Class v1beta1.TensorboardServiceClient

TensorboardService v1beta1

Package

@google-cloud/aiplatform

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Construct an instance of TensorboardServiceClient.

Parameter
NameDescription
opts ClientOptions

Properties

apiEndpoint

static get apiEndpoint(): string;

The DNS address for this API service - same as servicePath(), exists for compatibility reasons.

auth

auth: gax.GoogleAuth;

descriptors

descriptors: Descriptors;

innerApiCalls

innerApiCalls: {
        [name: string]: Function;
    };

operationsClient

operationsClient: gax.OperationsClient;

pathTemplates

pathTemplates: {
        [name: string]: gax.PathTemplate;
    };

port

static get port(): number;

The port for this API service.

scopes

static get scopes(): string[];

The scopes needed to make gRPC calls for every method defined in this service.

servicePath

static get servicePath(): string;

The DNS address for this API service.

tensorboardServiceStub

tensorboardServiceStub?: Promise<{
        [name: string]: Function;
    }>;

warn

warn: (code: string, message: string, warnType?: string) => void;

Methods

annotationPath(project, location, dataset, dataItem, annotation)

annotationPath(project: string, location: string, dataset: string, dataItem: string, annotation: string): string;

Return a fully-qualified annotation resource name string.

Parameters
NameDescription
project string
location string
dataset string
dataItem string
annotation string
Returns
TypeDescription
string

{string} Resource name string.

annotationSpecPath(project, location, dataset, annotationSpec)

annotationSpecPath(project: string, location: string, dataset: string, annotationSpec: string): string;

Return a fully-qualified annotationSpec resource name string.

Parameters
NameDescription
project string
location string
dataset string
annotationSpec string
Returns
TypeDescription
string

{string} Resource name string.

artifactPath(project, location, metadataStore, artifact)

artifactPath(project: string, location: string, metadataStore: string, artifact: string): string;

Return a fully-qualified artifact resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
artifact string
Returns
TypeDescription
string

{string} Resource name string.

batchCreateTensorboardRuns(request, options)

batchCreateTensorboardRuns(request?: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse,
        (protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | undefined),
        {} | undefined
    ]>;

Batch create TensorboardRuns.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse, (protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [BatchCreateTensorboardRunsResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardExperiment to create the
   *  TensorboardRuns in. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   *  The parent field in the CreateTensorboardRunRequest messages must match
   *  this field.
   */
  // const parent = 'abc123'
  /**
   *  Required. The request message specifying the TensorboardRuns to create.
   *  A maximum of 1000 TensorboardRuns can be created in a batch.
   */
  // const requests = 1234

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callBatchCreateTensorboardRuns() {
    // Construct request
    const request = {
      parent,
      requests,
    };

    // Run request
    const response = await aiplatformClient.batchCreateTensorboardRuns(request);
    console.log(response);
  }

  callBatchCreateTensorboardRuns();

batchCreateTensorboardRuns(request, options, callback)

batchCreateTensorboardRuns(request: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchCreateTensorboardRuns(request, callback)

batchCreateTensorboardRuns(request: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchCreateTensorboardTimeSeries(request, options)

batchCreateTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse,
        (protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

Batch create TensorboardTimeSeries that belong to a TensorboardExperiment.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse, (protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [BatchCreateTensorboardTimeSeriesResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardExperiment to create the
   *  TensorboardTimeSeries in.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   *  The TensorboardRuns referenced by the parent fields in the
   *  CreateTensorboardTimeSeriesRequest messages must be sub resources of this
   *  TensorboardExperiment.
   */
  // const parent = 'abc123'
  /**
   *  Required. The request message specifying the TensorboardTimeSeries to create.
   *  A maximum of 1000 TensorboardTimeSeries can be created in a batch.
   */
  // const requests = 1234

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callBatchCreateTensorboardTimeSeries() {
    // Construct request
    const request = {
      parent,
      requests,
    };

    // Run request
    const response = await aiplatformClient.batchCreateTensorboardTimeSeries(request);
    console.log(response);
  }

  callBatchCreateTensorboardTimeSeries();

batchCreateTensorboardTimeSeries(request, options, callback)

batchCreateTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchCreateTensorboardTimeSeries(request, callback)

batchCreateTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchPredictionJobPath(project, location, batchPredictionJob)

batchPredictionJobPath(project: string, location: string, batchPredictionJob: string): string;

Return a fully-qualified batchPredictionJob resource name string.

