public static final class AutoMlGrpc.AutoMlBlockingStub extends AbstractBlockingStub<AutoMlGrpc.AutoMlBlockingStub>
AutoML Server API.
The resource names are assigned by the server.
The server never reuses names that it has created after the resources with
those names are deleted.
An ID of a resource is the last element of the item's resource name. For
projects/{project_id}/locations/{location_id}/datasets/{dataset_id}
, then
the id for the item is {dataset_id}
.
Currently the only supported location_id
is "us-central1".
On any input that is documented to expect a string parameter in
snake_case or kebab-case, either of those cases is accepted.
Inheritance
java.lang.Object >
io.grpc.stub.AbstractStub >
io.grpc.stub.AbstractBlockingStub >
AutoMlGrpc.AutoMlBlockingStub
Inherited Members
io.grpc.stub.AbstractBlockingStub.<T>newStub(io.grpc.stub.AbstractStub.StubFactory<T>,io.grpc.Channel)
io.grpc.stub.AbstractBlockingStub.<T>newStub(io.grpc.stub.AbstractStub.StubFactory<T>,io.grpc.Channel,io.grpc.CallOptions)
io.grpc.stub.AbstractStub.<T>withOption(io.grpc.CallOptions.Key<T>,T)
io.grpc.stub.AbstractStub.build(io.grpc.Channel,io.grpc.CallOptions)
io.grpc.stub.AbstractStub.getCallOptions()
io.grpc.stub.AbstractStub.getChannel()
io.grpc.stub.AbstractStub.withCallCredentials(io.grpc.CallCredentials)
io.grpc.stub.AbstractStub.withChannel(io.grpc.Channel)
io.grpc.stub.AbstractStub.withCompression(java.lang.String)
io.grpc.stub.AbstractStub.withDeadline(io.grpc.Deadline)
io.grpc.stub.AbstractStub.withDeadlineAfter(long,java.util.concurrent.TimeUnit)
io.grpc.stub.AbstractStub.withExecutor(java.util.concurrent.Executor)
io.grpc.stub.AbstractStub.withInterceptors(io.grpc.ClientInterceptor...)
io.grpc.stub.AbstractStub.withMaxInboundMessageSize(int)
io.grpc.stub.AbstractStub.withMaxOutboundMessageSize(int)
io.grpc.stub.AbstractStub.withWaitForReady()
Methods
build(Channel channel, CallOptions callOptions)
protected AutoMlGrpc.AutoMlBlockingStub build(Channel channel, CallOptions callOptions)
Parameters
Name | Description |
channel | io.grpc.Channel
|
callOptions | io.grpc.CallOptions
|
Returns
Overrides
io.grpc.stub.AbstractStub.build(io.grpc.Channel,io.grpc.CallOptions)
createDataset(CreateDatasetRequest request)
public Dataset createDataset(CreateDatasetRequest request)
Parameter
Returns
createModel(CreateModelRequest request)
public Operation createModel(CreateModelRequest request)
Creates a model.
Returns a Model in the response
field when it completes.
When you create a model, several model evaluations are created for it:
a global evaluation, and one evaluation for each annotation spec.
Parameter
Returns
deleteDataset(DeleteDatasetRequest request)
public Operation deleteDataset(DeleteDatasetRequest request)
Deletes a dataset and all of its contents.
Returns empty response in the
response field when it completes,
and delete_details
in the
metadata field.
Parameter
Returns
deleteModel(DeleteModelRequest request)
public Operation deleteModel(DeleteModelRequest request)
Deletes a model.
Returns google.protobuf.Empty
in the
response field when it completes,
and delete_details
in the
metadata field.
Parameter
Returns
deployModel(DeployModelRequest request)
public Operation deployModel(DeployModelRequest request)
Deploys a model. If a model is already deployed, deploying it with the
same parameters has no effect. Deploying with different parametrs
(as e.g. changing
node_number)
will reset the deployment state without pausing the model's availability.
Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage
deployment automatically.
