleteModelRequest

The request object. Request message for ModelService.DeleteModel.

name str

Required. The name of the Model resource to be deleted. Format: projects/{project}/locations/{location}/models/{model} 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
Type Description
google.api_core.operation.Operation An 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 {}.

endpoint_path

endpoint_path(project: str, location: str, endpoint: str)

Return a fully-qualified endpoint string.

export_model

export_model(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.ExportModelRequest] = None, *, name: Optional[str] = None, output_config: Optional[google.cloud.aiplatform_v1beta1.types.model_service.ExportModelRequest.OutputConfig] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Exports a trained, exportable, Model to a location specified by the user. A Model is considered to be exportable if it has at least one [supported export format][google.cloud.aiplatform.v1beta1.Model.supported_export_formats].

Parameters
Name Description
request google.cloud.aiplatform_v1beta1.types.ExportModelRequest

The request object. Request message for ModelService.ExportModel.

name str

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

output_config google.cloud.aiplatform_v1beta1.types.ExportModelRequest.OutputConfig

Required. The desired output location and configuration. This corresponds to the output_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
Type Description
google.api_core.operation.Operation An object representing a long-running operation. The result type for the operation will be ExportModelResponse Response message of ModelService.ExportModel operation.

from_service_account_file

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

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

Parameter
Name Description
filename str

The path to the service account private key json file.

Returns
Type Description
ModelServiceClient The 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
Name Description
info dict

The service account private key info.

Returns
Type Description
ModelServiceClient The 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
Name Description
filename str

The path to the service account private key json file.

Returns
Type Description
ModelServiceClient The constructed client.

get_model

get_model(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.GetModelRequest] = None, *, name: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a Model.

Parameters
Name Description