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PredictionServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport] = '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 online predictions and explanations.
Inheritance
builtins.object > PredictionServiceAsyncClientProperties
transport
Return the transport used by the client instance.
Type | Description |
PredictionServiceTransport | The transport used by the client instance. |
Methods
PredictionServiceAsyncClient
PredictionServiceAsyncClient(*, credentials: google.auth.credentials.Credentials = None, transport: Union[str, google.cloud.aiplatform_v1beta1.services.prediction_service.transports.base.PredictionServiceTransport] = '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>)
Instantiate the prediction service client.
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, `.PredictionServiceTransport`]
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 |
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.
endpoint_path
endpoint_path(project: str, location: str, endpoint: str)
Return a fully-qualified endpoint string.
explain
explain(request: Optional[google.cloud.aiplatform_v1beta1.types.prediction_service.ExplainRequest] = None, *, endpoint: Optional[str] = None, instances: Optional[Sequence[google.protobuf.struct_pb2.Value]] = None, parameters: Optional[google.protobuf.struct_pb2.Value] = None, deployed_model_id: Optional[str] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Perform an online explanation.
If
deployed_model_id
is specified, the corresponding DeployModel must have
explanation_spec
populated. If
deployed_model_id
is not specified, all DeployedModels must have
explanation_spec
populated. Only deployed AutoML tabular Models have
explanation_spec.
Name | Description |
request |
ExplainRequest
The request object. Request message for |
endpoint |
`str`
Required. The name of the Endpoint requested to serve the explanation. Format: |
instances |
:class:`Sequence[google.protobuf.struct_pb2.Value]`
Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] |
parameters |
`google.protobuf.struct_pb2.Value`
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] |
deployed_model_id |
`str`
If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding |
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. |
Type | Description |
google.cloud.aiplatform_v1beta1.types.ExplainResponse | Response message for ``PredictionService.Explain``. |
from_service_account_file
from_service_account_file(filename: str, *args, **kwargs)
Creates an instance of this client using the provided credentials file.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
PredictionServiceClient | 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.
Name | Description |
info |
dict
The service account private key info. |
Type | Description |
PredictionServiceClient | 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.
Name | Description |
filename |
str
The path to the service account private key json file. |
Type | Description |
PredictionServiceClient | The constructed client. |
get_transport_class
get_transport_class()
Return an appropriate transport class.
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)
Parse a endpoint path into its component segments.
predict
predict(request: Optional[google.cloud.aiplatform_v1beta1.types.prediction_service.PredictRequest] = None, *, endpoint: Optional[str] = None, instances: Optional[Sequence[google.protobuf.struct_pb2.Value]] = None, parameters: Optional[google.protobuf.struct_pb2.Value] = None, retry: google.api_core.retry.Retry = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Perform an online prediction.
Name | Description |
request |
PredictRequest
The request object. Request message for |
endpoint |
`str`
Required. The name of the Endpoint requested to serve the prediction. Format: |
instances |
:class:`Sequence[google.protobuf.struct_pb2.Value]`
Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] |
parameters |
`google.protobuf.struct_pb2.Value`
The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1beta1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1beta1.Model.predict_schemata] |
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. |
Type | Description |
google.cloud.aiplatform_v1beta1.types.PredictResponse | Response message for ``PredictionService.Predict``. |