Class ModelServiceAsyncClient (1.4.3)

Version 1.4.3

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ModelServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.model_service.transports.base.ModelServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

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

Inheritance

builtins.object > ModelServiceAsyncClient

Properties

transport

Returns the transport used by the client instance.

Returns

Type	Description
ModelServiceTransport	The transport used by the client instance.

Methods

ModelServiceAsyncClient

ModelServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.model_service.transports.base.ModelServiceTransport] = 'grpc_asyncio', client_options: <module 'google.api_core.client_options' from '/workspace/python-aiplatform/.nox/docfx/lib/python3.8/site-packages/google/api_core/client_options.py'> = None, client_info: google.api_core.gapic_v1.client_info.ClientInfo = <google.api_core.gapic_v1.client_info.ClientInfo object>)

Instantiates 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	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

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)

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.

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 = <_MethodDefault._DEFAULT_VALUE: <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	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_async.AsyncOperation

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)

Returns 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 = <_MethodDefault._DEFAULT_VALUE: <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	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	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_async.AsyncOperation	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
ModelServiceAsyncClient	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
ModelServiceAsyncClient	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
ModelServiceAsyncClient	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 = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Gets a Model.

Parameters

Name	Description
request	GetModelRequest The request object. Request message for ModelService.GetModel.
name	`str` Required. The name of the Model resource. 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.cloud.aiplatform_v1beta1.types.Model	A trained machine learning Model.

get_model_evaluation

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

Gets a ModelEvaluation.

Parameters

Name	Description
request	GetModelEvaluationRequest The request object. Request message for ModelService.GetModelEvaluation.
name	`str` Required. The name of the ModelEvaluation resource. Format: projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation} 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.cloud.aiplatform_v1beta1.types.ModelEvaluation	A collection of metrics calculated by comparing Model's predictions on all of the test data against annotations from the test data.

get_model_evaluation_slice

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

Gets a ModelEvaluationSlice.

Parameters

Name	Description
request	GetModelEvaluationSliceRequest The request object. Request message for ModelService.GetModelEvaluationSlice.
name	`str` Required. The name of the ModelEvaluationSlice resource. Format: projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice} 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.cloud.aiplatform_v1beta1.types.ModelEvaluationSlice	A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations.

get_transport_class

get_transport_class()

Returns an appropriate transport class.

list_model_evaluation_slices

list_model_evaluation_slices(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.ListModelEvaluationSlicesRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists ModelEvaluationSlices in a ModelEvaluation.

Parameters

Name	Description
request	ListModelEvaluationSlicesRequest The request object. Request message for ModelService.ListModelEvaluationSlices.
parent	`str` Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation} 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

Type	Description
google.cloud.aiplatform_v1beta1.services.model_service.pagers.ListModelEvaluationSlicesAsyncPager	Response message for ModelService.ListModelEvaluationSlices. Iterating over this object will yield results and resolve additional pages automatically.

list_model_evaluations

list_model_evaluations(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.ListModelEvaluationsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists ModelEvaluations in a Model.

Parameters

Name	Description
request	ListModelEvaluationsRequest The request object. Request message for ModelService.ListModelEvaluations.
parent	`str` Required. The resource name of the Model to list the ModelEvaluations from. Format: projects/{project}/locations/{location}/models/{model} 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

Type	Description
google.cloud.aiplatform_v1beta1.services.model_service.pagers.ListModelEvaluationsAsyncPager	Response message for ModelService.ListModelEvaluations. Iterating over this object will yield results and resolve additional pages automatically.

list_models

list_models(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.ListModelsRequest] = None, *, parent: Optional[str] = None, retry: google.api_core.retry.Retry = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Lists Models in a Location.

Parameters

Name	Description
request	ListModelsRequest The request object. Request message for ModelService.ListModels.
parent	`str` Required. The resource name of the Location to list the Models from. 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

Type	Description
google.cloud.aiplatform_v1beta1.services.model_service.pagers.ListModelsAsyncPager	Response message for ModelService.ListModels Iterating over this object will yield results and resolve additional pages automatically.

model_evaluation_path

model_evaluation_path(project: str, location: str, model: str, evaluation: str)

Returns a fully-qualified model_evaluation string.

model_evaluation_slice_path

model_evaluation_slice_path(
    project: str, location: str, model: str, evaluation: str, slice: str
)

Returns a fully-qualified model_evaluation_slice string.

model_path

model_path(project: str, location: str, model: str)

Returns a fully-qualified model string.

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_endpoint_path

parse_endpoint_path(path: str)

Parses a endpoint path into its component segments.

parse_model_evaluation_path

parse_model_evaluation_path(path: str)

Parses a model_evaluation path into its component segments.

parse_model_evaluation_slice_path

parse_model_evaluation_slice_path(path: str)

Parses a model_evaluation_slice path into its component segments.

parse_model_path

parse_model_path(path: str)

Parses a model path into its component segments.

parse_training_pipeline_path

parse_training_pipeline_path(path: str)

Parses a training_pipeline path into its component segments.

training_pipeline_path

training_pipeline_path(project: str, location: str, training_pipeline: str)

Returns a fully-qualified training_pipeline string.

update_model

update_model(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.UpdateModelRequest] = None, *, model: Optional[google.cloud.aiplatform_v1beta1.types.model.Model] = None, update_mask: Optional[google.protobuf.field_mask_pb2.FieldMask] = None, retry: google.api_core.retry.Retry = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Updates a Model.

Parameters

Name	Description
request	UpdateModelRequest The request object. Request message for ModelService.UpdateModel.
model	Model Required. The Model which replaces the resource on the server. This corresponds to the model 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]. 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

Type	Description
google.cloud.aiplatform_v1beta1.types.Model	A trained machine learning Model.

upload_model

upload_model(request: Optional[google.cloud.aiplatform_v1beta1.types.model_service.UploadModelRequest] = None, *, parent: Optional[str] = None, model: Optional[google.cloud.aiplatform_v1beta1.types.model.Model] = None, retry: google.api_core.retry.Retry = <_MethodDefault._DEFAULT_VALUE: <object object>>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())

Uploads a Model artifact into Vertex AI.

Parameters

Name	Description
request	UploadModelRequest The request object. Request message for ModelService.UploadModel.
parent	`str` Required. The resource name of the Location into which to upload the Model. Format: projects/{project}/locations/{location} This corresponds to the parent field on the request instance; if request is provided, this should not be set.
model	Model Required. The Model to create. This corresponds to the model 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_async.AsyncOperation	An object representing a long-running operation. The result type for the operation will be UploadModelResponse Response message of ModelService.UploadModel operation.