Parameters
NameDescription
project string
location string
batchPredictionJob string
Returns
TypeDescription
string

{string} Resource name string.

batchReadTensorboardTimeSeriesData(request, options)

batchReadTensorboardTimeSeriesData(request?: protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse,
        (protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | undefined),
        {} | undefined
    ]>;

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.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse, (protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [BatchReadTensorboardTimeSeriesDataResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Tensorboard containing TensorboardTimeSeries to
   *  read data from. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`.
   *  The TensorboardTimeSeries referenced by time_series google.cloud.aiplatform.v1beta1.BatchReadTensorboardTimeSeriesDataRequest.time_series  must be sub
   *  resources of this Tensorboard.
   */
  // const tensorboard = 'abc123'
  /**
   *  Required. The resource names of the TensorboardTimeSeries to read data from. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const timeSeries = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callBatchReadTensorboardTimeSeriesData() {
    // Construct request
    const request = {
      tensorboard,
      timeSeries,
    };

    // Run request
    const response = await aiplatformClient.batchReadTensorboardTimeSeriesData(request);
    console.log(response);
  }

  callBatchReadTensorboardTimeSeriesData();

batchReadTensorboardTimeSeriesData(request, options, callback)

batchReadTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

batchReadTensorboardTimeSeriesData(request, callback)

batchReadTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

checkCreateTensorboardProgress(name)

checkCreateTensorboardProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Tensorboard, protos.google.cloud.aiplatform.v1beta1.CreateTensorboardOperationMetadata>>;

Check the status of the long running operation returned by createTensorboard().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Tensorboard, protos.google.cloud.aiplatform.v1beta1.CreateTensorboardOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to create the Tensorboard in.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Tensorboard to create.
   */
  // const tensorboard = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callCreateTensorboard() {
    // Construct request
    const request = {
      parent,
      tensorboard,
    };

    // Run request
    const [operation] = await aiplatformClient.createTensorboard(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateTensorboard();

checkDeleteTensorboardExperimentProgress(name)

checkDeleteTensorboardExperimentProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteTensorboardExperiment().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardExperiment to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardExperiment() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardExperiment(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardExperiment();

checkDeleteTensorboardProgress(name)

checkDeleteTensorboardProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteTensorboard().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Tensorboard to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboard() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboard(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboard();

checkDeleteTensorboardRunProgress(name)

checkDeleteTensorboardRunProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteTensorboardRun().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardRun to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardRun() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardRun(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardRun();

checkDeleteTensorboardTimeSeriesProgress(name)

checkDeleteTensorboardTimeSeriesProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;

Check the status of the long running operation returned by deleteTensorboardTimeSeries().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardTimeSeries to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardTimeSeries() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardTimeSeries(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardTimeSeries();

checkUpdateTensorboardProgress(name)

checkUpdateTensorboardProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Tensorboard, protos.google.cloud.aiplatform.v1beta1.UpdateTensorboardOperationMetadata>>;

Check the status of the long running operation returned by updateTensorboard().

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.Tensorboard, protos.google.cloud.aiplatform.v1beta1.UpdateTensorboardOperationMetadata>>

{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Field mask is used to specify the fields to be overwritten in the
   *  Tensorboard resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field will be overwritten if it is in the mask. If the
   *  user does not provide a mask then all fields will be overwritten if new
   *  values are specified.
   */
  // const updateMask = {}
  /**
   *  Required. The Tensorboard's `name` field is used to identify the
   *  Tensorboard to be updated. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const tensorboard = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callUpdateTensorboard() {
    // Construct request
    const request = {
      updateMask,
      tensorboard,
    };

    // Run request
    const [operation] = await aiplatformClient.updateTensorboard(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callUpdateTensorboard();

close()

close(): Promise<void>;

Terminate the gRPC channel and close the client.

The client will no longer be usable and all future behavior is undefined.

