Struct google_api_proto::google::cloud::aiplatform::v1::model_service_client::ModelServiceClient

pub struct ModelServiceClient<T> { /* private fields */ }

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

Implementations

impl<T> ModelServiceClient<T>

where T: GrpcService<BoxBody>, T::Error: Into<StdError>, T::ResponseBody: Body<Data = Bytes> + Send + 'static, <T::ResponseBody as Body>::Error: Into<StdError> + Send,

pub fn new(inner: T) -> Self

pub fn with_origin(inner: T, origin: Uri) -> Self

pub fn with_interceptor<F>( inner: T, interceptor: F, ) -> ModelServiceClient<InterceptedService<T, F>>

where F: Interceptor, T::ResponseBody: Default, T: Service<Request<BoxBody>, Response = Response<<T as GrpcService<BoxBody>>::ResponseBody>>, <T as Service<Request<BoxBody>>>::Error: Into<StdError> + Send + Sync,

pub fn send_compressed(self, encoding: CompressionEncoding) -> Self

Compress requests with the given encoding.

This requires the server to support it otherwise it might respond with an error.

pub fn accept_compressed(self, encoding: CompressionEncoding) -> Self

Enable decompressing responses.

pub fn max_decoding_message_size(self, limit: usize) -> Self

Limits the maximum size of a decoded message.

Default: 4MB

pub fn max_encoding_message_size(self, limit: usize) -> Self

Limits the maximum size of an encoded message.

Default: usize::MAX

pub async fn upload_model( &mut self, request: impl IntoRequest<UploadModelRequest>, ) -> Result<Response<Operation>, Status>

Uploads a Model artifact into Vertex AI.

pub async fn get_model( &mut self, request: impl IntoRequest<GetModelRequest>, ) -> Result<Response<Model>, Status>

Gets a Model.

pub async fn list_models( &mut self, request: impl IntoRequest<ListModelsRequest>, ) -> Result<Response<ListModelsResponse>, Status>

Lists Models in a Location.

pub async fn list_model_versions( &mut self, request: impl IntoRequest<ListModelVersionsRequest>, ) -> Result<Response<ListModelVersionsResponse>, Status>

Lists versions of the specified model.

pub async fn update_model( &mut self, request: impl IntoRequest<UpdateModelRequest>, ) -> Result<Response<Model>, Status>

Updates a Model.

pub async fn update_explanation_dataset( &mut self, request: impl IntoRequest<UpdateExplanationDatasetRequest>, ) -> Result<Response<Operation>, Status>

Incrementally update the dataset used for an examples model.

pub async fn delete_model( &mut self, request: impl IntoRequest<DeleteModelRequest>, ) -> Result<Response<Operation>, Status>

Deletes a Model.

A model cannot be deleted if any [Endpoint][google.cloud.aiplatform.v1.Endpoint] resource has a [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] based on the model in its [deployed_models][google.cloud.aiplatform.v1.Endpoint.deployed_models] field.

pub async fn delete_model_version( &mut self, request: impl IntoRequest<DeleteModelVersionRequest>, ) -> Result<Response<Operation>, Status>

Deletes a Model version.

Model version can only be deleted if there are no [DeployedModels][google.cloud.aiplatform.v1.DeployedModel] created from it. Deleting the only version in the Model is not allowed. Use [DeleteModel][google.cloud.aiplatform.v1.ModelService.DeleteModel] for deleting the Model instead.

pub async fn merge_version_aliases( &mut self, request: impl IntoRequest<MergeVersionAliasesRequest>, ) -> Result<Response<Model>, Status>

Merges a set of aliases for a Model version.

pub async fn export_model( &mut self, request: impl IntoRequest<ExportModelRequest>, ) -> Result<Response<Operation>, Status>

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.v1.Model.supported_export_formats].

pub async fn copy_model( &mut self, request: impl IntoRequest<CopyModelRequest>, ) -> Result<Response<Operation>, Status>

Copies an already existing Vertex AI Model into the specified Location. The source Model must exist in the same Project. When copying custom Models, the users themselves are responsible for [Model.metadata][google.cloud.aiplatform.v1.Model.metadata] content to be region-agnostic, as well as making sure that any resources (e.g. files) it depends on remain accessible.

pub async fn import_model_evaluation( &mut self, request: impl IntoRequest<ImportModelEvaluationRequest>, ) -> Result<Response<ModelEvaluation>, Status>

Imports an externally generated ModelEvaluation.

pub async fn batch_import_model_evaluation_slices( &mut self, request: impl IntoRequest<BatchImportModelEvaluationSlicesRequest>, ) -> Result<Response<BatchImportModelEvaluationSlicesResponse>, Status>

Imports a list of externally generated ModelEvaluationSlice.

pub async fn batch_import_evaluated_annotations( &mut self, request: impl IntoRequest<BatchImportEvaluatedAnnotationsRequest>, ) -> Result<Response<BatchImportEvaluatedAnnotationsResponse>, Status>

Imports a list of externally generated EvaluatedAnnotations.

pub async fn get_model_evaluation( &mut self, request: impl IntoRequest<GetModelEvaluationRequest>, ) -> Result<Response<ModelEvaluation>, Status>

Gets a ModelEvaluation.

pub async fn list_model_evaluations( &mut self, request: impl IntoRequest<ListModelEvaluationsRequest>, ) -> Result<Response<ListModelEvaluationsResponse>, Status>

Lists ModelEvaluations in a Model.

pub async fn get_model_evaluation_slice( &mut self, request: impl IntoRequest<GetModelEvaluationSliceRequest>, ) -> Result<Response<ModelEvaluationSlice>, Status>

Gets a ModelEvaluationSlice.

pub async fn list_model_evaluation_slices( &mut self, request: impl IntoRequest<ListModelEvaluationSlicesRequest>, ) -> Result<Response<ListModelEvaluationSlicesResponse>, Status>

Lists ModelEvaluationSlices in a ModelEvaluation.

Trait Implementations

impl<T: Clone> Clone for ModelServiceClient<T>

fn clone(&self) -> ModelServiceClient<T>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<T: Debug> Debug for ModelServiceClient<T>

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.