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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 > ModelServiceClientProperties
transport
Return the transport used by the client instance.
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.
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 |
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 |
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.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.DeleteModelRequest
The request object. Request message for |
name |
str
Required. The name of the Model resource to be deleted. Format: |
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.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].
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.ExportModelRequest
The request object. Request message for |
name |
str
Required. The resource name of the Model to export. Format: |
output_config |
google.cloud.aiplatform_v1beta1.types.ExportModelRequest.OutputConfig
Required. The desired output location and configuration. This corresponds to the |
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.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.
Name | Description |
filename |
str
The path to the service account private key json file. |
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.
Name | Description |
info |
dict
The service account private key info. |
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.
Name | Description |
filename |
str
The path to the service account private key json file. |
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.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.GetModelRequest
The request object. Request message for |
name |
str
Required. The name of the Model resource. Format: |
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.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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a ModelEvaluation.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.GetModelEvaluationRequest
The request object. Request message for |
name |
str
Required. The name of the ModelEvaluation resource. Format: |
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.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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Gets a ModelEvaluationSlice.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.GetModelEvaluationSliceRequest
The request object. Request message for |
name |
str
Required. The name of the ModelEvaluationSlice resource. Format: |
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.ModelEvaluationSlice | A collection of metrics calculated by comparing Model's predictions on a slice of the test data against ground truth annotations. |
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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists ModelEvaluationSlices in a ModelEvaluation.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.ListModelEvaluationSlicesRequest
The request object. Request message for |
parent |
str
Required. The resource name of the ModelEvaluation to list the ModelEvaluationSlices from. Format: |
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.services.model_service.pagers.ListModelEvaluationSlicesPager | 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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists ModelEvaluations in a Model.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.ListModelEvaluationsRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Model to list the ModelEvaluations from. Format: |
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.services.model_service.pagers.ListModelEvaluationsPager | 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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Lists Models in a Location.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.ListModelsRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Location to list the Models from. Format: |
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.services.model_service.pagers.ListModelsPager | 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)
Return a fully-qualified model_evaluation string.
model_evaluation_slice_path
model_evaluation_slice_path(
project: str, location: str, model: str, evaluation: str, slice: str
)
Return a fully-qualified model_evaluation_slice string.
model_path
model_path(project: str, location: str, model: str)
Return 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)
Parse a endpoint path into its component segments.
parse_model_evaluation_path
parse_model_evaluation_path(path: str)
Parse a model_evaluation path into its component segments.
parse_model_evaluation_slice_path
parse_model_evaluation_slice_path(path: str)
Parse a model_evaluation_slice path into its component segments.
parse_model_path
parse_model_path(path: str)
Parse a model path into its component segments.
parse_training_pipeline_path
parse_training_pipeline_path(path: str)
Parse a training_pipeline path into its component segments.
training_pipeline_path
training_pipeline_path(project: str, location: str, training_pipeline: str)
Return 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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Updates a Model.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.UpdateModelRequest
The request object. Request message for |
model |
google.cloud.aiplatform_v1beta1.types.Model
Required. The Model which replaces the resource on the server. This corresponds to the |
update_mask |
google.protobuf.field_mask_pb2.FieldMask
Required. The update mask applies to the resource. For the |
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.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 = <object object>, timeout: Optional[float] = None, metadata: Sequence[Tuple[str, str]] = ())
Uploads a Model artifact into AI Platform.
Name | Description |
request |
google.cloud.aiplatform_v1beta1.types.UploadModelRequest
The request object. Request message for |
parent |
str
Required. The resource name of the Location into which to upload the Model. Format: |
model |
google.cloud.aiplatform_v1beta1.types.Model
Required. The Model to create. This corresponds to the |
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.api_core.operation.Operation | An object representing a long-running operation. The result type for the operation will be UploadModelResponse Response message of ``ModelService.UploadModel`` operation. |