Returns
TypeDescription
Promise<void>

{Promise} A promise that resolves when the client is closed.

contextPath(project, location, metadataStore, context)

contextPath(project: string, location: string, metadataStore: string, context: string): string;

Return a fully-qualified context resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
context string
Returns
TypeDescription
string

{string} Resource name string.

createTensorboard(request, options)

createTensorboard(request?: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Creates a Tensorboard.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to create the Tensorboard in.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Tensorboard to create.
   */
  // const tensorboard = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callCreateTensorboard() {
    // Construct request
    const request = {
      parent,
      tensorboard,
    };

    // Run request
    const [operation] = await aiplatformClient.createTensorboard(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callCreateTensorboard();

createTensorboard(request, options, callback)

createTensorboard(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboard(request, callback)

createTensorboard(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardExperiment(request, options)

createTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment,
        (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | undefined),
        {} | undefined
    ]>;

Creates a TensorboardExperiment.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardExperiment]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Tensorboard to create the TensorboardExperiment
   *  in. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const parent = 'abc123'
  /**
   *  The TensorboardExperiment to create.
   */
  // const tensorboardExperiment = {}
  /**
   *  Required. The ID to use for the Tensorboard experiment, which will become the final
   *  component of the Tensorboard experiment's resource name.
   *  This value should be 1-128 characters, and valid characters
   *  are /[a-z][0-9]-/.
   */
  // const tensorboardExperimentId = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callCreateTensorboardExperiment() {
    // Construct request
    const request = {
      parent,
      tensorboardExperimentId,
    };

    // Run request
    const response = await aiplatformClient.createTensorboardExperiment(request);
    console.log(response);
  }

  callCreateTensorboardExperiment();

createTensorboardExperiment(request, options, callback)

createTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardExperiment(request, callback)

createTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardRun(request, options)

createTensorboardRun(request?: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardRun,
        (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | undefined),
        {} | undefined
    ]>;

Creates a TensorboardRun.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardRun]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardExperiment to create the TensorboardRun
   *  in. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The TensorboardRun to create.
   */
  // const tensorboardRun = {}
  /**
   *  Required. The ID to use for the Tensorboard run, which will become the final
   *  component of the Tensorboard run's resource name.
   *  This value should be 1-128 characters, and valid characters
   *  are /[a-z][0-9]-/.
   */
  // const tensorboardRunId = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callCreateTensorboardRun() {
    // Construct request
    const request = {
      parent,
      tensorboardRun,
      tensorboardRunId,
    };

    // Run request
    const response = await aiplatformClient.createTensorboardRun(request);
    console.log(response);
  }

  callCreateTensorboardRun();

createTensorboardRun(request, options, callback)

createTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardRun(request, callback)

createTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardTimeSeries(request, options)

createTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries,
        (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

Creates a TensorboardTimeSeries.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, (protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardTimeSeries]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardRun to create the
   *  TensorboardTimeSeries in.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const parent = 'abc123'
  /**
   *  Optional. The user specified unique ID to use for the TensorboardTimeSeries, which
   *  will become the final component of the TensorboardTimeSeries's resource
   *  name.
   *  This value should match "[a-z0-9][a-z0-9-]{0, 127}"
   */
  // const tensorboardTimeSeriesId = 'abc123'
  /**
   *  Required. The TensorboardTimeSeries to create.
   */
  // const tensorboardTimeSeries = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callCreateTensorboardTimeSeries() {
    // Construct request
    const request = {
      parent,
      tensorboardTimeSeries,
    };

    // Run request
    const response = await aiplatformClient.createTensorboardTimeSeries(request);
    console.log(response);
  }

  callCreateTensorboardTimeSeries();

createTensorboardTimeSeries(request, options, callback)

createTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createTensorboardTimeSeries(request, callback)

createTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

customJobPath(project, location, customJob)

customJobPath(project: string, location: string, customJob: string): string;

Return a fully-qualified customJob resource name string.

Parameters
NameDescription
project string
location string
customJob string
Returns
TypeDescription
string

{string} Resource name string.

dataItemPath(project, location, dataset, dataItem)

dataItemPath(project: string, location: string, dataset: string, dataItem: string): string;

Return a fully-qualified dataItem resource name string.

Parameters
NameDescription
project string
location string
dataset string
dataItem string
Returns
TypeDescription
string

{string} Resource name string.

dataLabelingJobPath(project, location, dataLabelingJob)

dataLabelingJobPath(project: string, location: string, dataLabelingJob: string): string;

Return a fully-qualified dataLabelingJob resource name string.