Returns an empty response in the
response field when it completes.
Parameter
Returns
exportData(ExportDataRequest request)
public Operation exportData(ExportDataRequest request)
Exports dataset's data to the provided output location.
Returns an empty response in the
response field when it completes.
Parameter
Returns
exportEvaluatedExamples(ExportEvaluatedExamplesRequest request)
public Operation exportEvaluatedExamples(ExportEvaluatedExamplesRequest request)
Exports examples on which the model was evaluated (i.e. which were in the
TEST set of the dataset the model was created from), together with their
ground truth annotations and the annotations created (predicted) by the
model.
The examples, ground truth and predictions are exported in the state
they were at the moment the model was evaluated.
This export is available only for 30 days since the model evaluation is
created.
Currently only available for Tables.
Returns an empty response in the
response field when it completes.
Parameter
Returns
exportModel(ExportModelRequest request)
public Operation exportModel(ExportModelRequest request)
Exports a trained, "export-able", model to a user specified Google Cloud
Storage location. A model is considered export-able if and only if it has
an export format defined for it in
ModelExportOutputConfig.
Returns an empty response in the
response field when it completes.
Parameter
Returns
getAnnotationSpec(GetAnnotationSpecRequest request)
public AnnotationSpec getAnnotationSpec(GetAnnotationSpecRequest request)
Parameter
Returns
getColumnSpec(GetColumnSpecRequest request)
public ColumnSpec getColumnSpec(GetColumnSpecRequest request)
Parameter
Returns
getDataset(GetDatasetRequest request)
public Dataset getDataset(GetDatasetRequest request)
Parameter
Returns
getModel(GetModelRequest request)
public Model getModel(GetModelRequest request)
Parameter
Returns
getModelEvaluation(GetModelEvaluationRequest request)
public ModelEvaluation getModelEvaluation(GetModelEvaluationRequest request)
Parameter
Returns
getTableSpec(GetTableSpecRequest request)
public TableSpec getTableSpec(GetTableSpecRequest request)
Parameter
Returns
importData(ImportDataRequest request)
public Operation importData(ImportDataRequest request)
Imports data into a dataset.
For Tables this method can only be called on an empty Dataset.
For Tables:
- A
schema_inference_version
parameter must be explicitly set.
Returns an empty response in the
response field when it completes.
Parameter
Returns
listColumnSpecs(ListColumnSpecsRequest request)
public ListColumnSpecsResponse listColumnSpecs(ListColumnSpecsRequest request)
Lists column specs in a table spec.
Parameter
Returns
listDatasets(ListDatasetsRequest request)
public ListDatasetsResponse listDatasets(ListDatasetsRequest request)
Lists datasets in a project.
Parameter
Returns
listModelEvaluations(ListModelEvaluationsRequest request)
public ListModelEvaluationsResponse listModelEvaluations(ListModelEvaluationsRequest request)
Parameter
Returns
listModels(ListModelsRequest request)
public ListModelsResponse listModels(ListModelsRequest request)
Parameter
Returns
listTableSpecs(ListTableSpecsRequest request)
public ListTableSpecsResponse listTableSpecs(ListTableSpecsRequest request)
Lists table specs in a dataset.
Parameter
Returns
undeployModel(UndeployModelRequest request)
public Operation undeployModel(UndeployModelRequest request)
Undeploys a model. If the model is not deployed this method has no effect.
Only applicable for Text Classification, Image Object Detection and Tables;
all other domains manage deployment automatically.
Returns an empty response in the
response field when it completes.
Parameter
Returns
updateColumnSpec(UpdateColumnSpecRequest request)
public ColumnSpec updateColumnSpec(UpdateColumnSpecRequest request)
Parameter
Returns
updateDataset(UpdateDatasetRequest request)
public Dataset updateDataset(UpdateDatasetRequest request)
Parameter
Returns
updateTableSpec(UpdateTableSpecRequest request)
public TableSpec updateTableSpec(UpdateTableSpecRequest request)
Parameter
Returns