public static final class TensorboardServiceGrpc.TensorboardServiceBlockingStub extends AbstractBlockingStub<TensorboardServiceGrpc.TensorboardServiceBlockingStub>
Inheritance
java.lang.Object >
io.grpc.stub.AbstractStub >
io.grpc.stub.AbstractBlockingStub >
TensorboardServiceGrpc.TensorboardServiceBlockingStub
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
public BatchCreateTensorboardRunsResponse batchCreateTensorboardRuns(BatchCreateTensorboardRunsRequest request)
Batch create TensorboardRuns.
public BatchCreateTensorboardTimeSeriesResponse batchCreateTensorboardTimeSeries(BatchCreateTensorboardTimeSeriesRequest request)
Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.
public BatchReadTensorboardTimeSeriesDataResponse batchReadTensorboardTimeSeriesData(BatchReadTensorboardTimeSeriesDataRequest request)
Reads multiple TensorboardTimeSeries' data. The data point number limit is
1000 for scalars, 100 for tensors and blob references. If the number of
data points stored is less than the limit, all data will be returned.
Otherwise, that limit number of data points will be randomly selected from
this time series and returned.
protected TensorboardServiceGrpc.TensorboardServiceBlockingStub 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)
public Operation createTensorboard(CreateTensorboardRequest request)
Parameter
Returns
public TensorboardExperiment createTensorboardExperiment(CreateTensorboardExperimentRequest request)
Creates a TensorboardExperiment.
public TensorboardRun createTensorboardRun(CreateTensorboardRunRequest request)
Creates a TensorboardRun.
public TensorboardTimeSeries createTensorboardTimeSeries(CreateTensorboardTimeSeriesRequest request)
Creates a TensorboardTimeSeries.
public Operation deleteTensorboard(DeleteTensorboardRequest request)
Parameter
Returns
public Operation deleteTensorboardExperiment(DeleteTensorboardExperimentRequest request)
Deletes a TensorboardExperiment.
public Operation deleteTensorboardRun(DeleteTensorboardRunRequest request)
Deletes a TensorboardRun.
public Operation deleteTensorboardTimeSeries(DeleteTensorboardTimeSeriesRequest request)
Deletes a TensorboardTimeSeries.
public ExportTensorboardTimeSeriesDataResponse exportTensorboardTimeSeriesData(ExportTensorboardTimeSeriesDataRequest request)
Exports a TensorboardTimeSeries' data. Data is returned in paginated
responses.
public Tensorboard getTensorboard(GetTensorboardRequest request)
Parameter
Returns
public TensorboardExperiment getTensorboardExperiment(GetTensorboardExperimentRequest request)
Gets a TensorboardExperiment.
public TensorboardRun getTensorboardRun(GetTensorboardRunRequest request)
Parameter
Returns
public TensorboardTimeSeries getTensorboardTimeSeries(GetTensorboardTimeSeriesRequest request)
Gets a TensorboardTimeSeries.
public ListTensorboardExperimentsResponse listTensorboardExperiments(ListTensorboardExperimentsRequest request)
Lists TensorboardExperiments in a Location.
public ListTensorboardRunsResponse listTensorboardRuns(ListTensorboardRunsRequest request)
Lists TensorboardRuns in a Location.
public ListTensorboardTimeSeriesResponse listTensorboardTimeSeries(ListTensorboardTimeSeriesRequest request)
Lists TensorboardTimeSeries in a Location.
public ListTensorboardsResponse listTensorboards(ListTensorboardsRequest request)
Lists Tensorboards in a Location.
public Iterator<ReadTensorboardBlobDataResponse> readTensorboardBlobData(ReadTensorboardBlobDataRequest request)
Gets bytes of TensorboardBlobs.
This is to allow reading blob data stored in consumer project's Cloud
Storage bucket without users having to obtain Cloud Storage access
permission.
public ReadTensorboardTimeSeriesDataResponse readTensorboardTimeSeriesData(ReadTensorboardTimeSeriesDataRequest request)
Reads a TensorboardTimeSeries' data. By default, if the number of data
points stored is less than 1000, all data will be returned. Otherwise, 1000
data points will be randomly selected from this time series and returned.
This value can be changed by changing max_data_points, which can't be
greater than 10k.
public Operation updateTensorboard(UpdateTensorboardRequest request)
Parameter
Returns
public TensorboardExperiment updateTensorboardExperiment(UpdateTensorboardExperimentRequest request)
Updates a TensorboardExperiment.
public TensorboardRun updateTensorboardRun(UpdateTensorboardRunRequest request)
Updates a TensorboardRun.
public TensorboardTimeSeries updateTensorboardTimeSeries(UpdateTensorboardTimeSeriesRequest request)
Updates a TensorboardTimeSeries.
public WriteTensorboardExperimentDataResponse writeTensorboardExperimentData(WriteTensorboardExperimentDataRequest request)
Write time series data points of multiple TensorboardTimeSeries in multiple
TensorboardRun's. If any data fail to be ingested, an error will be
returned.
public WriteTensorboardRunDataResponse writeTensorboardRunData(WriteTensorboardRunDataRequest request)
Write time series data points into multiple TensorboardTimeSeries under
a TensorboardRun. If any data fail to be ingested, an error will be
returned.