Parameters
NameDescription
project string
location string
dataLabelingJob string
Returns
TypeDescription
string

{string} Resource name string.

datasetPath(project, location, dataset)

datasetPath(project: string, location: string, dataset: string): string;

Return a fully-qualified dataset resource name string.

Parameters
NameDescription
project string
location string
dataset string
Returns
TypeDescription
string

{string} Resource name string.

deleteTensorboard(request, options)

deleteTensorboard(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a Tensorboard.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Tensorboard to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboard() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboard(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboard();

deleteTensorboard(request, options, callback)

deleteTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboard(request, callback)

deleteTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardExperiment(request, options)

deleteTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a TensorboardExperiment.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardExperiment to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardExperiment() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardExperiment(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardExperiment();

deleteTensorboardExperiment(request, options, callback)

deleteTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardExperiment(request, callback)

deleteTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardRun(request, options)

deleteTensorboardRun(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a TensorboardRun.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardRun to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardRun() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardRun(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardRun();

deleteTensorboardRun(request, options, callback)

deleteTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardRun(request, callback)

deleteTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardTimeSeries(request, options)

deleteTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a TensorboardTimeSeries.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardTimeSeries to be deleted.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callDeleteTensorboardTimeSeries() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const [operation] = await aiplatformClient.deleteTensorboardTimeSeries(request);
    const [response] = await operation.promise();
    console.log(response);
  }

  callDeleteTensorboardTimeSeries();

deleteTensorboardTimeSeries(request, options, callback)

deleteTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteTensorboardTimeSeries(request, callback)

deleteTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

endpointPath(project, location, endpoint)

endpointPath(project: string, location: string, endpoint: string): string;

Return a fully-qualified endpoint resource name string.

Parameters
NameDescription
project string
location string
endpoint string
Returns
TypeDescription
string

{string} Resource name string.

entityTypePath(project, location, featurestore, entityType)

entityTypePath(project: string, location: string, featurestore: string, entityType: string): string;

Return a fully-qualified entityType resource name string.

Parameters
NameDescription
project string
location string
featurestore string
entityType string
Returns
TypeDescription
string

{string} Resource name string.

executionPath(project, location, metadataStore, execution)

executionPath(project: string, location: string, metadataStore: string, execution: string): string;

Return a fully-qualified execution resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
execution string
Returns
TypeDescription
string

{string} Resource name string.

exportTensorboardTimeSeriesData(request, options)

exportTensorboardTimeSeriesData(request?: protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint[],
        protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse
    ]>;

Exports a TensorboardTimeSeries' data. Data is returned in paginated responses.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint[], protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest | null, protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [TimeSeriesDataPoint]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using exportTensorboardTimeSeriesDataAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

exportTensorboardTimeSeriesData(request, options, callback)

exportTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>
Returns
TypeDescription
void

exportTensorboardTimeSeriesData(request, callback)

exportTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>
Returns
TypeDescription
void

exportTensorboardTimeSeriesDataAsync(request, options)

exportTensorboardTimeSeriesDataAsync(request?: protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>;

Equivalent to exportTensorboardTimeSeriesData, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITimeSeriesDataPoint>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [TimeSeriesDataPoint]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardTimeSeries to export data from.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const tensorboardTimeSeries = 'abc123'
  /**
   *  Exports the TensorboardTimeSeries' data that match the filter expression.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of data points to return per page.
   *  The default page_size will be 1000. Values must be between 1 and 10000.
   *  Values above 10000 will be coerced to 10000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  TensorboardService.ExportTensorboardTimeSeries   call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ExportTensorboardTimeSeries   must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Field to use to sort the TensorboardTimeSeries' data.
   *  By default, TensorboardTimeSeries' data will be returned in a pseudo random
   *  order.
   */
  // const orderBy = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callExportTensorboardTimeSeriesData() {
    // Construct request
    const request = {
      tensorboardTimeSeries,
    };

    // Run request
    const iterable = await aiplatformClient.exportTensorboardTimeSeriesDataAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callExportTensorboardTimeSeriesData();

exportTensorboardTimeSeriesDataStream(request, options)

exportTensorboardTimeSeriesDataStream(request?: protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Transform

{Stream} An object stream which emits an object representing [TimeSeriesDataPoint] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using exportTensorboardTimeSeriesDataAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

featurePath(project, location, featurestore, entityType, feature)

featurePath(project: string, location: string, featurestore: string, entityType: string, feature: string): string;

Return a fully-qualified feature resource name string.

Parameters
NameDescription
project string
location string
featurestore string
entityType string
feature string
Returns
TypeDescription
string

{string} Resource name string.

featurestorePath(project, location, featurestore)

featurestorePath(project: string, location: string, featurestore: string): string;

Return a fully-qualified featurestore resource name string.

Parameters
NameDescription
project string
location string
featurestore string
Returns
TypeDescription
string

{string} Resource name string.

getProjectId()

getProjectId(): Promise<string>;
Returns
TypeDescription
Promise<string>

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;
Parameter
NameDescription
callback Callback<string, undefined, undefined>
Returns
TypeDescription
void

getTensorboard(request, options)

getTensorboard(request?: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboard,
        protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | undefined,
        {} | undefined
    ]>;

Gets a Tensorboard.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Tensorboard]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Tensorboard resource.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callGetTensorboard() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getTensorboard(request);
    console.log(response);
  }

  callGetTensorboard();

getTensorboard(request, options, callback)

getTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboard(request, callback)

getTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardExperiment(request, options)

getTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment,
        (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | undefined),
        {} | undefined
    ]>;

Gets a TensorboardExperiment.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardExperiment]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardExperiment resource.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callGetTensorboardExperiment() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getTensorboardExperiment(request);
    console.log(response);
  }

  callGetTensorboardExperiment();

getTensorboardExperiment(request, options, callback)

getTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardExperiment(request, callback)

getTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardRun(request, options)

getTensorboardRun(request?: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardRun,
        (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | undefined),
        {} | undefined
    ]>;

Gets a TensorboardRun.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardRun]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardRun resource.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callGetTensorboardRun() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getTensorboardRun(request);
    console.log(response);
  }

  callGetTensorboardRun();

getTensorboardRun(request, options, callback)

getTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardRun(request, callback)

getTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardTimeSeries(request, options)

getTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries,
        (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

Gets a TensorboardTimeSeries.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, (protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TensorboardTimeSeries]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the TensorboardTimeSeries resource.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callGetTensorboardTimeSeries() {
    // Construct request
    const request = {
      name,
    };

    // Run request
    const response = await aiplatformClient.getTensorboardTimeSeries(request);
    console.log(response);
  }

  callGetTensorboardTimeSeries();

getTensorboardTimeSeries(request, options, callback)

getTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getTensorboardTimeSeries(request, callback)

getTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest
callback Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

hyperparameterTuningJobPath(project: string, location: string, hyperparameterTuningJob: string): string;

Return a fully-qualified hyperparameterTuningJob resource name string.

Parameters
NameDescription
project string
location string
hyperparameterTuningJob string
Returns
TypeDescription
string

{string} Resource name string.

indexEndpointPath(project, location, indexEndpoint)

indexEndpointPath(project: string, location: string, indexEndpoint: string): string;

Return a fully-qualified indexEndpoint resource name string.

Parameters
NameDescription
project string
location string
indexEndpoint string
Returns
TypeDescription
string

{string} Resource name string.

indexPath(project, location, index)

indexPath(project: string, location: string, index: string): string;

Return a fully-qualified index resource name string.

Parameters
NameDescription
project string
location string
index string
Returns
TypeDescription
string

{string} Resource name string.

initialize()

initialize(): Promise<{
        [name: string]: Function;
    }>;

Initialize the client. Performs asynchronous operations (such as authentication) and prepares the client. This function will be called automatically when any class method is called for the first time, but if you need to initialize it before calling an actual method, feel free to call initialize() directly.

You can await on this method if you want to make sure the client is initialized.

Returns
TypeDescription
Promise<{ [name: string]: Function; }>

{Promise} A promise that resolves to an authenticated service stub.

listTensorboardExperiments(request, options)

listTensorboardExperiments(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment[],
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse
    ]>;

Lists TensorboardExperiments in a Location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment[], protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest | null, protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [TensorboardExperiment]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listTensorboardExperimentsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboardExperiments(request, options, callback)

listTensorboardExperiments(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>
Returns
TypeDescription
void

listTensorboardExperiments(request, callback)

listTensorboardExperiments(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>
Returns
TypeDescription
void

listTensorboardExperimentsAsync(request, options)

listTensorboardExperimentsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>;

Equivalent to listTensorboardExperiments, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [TensorboardExperiment]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Tensorboard to list TensorboardExperiments.
   *  Format:
   *  'projects/{project}/locations/{location}/tensorboards/{tensorboard}'
   */
  // const parent = 'abc123'
  /**
   *  Lists the TensorboardExperiments that match the filter expression.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of TensorboardExperiments to return. The service may
   *  return fewer than this value. If unspecified, at most 50
   *  TensorboardExperiments will be returned. The maximum value is 1000; values
   *  above 1000 will be coerced to 1000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  TensorboardService.ListTensorboardExperiments google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardExperiments google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardExperiments  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Field to use to sort the list.
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callListTensorboardExperiments() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listTensorboardExperimentsAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListTensorboardExperiments();

listTensorboardExperimentsStream(request, options)

listTensorboardExperimentsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Transform

{Stream} An object stream which emits an object representing [TensorboardExperiment] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listTensorboardExperimentsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboardRuns(request, options)

listTensorboardRuns(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardRun[],
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse
    ]>;

Lists TensorboardRuns in a Location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardRun[], protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest | null, protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [TensorboardRun]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listTensorboardRunsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboardRuns(request, options, callback)

listTensorboardRuns(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>
Returns
TypeDescription
void

listTensorboardRuns(request, callback)

listTensorboardRuns(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>
Returns
TypeDescription
void

listTensorboardRunsAsync(request, options)

listTensorboardRunsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>;

Equivalent to listTensorboardRuns, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [TensorboardRun]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardExperiment to list TensorboardRuns.
   *  Format:
   *  'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}'
   */
  // const parent = 'abc123'
  /**
   *  Lists the TensorboardRuns that match the filter expression.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of TensorboardRuns to return. The service may return
   *  fewer than this value. If unspecified, at most 50 TensorboardRuns will be
   *  returned. The maximum value is 1000; values above 1000 will be coerced to
   *  1000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  TensorboardService.ListTensorboardRuns google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardRuns google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardRuns  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Field to use to sort the list.
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callListTensorboardRuns() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listTensorboardRunsAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListTensorboardRuns();

listTensorboardRunsStream(request, options)

listTensorboardRunsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Transform

{Stream} An object stream which emits an object representing [TensorboardRun] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listTensorboardRunsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboards(request, options)

listTensorboards(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboard[],
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse
    ]>;

Lists Tensorboards in a Location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboard[], protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest | null, protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Tensorboard]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listTensorboardsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboards(request, options, callback)

listTensorboards(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboard>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboard>
Returns
TypeDescription
void

listTensorboards(request, callback)

listTensorboards(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboard>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboard>
Returns
TypeDescription
void

listTensorboardsAsync(request, options)

listTensorboardsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboard>;

Equivalent to listTensorboards, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboard>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Tensorboard]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the Location to list Tensorboards.
   *  Format:
   *  `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Lists the Tensorboards that match the filter expression.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of Tensorboards to return. The service may return
   *  fewer than this value. If unspecified, at most 100 Tensorboards will be
   *  returned. The maximum value is 100; values above 100 will be coerced to
   *  100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  TensorboardService.ListTensorboards google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboards google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboards  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Field to use to sort the list.
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callListTensorboards() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listTensorboardsAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListTensorboards();

listTensorboardsStream(request, options)

listTensorboardsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Transform

{Stream} An object stream which emits an object representing [Tensorboard] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listTensorboardsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboardTimeSeries(request, options)

listTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries[],
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest | null,
        protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse
    ]>;

Lists TensorboardTimeSeries in a Location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries[], protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest | null, protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [TensorboardTimeSeries]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listTensorboardTimeSeriesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTensorboardTimeSeries(request, options, callback)

listTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>
Returns
TypeDescription
void

listTensorboardTimeSeries(request, callback)

listTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>
Returns
TypeDescription
void

listTensorboardTimeSeriesAsync(request, options)

listTensorboardTimeSeriesAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>;

Equivalent to listTensorboardTimeSeries, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [TensorboardTimeSeries]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardRun to list TensorboardTimeSeries.
   *  Format:
   *  'projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}'
   */
  // const parent = 'abc123'
  /**
   *  Lists the TensorboardTimeSeries that match the filter expression.
   */
  // const filter = 'abc123'
  /**
   *  The maximum number of TensorboardTimeSeries to return. The service may
   *  return fewer than this value. If unspecified, at most 50
   *  TensorboardTimeSeries will be returned. The maximum value is 1000; values
   *  above 1000 will be coerced to 1000.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  TensorboardService.ListTensorboardTimeSeries google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries  call.
   *  Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardTimeSeries google.cloud.aiplatform.v1beta1.TensorboardService.ListTensorboardTimeSeries  must
   *  match the call that provided the page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Field to use to sort the list.
   */
  // const orderBy = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1beta1;

  // Instantiates a client
  const aiplatformClient = new TensorboardServiceClient();

  async function callListTensorboardTimeSeries() {
    // Construct request
    const request = {
      parent,
    };

    // Run request
    const iterable = await aiplatformClient.listTensorboardTimeSeriesAsync(request);
    for await (const response of iterable) {
        console.log(response);
    }
  }

  callListTensorboardTimeSeries();

listTensorboardTimeSeriesStream(request, options)

listTensorboardTimeSeriesStream(request?: protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Transform

{Stream} An object stream which emits an object representing [TensorboardTimeSeries] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listTensorboardTimeSeriesAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

locationPath(project, location)

locationPath(project: string, location: string): string;

Return a fully-qualified location resource name string.

Parameters
NameDescription
project string
location string
Returns
TypeDescription
string

{string} Resource name string.

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

Parse the annotation from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation_spec.

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

Parse the artifact from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the artifact.

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the batch_prediction_job from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the batch_prediction_job.

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

Parse the context from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the context.

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

Parse the custom_job from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the custom_job.

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

Parse the data_item from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the data_item.

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

Parse the data_item from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the data_item.

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the data_labeling_job from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the data_labeling_job.

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

Parse the dataset from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

Parse the dataset from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

Parse the endpoint from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the endpoint.

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

Parse the entity_type from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: string): string | number;

Parse the entity_type from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the evaluation from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the evaluation from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

Parse the execution from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the execution.

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the experiment from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the experiment from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the experiment from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

Parse the feature from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature.

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

Parse the featurestore from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

Parse the featurestore from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

Parse the featurestore from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the hyperparameter_tuning_job.

matchIndexEndpointFromIndexEndpointName(indexEndpointName)

matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the index_endpoint from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the index_endpoint.

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

Parse the index from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the index.

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

Parse the location from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

Parse the location from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the location from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

Parse the location from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

Parse the location from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

Parse the location from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the location from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

Parse the location from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

Parse the location from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

Parse the location from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

Parse the location from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

Parse the location from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the location from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the location from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

Parse the location from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the location from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the location from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the location from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the location from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

Parse the location from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the location from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

Parse the location from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the location from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

Parse the location from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the location from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the location from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the location from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

Parse the location from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_schema from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_schema.

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

Parse the metadata_store from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

Parse the metadata_store from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

Parse the metadata_store from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_store from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the metadata_store from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the model_deployment_monitoring_job from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the model_deployment_monitoring_job.

matchModelFromModelEvaluationName(modelEvaluationName)

matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the model from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

Parse the pipeline_job from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the pipeline_job.

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

Parse the project from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

Parse the project from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the project from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

Parse the project from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

Parse the project from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

Parse the project from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the project from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromEndpointName(endpointName)

matchProjectFromEndpointName(endpointName: string): string | number;

Parse the project from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

Parse the project from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

Parse the project from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureName(featureName)

matchProjectFromFeatureName(featureName: string): string | number;

Parse the project from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

Parse the project from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the project from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the project from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

Parse the project from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the project from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the project from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the project from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the project from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

Parse the project from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

Parse the project from Project resource.

Parameter
NameDescription
projectName string

A fully-qualified path representing Project resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the project from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

Parse the project from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the project from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

Parse the project from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the project from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the project from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrainingPipelineName(trainingPipelineName)

matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the project from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrialName(trialName)

matchProjectFromTrialName(trialName: string): string | number;

Parse the project from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchRunFromTensorboardRunName(tensorboardRunName)

matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the run from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the run from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the slice from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the slice.

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the specialist_pool from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the specialist_pool.

matchStudyFromStudyName(studyName)

matchStudyFromStudyName(studyName: string): string | number;

Parse the study from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing