Class v1beta1.TensorboardServiceClient (2.5.0)

TensorboardService v1beta1

Package

Constructors

(constructor)(opts, gaxInstance)

constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);

Construct an instance of TensorboardServiceClient.

Parameters

Name	Description
`opts`	`ClientOptions`
`gaxInstance`	`typeof gax \| typeof gax.fallback` : loaded instance of `google-gax`. Useful if you need to avoid loading the default gRPC version and want to use the fallback HTTP implementation. Load only fallback version and pass it to the constructor: ``` const gax = require('google-gax/build/src/fallback'); // avoids loading google-gax with gRPC const client = new TensorboardServiceClient({fallback: 'rest'}, gax); ```

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;

iamClient

iamClient: IamClient;

innerApiCalls

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

locationsClient

locationsClient: LocationsClient;

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

Name	Description
`project`	`string`
`location`	`string`
`dataset`	`string`
`dataItem`	`string`
`annotation`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`dataset`	`string`
`annotationSpec`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`metadataStore`	`string`
`artifact`	`string`

Returns

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardRunsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IBatchCreateTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`void`

batchPredictionJobPath(project, location, batchPredictionJob)

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

Return a fully-qualified batchPredictionJob resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`batchPredictionJob`	`string`

Returns

Type	Description
`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 is returned. Otherwise, the number limit of data points is randomly selected from this time series and returned.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IBatchReadTensorboardTimeSeriesDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`void`

cancelOperation(request, options, callback)

cancelOperation(request: protos.google.longrunning.CancelOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>, callback?: Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>): Promise<protos.google.protobuf.Empty>;

Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED. Clients can use or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an value with a of 1, corresponding to Code.CANCELLED.

Parameters

Name	Description
`request`	`protos.google.longrunning.CancelOperationRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} \| undefined \| null>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.
`callback`	`Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} \| undefined \| null>` The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call.

Returns

Type	Description
`Promise<protos.google.protobuf.Empty>`

Example


const client = longrunning.operationsClient();
await client.cancelOperation({name: ''});

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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`name`	`string` The operation name that will be passed.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 is overwritten if it's in the mask. If the
   *  user does not provide a mask then all fields are 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

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`metadataStore`	`string`
`context`	`string`

Returns

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardExperimentRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 becomes 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardRunRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 becomes 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.ICreateTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 becomes 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`void`

customJobPath(project, location, customJob)

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

Return a fully-qualified customJob resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`customJob`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`dataset`	`string`
`dataItem`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`dataLabelingJob`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`dataset`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

deleteOperation(request, options, callback)

deleteOperation(request: protos.google.longrunning.DeleteOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>): Promise<protos.google.protobuf.Empty>;

Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED.

Parameters

Name	Description
`request`	`protos.google.longrunning.DeleteOperationRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} \| null \| undefined>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.
`callback`	`Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} \| null \| undefined>` The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call.

Returns

Type	Description
`Promise<protos.google.protobuf.Empty>`

Example


const client = longrunning.operationsClient();
await client.deleteOperation({name: ''});

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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardExperimentRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardRunRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IDeleteTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`void`

deploymentResourcePoolPath(project, location, deploymentResourcePool)

deploymentResourcePoolPath(project: string, location: string, deploymentResourcePool: string): string;

Return a fully-qualified deploymentResourcePool resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`deploymentResourcePool`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

endpointPath(project, location, endpoint)

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

Return a fully-qualified endpoint resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`endpoint`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`featurestore`	`string`
`entityType`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`metadataStore`	`string`
`execution`	`string`

Returns

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 is 1000. Values must be between 1 and 10000.
   *  Values above 10000 are 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 is 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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IExportTensorboardTimeSeriesDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`project`	`string`
`location`	`string`
`featurestore`	`string`
`entityType`	`string`
`feature`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`featurestore`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

getIamPolicy(request, options, callback)

getIamPolicy(request: IamProtos.google.iam.v1.GetIamPolicyRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.Policy>;

Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.

Parameters

Name	Description
`request`	`IamProtos.google.iam.v1.GetIamPolicyRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest \| null \| undefined, {} \| null \| undefined>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details.
`callback`	`Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest \| null \| undefined, {} \| null \| undefined>` The function which will be called with the result of the API call. The second parameter to the callback is an object representing [Policy].

Returns

Type	Description
`Promise<IamProtos.google.iam.v1.Policy>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Policy]. The promise has a method named "cancel" which cancels the ongoing API call.

getLocation(request, options, callback)

getLocation(request: LocationProtos.google.cloud.location.IGetLocationRequest, options?: gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>, callback?: Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>): Promise<LocationProtos.google.cloud.location.ILocation>;

Gets information about a location.

Parameters

Name	Description
`request`	`LocationProtos.google.cloud.location.IGetLocationRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest \| null \| undefined, {} \| null \| undefined>` Call options. See CallOptions for more details.
`callback`	`Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`Promise<LocationProtos.google.cloud.location.ILocation>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Location]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example


const [response] = await client.getLocation(request);

getOperation(request, options, callback)

getOperation(request: protos.google.longrunning.GetOperationRequest, options?: gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>): Promise<[protos.google.longrunning.Operation]>;

Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.

Parameters

Name	Description
`request`	`protos.google.longrunning.GetOperationRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} \| null \| undefined>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.
`callback`	`Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} \| null \| undefined>` The function which will be called with the result of the API call. The second parameter to the callback is an object representing [google.longrunning.Operation]. {Promise} - The promise which resolves to an array. The first element of the array is an object representing [google.longrunning.Operation]. The promise has a method named "cancel" which cancels the ongoing API call.

Returns

Type	Description
`Promise<[protos.google.longrunning.Operation]>`

Example


const client = longrunning.operationsClient();
const name = '';
const [response] = await client.getOperation({name});
// doThingsWith(response)

getProjectId()

getProjectId(): Promise<string>;

Returns

Type	Description
`Promise<string>`

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;

Parameter

Name	Description
`callback`	`Callback<string, undefined, undefined>`

Returns

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IGetTensorboardExperimentRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IGetTensorboardRunRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IGetTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`void`

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

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

Return a fully-qualified hyperparameterTuningJob resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`hyperparameterTuningJob`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`indexEndpoint`	`string`

Returns

Type	Description
`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

Name	Description
`project`	`string`
`location`	`string`
`index`	`string`

Returns

Type	Description
`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

Type	Description
`Promise<{ [name: string]: Function; }>`	{Promise} A promise that resolves to an authenticated service stub.

listLocationsAsync(request, options)

listLocationsAsync(request: LocationProtos.google.cloud.location.IListLocationsRequest, options?: CallOptions): AsyncIterable<LocationProtos.google.cloud.location.ILocation>;

Lists information about the supported locations for this service. Returns an iterable object.

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

Parameters

Name	Description
`request`	`LocationProtos.google.cloud.location.IListLocationsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

AsyncIterable<LocationProtos.google.cloud.location.ILocation>

{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 [Location]. 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


const iterable = client.listLocationsAsync(request);
for await (const response of iterable) {
  // process response
}

listOperationsAsync(request, options)

listOperationsAsync(request: protos.google.longrunning.ListOperationsRequest, options?: gax.CallOptions): AsyncIterable<protos.google.longrunning.ListOperationsResponse>;

Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns UNIMPLEMENTED. Returns an iterable object.

For-await-of syntax is used with the iterable to recursively get response element on-demand.

Parameters

Name	Description
`request`	`protos.google.longrunning.ListOperationsRequest` The request object that will be sent.
`options`	`gax.CallOptions` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details.

Returns

Type	Description
`AsyncIterable<protos.google.longrunning.ListOperationsResponse>`	{Object} An iterable Object that conforms to https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols.

Example


const client = longrunning.operationsClient();
for await (const response of client.listOperationsAsync(request));
// doThingsWith(response)

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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 are returned. The maximum value is 1000; values
   *  above 1000 are 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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardExperimentsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 are
   *  returned. The maximum value is 1000; values above 1000 are 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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardRunsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 are
   *  returned. The maximum value is 100; values above 100 are 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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardsRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`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

Type	Description
`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

Name	Description
`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

Type	Description
`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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 are returned. The maximum value is 1000; values
   *  above 1000 are 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

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IListTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type Description

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

Name	Description
`project`	`string`
`location`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

Parse the annotation from Annotation resource.

Parameter

Name	Description
`annotationName`	`string` A fully-qualified path representing Annotation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the annotation.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter

Name	Description
`annotationSpecName`	`string` A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
`string \| number`	{string} A string representing the annotation_spec.

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

Parse the artifact from Artifact resource.

Parameter

Name	Description
`artifactName`	`string` A fully-qualified path representing Artifact resource.

Returns

Type	Description
`string \| number`	{string} A string representing the artifact.

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the batch_prediction_job from BatchPredictionJob resource.

Parameter

Name	Description
`batchPredictionJobName`	`string` A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the batch_prediction_job.

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

Parse the context from Context resource.

Parameter

Name	Description
`contextName`	`string` A fully-qualified path representing Context resource.

Returns

Type	Description
`string \| number`	{string} A string representing the context.

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

Parse the custom_job from CustomJob resource.

Parameter

Name	Description
`customJobName`	`string` A fully-qualified path representing CustomJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the custom_job.

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

Parse the data_item from Annotation resource.

Parameter

Name	Description
`annotationName`	`string` A fully-qualified path representing Annotation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the data_item.

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

Parse the data_item from DataItem resource.

Parameter

Name	Description
`dataItemName`	`string` A fully-qualified path representing DataItem resource.

Returns

Type	Description
`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

Name	Description
`dataLabelingJobName`	`string` A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the data_labeling_job.

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

Parse the dataset from Annotation resource.

Parameter

Name	Description
`annotationName`	`string` A fully-qualified path representing Annotation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the dataset.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter

Name	Description
`annotationSpecName`	`string` A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
`string \| number`	{string} A string representing the dataset.

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

Parse the dataset from DataItem resource.

Parameter

Name	Description
`dataItemName`	`string` A fully-qualified path representing DataItem resource.

Returns

Type	Description
`string \| number`	{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter

Name	Description
`datasetName`	`string` A fully-qualified path representing Dataset resource.

Returns

Type	Description
`string \| number`	{string} A string representing the dataset.

matchDatasetFromSavedQueryName(savedQueryName)

matchDatasetFromSavedQueryName(savedQueryName: string): string | number;

Parse the dataset from SavedQuery resource.

Parameter

Name	Description
`savedQueryName`	`string` A fully-qualified path representing SavedQuery resource.

Returns

Type	Description
`string \| number`	{string} A string representing the dataset.

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the deployment_resource_pool from DeploymentResourcePool resource.

Parameter

Name	Description
`deploymentResourcePoolName`	`string` A fully-qualified path representing DeploymentResourcePool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the deployment_resource_pool.

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

Parse the endpoint from Endpoint resource.

Parameter

Name	Description
`endpointName`	`string` A fully-qualified path representing Endpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the endpoint.

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

Parse the entity_type from EntityType resource.

Parameter

Name	Description
`entityTypeName`	`string` A fully-qualified path representing EntityType resource.

Returns

Type	Description
`string \| number`	{string} A string representing the entity_type.

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: string): string | number;

Parse the entity_type from Feature resource.

Parameter

Name	Description
`featureName`	`string` A fully-qualified path representing Feature resource.

Returns

Type	Description
`string \| number`	{string} A string representing the entity_type.

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the evaluation from ModelEvaluation resource.

Parameter

Name	Description
`modelEvaluationName`	`string` A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the evaluation.

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the evaluation from ModelEvaluationSlice resource.

Parameter

Name	Description
`modelEvaluationSliceName`	`string` A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
`string \| number`	{string} A string representing the evaluation.

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

Parse the execution from Execution resource.

Parameter

Name	Description
`executionName`	`string` A fully-qualified path representing Execution resource.

Returns

Type	Description
`string \| number`	{string} A string representing the execution.

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the experiment from TensorboardExperiment resource.

Parameter

Name	Description
`tensorboardExperimentName`	`string` A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
`string \| number`	{string} A string representing the experiment.

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the experiment from TensorboardRun resource.

Parameter

Name	Description
`tensorboardRunName`	`string` A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
`string \| number`	{string} A string representing the experiment.

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the experiment from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the experiment.

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

Parse the feature from Feature resource.

Parameter

Name	Description
`featureName`	`string` A fully-qualified path representing Feature resource.

Returns

Type	Description
`string \| number`	{string} A string representing the feature.

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

Parse the featurestore from EntityType resource.

Parameter

Name	Description
`entityTypeName`	`string` A fully-qualified path representing EntityType resource.

Returns

Type	Description
`string \| number`	{string} A string representing the featurestore.

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

Parse the featurestore from Feature resource.

Parameter

Name	Description
`featureName`	`string` A fully-qualified path representing Feature resource.

Returns

Type	Description
`string \| number`	{string} A string representing the featurestore.

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

Parse the featurestore from Featurestore resource.

Parameter

Name	Description
`featurestoreName`	`string` A fully-qualified path representing Featurestore resource.

Returns

Type	Description
`string \| number`	{string} A string representing the featurestore.

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.

Parameter

Name	Description
`hyperparameterTuningJobName`	`string` A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
`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

Name	Description
`indexEndpointName`	`string` A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the index_endpoint.

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

Parse the index from Index resource.

Parameter

Name	Description
`indexName`	`string` A fully-qualified path representing Index resource.

Returns

Type	Description
`string \| number`	{string} A string representing the index.

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

Parse the location from Annotation resource.

Parameter

Name	Description
`annotationName`	`string` A fully-qualified path representing Annotation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter

Name	Description
`annotationSpecName`	`string` A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

Parse the location from Artifact resource.

Parameter

Name	Description
`artifactName`	`string` A fully-qualified path representing Artifact resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the location from BatchPredictionJob resource.

Parameter

Name	Description
`batchPredictionJobName`	`string` A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

Parse the location from Context resource.

Parameter

Name	Description
`contextName`	`string` A fully-qualified path representing Context resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

Parse the location from CustomJob resource.

Parameter

Name	Description
`customJobName`	`string` A fully-qualified path representing CustomJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

Parse the location from DataItem resource.

Parameter

Name	Description
`dataItemName`	`string` A fully-qualified path representing DataItem resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the location from DataLabelingJob resource.

Parameter

Name	Description
`dataLabelingJobName`	`string` A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter

Name	Description
`datasetName`	`string` A fully-qualified path representing Dataset resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the location from DeploymentResourcePool resource.

Parameter

Name	Description
`deploymentResourcePoolName`	`string` A fully-qualified path representing DeploymentResourcePool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

Parse the location from Endpoint resource.

Parameter

Name	Description
`endpointName`	`string` A fully-qualified path representing Endpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

Parse the location from EntityType resource.

Parameter

Name	Description
`entityTypeName`	`string` A fully-qualified path representing EntityType resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

Parse the location from Execution resource.

Parameter

Name	Description
`executionName`	`string` A fully-qualified path representing Execution resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

Parse the location from Feature resource.

Parameter

Name	Description
`featureName`	`string` A fully-qualified path representing Feature resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

Parse the location from Featurestore resource.

Parameter

Name	Description
`featurestoreName`	`string` A fully-qualified path representing Featurestore resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the location from HyperparameterTuningJob resource.

Parameter

Name	Description
`hyperparameterTuningJobName`	`string` A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the location from IndexEndpoint resource.

Parameter

Name	Description
`indexEndpointName`	`string` A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

Parse the location from Index resource.

Parameter

Name	Description
`indexName`	`string` A fully-qualified path representing Index resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter

Name	Description
`locationName`	`string` A fully-qualified path representing Location resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the location from MetadataSchema resource.

Parameter

Name	Description
`metadataSchemaName`	`string` A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the location from MetadataStore resource.

Parameter

Name	Description
`metadataStoreName`	`string` A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the location from ModelDeploymentMonitoringJob resource.

Parameter

Name	Description
`modelDeploymentMonitoringJobName`	`string` A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter

Name	Description
`modelEvaluationName`	`string` A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the location from ModelEvaluationSlice resource.

Parameter

Name	Description
`modelEvaluationSliceName`	`string` A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter

Name	Description
`modelName`	`string` A fully-qualified path representing Model resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

Parse the location from PipelineJob resource.

Parameter

Name	Description
`pipelineJobName`	`string` A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromSavedQueryName(savedQueryName)

matchLocationFromSavedQueryName(savedQueryName: string): string | number;

Parse the location from SavedQuery resource.

Parameter

Name	Description
`savedQueryName`	`string` A fully-qualified path representing SavedQuery resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the location from SpecialistPool resource.

Parameter

Name	Description
`specialistPoolName`	`string` A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

Parse the location from Study resource.

Parameter

Name	Description
`studyName`	`string` A fully-qualified path representing Study resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the location from TensorboardExperiment resource.

Parameter

Name	Description
`tensorboardExperimentName`	`string` A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

Parse the location from Tensorboard resource.

Parameter

Name	Description
`tensorboardName`	`string` A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the location from TensorboardRun resource.

Parameter

Name	Description
`tensorboardRunName`	`string` A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the location from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the location from TrainingPipeline resource.

Parameter

Name	Description
`trainingPipelineName`	`string` A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

Parse the location from Trial resource.

Parameter

Name	Description
`trialName`	`string` A fully-qualified path representing Trial resource.

Returns

Type	Description
`string \| number`	{string} A string representing the location.

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_schema from MetadataSchema resource.

Parameter

Name	Description
`metadataSchemaName`	`string` A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
`string \| number`	{string} A string representing the metadata_schema.

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

Parse the metadata_store from Artifact resource.

Parameter

Name	Description
`artifactName`	`string` A fully-qualified path representing Artifact resource.

Returns

Type	Description
`string \| number`	{string} A string representing the metadata_store.

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

Parse the metadata_store from Context resource.

Parameter

Name	Description
`contextName`	`string` A fully-qualified path representing Context resource.

Returns

Type	Description
`string \| number`	{string} A string representing the metadata_store.

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

Parse the metadata_store from Execution resource.

Parameter

Name	Description
`executionName`	`string` A fully-qualified path representing Execution resource.

Returns

Type	Description
`string \| number`	{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_store from MetadataSchema resource.

Parameter

Name	Description
`metadataSchemaName`	`string` A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
`string \| number`	{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the metadata_store from MetadataStore resource.

Parameter

Name	Description
`metadataStoreName`	`string` A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
`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

Name	Description
`modelDeploymentMonitoringJobName`	`string` A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
`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

Name	Description
`modelEvaluationName`	`string` A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the model.

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the model from ModelEvaluationSlice resource.

Parameter

Name	Description
`modelEvaluationSliceName`	`string` A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
`string \| number`	{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter

Name	Description
`modelName`	`string` A fully-qualified path representing Model resource.

Returns

Type	Description
`string \| number`	{string} A string representing the model.

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

Parse the pipeline_job from PipelineJob resource.

Parameter

Name	Description
`pipelineJobName`	`string` A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the pipeline_job.

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

Parse the project from Annotation resource.

Parameter

Name	Description
`annotationName`	`string` A fully-qualified path representing Annotation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter

Name	Description
`annotationSpecName`	`string` A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

Parse the project from Artifact resource.

Parameter

Name	Description
`artifactName`	`string` A fully-qualified path representing Artifact resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the project from BatchPredictionJob resource.

Parameter

Name	Description
`batchPredictionJobName`	`string` A fully-qualified path representing BatchPredictionJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

Parse the project from Context resource.

Parameter

Name	Description
`contextName`	`string` A fully-qualified path representing Context resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

Parse the project from CustomJob resource.

Parameter

Name	Description
`customJobName`	`string` A fully-qualified path representing CustomJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

Parse the project from DataItem resource.

Parameter

Name	Description
`dataItemName`	`string` A fully-qualified path representing DataItem resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the project from DataLabelingJob resource.

Parameter

Name	Description
`dataLabelingJobName`	`string` A fully-qualified path representing DataLabelingJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter

Name	Description
`datasetName`	`string` A fully-qualified path representing Dataset resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName)

matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;

Parse the project from DeploymentResourcePool resource.

Parameter

Name	Description
`deploymentResourcePoolName`	`string` A fully-qualified path representing DeploymentResourcePool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromEndpointName(endpointName)

matchProjectFromEndpointName(endpointName: string): string | number;

Parse the project from Endpoint resource.

Parameter

Name	Description
`endpointName`	`string` A fully-qualified path representing Endpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

Parse the project from EntityType resource.

Parameter

Name	Description
`entityTypeName`	`string` A fully-qualified path representing EntityType resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

Parse the project from Execution resource.

Parameter

Name	Description
`executionName`	`string` A fully-qualified path representing Execution resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromFeatureName(featureName)

matchProjectFromFeatureName(featureName: string): string | number;

Parse the project from Feature resource.

Parameter

Name	Description
`featureName`	`string` A fully-qualified path representing Feature resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

Parse the project from Featurestore resource.

Parameter

Name	Description
`featurestoreName`	`string` A fully-qualified path representing Featurestore resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the project from HyperparameterTuningJob resource.

Parameter

Name	Description
`hyperparameterTuningJobName`	`string` A fully-qualified path representing HyperparameterTuningJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the project from IndexEndpoint resource.

Parameter

Name	Description
`indexEndpointName`	`string` A fully-qualified path representing IndexEndpoint resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

Parse the project from Index resource.

Parameter

Name	Description
`indexName`	`string` A fully-qualified path representing Index resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter

Name	Description
`locationName`	`string` A fully-qualified path representing Location resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the project from MetadataSchema resource.

Parameter

Name	Description
`metadataSchemaName`	`string` A fully-qualified path representing MetadataSchema resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the project from MetadataStore resource.

Parameter

Name	Description
`metadataStoreName`	`string` A fully-qualified path representing MetadataStore resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the project from ModelDeploymentMonitoringJob resource.

Parameter

Name	Description
`modelDeploymentMonitoringJobName`	`string` A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter

Name	Description
`modelEvaluationName`	`string` A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the project from ModelEvaluationSlice resource.

Parameter

Name	Description
`modelEvaluationSliceName`	`string` A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter

Name	Description
`modelName`	`string` A fully-qualified path representing Model resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

Parse the project from PipelineJob resource.

Parameter

Name	Description
`pipelineJobName`	`string` A fully-qualified path representing PipelineJob resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

Parse the project from Project resource.

Parameter

Name	Description
`projectName`	`string` A fully-qualified path representing Project resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromSavedQueryName(savedQueryName)

matchProjectFromSavedQueryName(savedQueryName: string): string | number;

Parse the project from SavedQuery resource.

Parameter

Name	Description
`savedQueryName`	`string` A fully-qualified path representing SavedQuery resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the project from SpecialistPool resource.

Parameter

Name	Description
`specialistPoolName`	`string` A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

Parse the project from Study resource.

Parameter

Name	Description
`studyName`	`string` A fully-qualified path representing Study resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the project from TensorboardExperiment resource.

Parameter

Name	Description
`tensorboardExperimentName`	`string` A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

Parse the project from Tensorboard resource.

Parameter

Name	Description
`tensorboardName`	`string` A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the project from TensorboardRun resource.

Parameter

Name	Description
`tensorboardRunName`	`string` A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the project from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTrainingPipelineName(trainingPipelineName)

matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the project from TrainingPipeline resource.

Parameter

Name	Description
`trainingPipelineName`	`string` A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchProjectFromTrialName(trialName)

matchProjectFromTrialName(trialName: string): string | number;

Parse the project from Trial resource.

Parameter

Name	Description
`trialName`	`string` A fully-qualified path representing Trial resource.

Returns

Type	Description
`string \| number`	{string} A string representing the project.

matchRunFromTensorboardRunName(tensorboardRunName)

matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the run from TensorboardRun resource.

Parameter

Name	Description
`tensorboardRunName`	`string` A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
`string \| number`	{string} A string representing the run.

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the run from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the run.

matchSavedQueryFromSavedQueryName(savedQueryName)

matchSavedQueryFromSavedQueryName(savedQueryName: string): string | number;

Parse the saved_query from SavedQuery resource.

Parameter

Name	Description
`savedQueryName`	`string` A fully-qualified path representing SavedQuery resource.

Returns

Type	Description
`string \| number`	{string} A string representing the saved_query.

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the slice from ModelEvaluationSlice resource.

Parameter

Name	Description
`modelEvaluationSliceName`	`string` A fully-qualified path representing ModelEvaluationSlice resource.

Returns

Type	Description
`string \| number`	{string} A string representing the slice.

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the specialist_pool from SpecialistPool resource.

Parameter

Name	Description
`specialistPoolName`	`string` A fully-qualified path representing SpecialistPool resource.

Returns

Type	Description
`string \| number`	{string} A string representing the specialist_pool.

matchStudyFromStudyName(studyName)

matchStudyFromStudyName(studyName: string): string | number;

Parse the study from Study resource.

Parameter

Name	Description
`studyName`	`string` A fully-qualified path representing Study resource.

Returns

Type	Description
`string \| number`	{string} A string representing the study.

matchStudyFromTrialName(trialName)

matchStudyFromTrialName(trialName: string): string | number;

Parse the study from Trial resource.

Parameter

Name	Description
`trialName`	`string` A fully-qualified path representing Trial resource.

Returns

Type	Description
`string \| number`	{string} A string representing the study.

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the tensorboard from TensorboardExperiment resource.

Parameter

Name	Description
`tensorboardExperimentName`	`string` A fully-qualified path representing TensorboardExperiment resource.

Returns

Type	Description
`string \| number`	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardName(tensorboardName)

matchTensorboardFromTensorboardName(tensorboardName: string): string | number;

Parse the tensorboard from Tensorboard resource.

Parameter

Name	Description
`tensorboardName`	`string` A fully-qualified path representing Tensorboard resource.

Returns

Type	Description
`string \| number`	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardRunName(tensorboardRunName)

matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the tensorboard from TensorboardRun resource.

Parameter

Name	Description
`tensorboardRunName`	`string` A fully-qualified path representing TensorboardRun resource.

Returns

Type	Description
`string \| number`	{string} A string representing the tensorboard.

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the tensorboard from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the tensorboard.

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the time_series from TensorboardTimeSeries resource.

Parameter

Name	Description
`tensorboardTimeSeriesName`	`string` A fully-qualified path representing TensorboardTimeSeries resource.

Returns

Type	Description
`string \| number`	{string} A string representing the time_series.

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the training_pipeline from TrainingPipeline resource.

Parameter

Name	Description
`trainingPipelineName`	`string` A fully-qualified path representing TrainingPipeline resource.

Returns

Type	Description
`string \| number`	{string} A string representing the training_pipeline.

matchTrialFromTrialName(trialName)

matchTrialFromTrialName(trialName: string): string | number;

Parse the trial from Trial resource.

Parameter

Name	Description
`trialName`	`string` A fully-qualified path representing Trial resource.

Returns

Type	Description
`string \| number`	{string} A string representing the trial.

metadataSchemaPath(project, location, metadataStore, metadataSchema)

metadataSchemaPath(project: string, location: string, metadataStore: string, metadataSchema: string): string;

Return a fully-qualified metadataSchema resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`metadataStore`	`string`
`metadataSchema`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

metadataStorePath(project, location, metadataStore)

metadataStorePath(project: string, location: string, metadataStore: string): string;

Return a fully-qualified metadataStore resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`metadataStore`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

modelDeploymentMonitoringJobPath(project, location, modelDeploymentMonitoringJob)

modelDeploymentMonitoringJobPath(project: string, location: string, modelDeploymentMonitoringJob: string): string;

Return a fully-qualified modelDeploymentMonitoringJob resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`modelDeploymentMonitoringJob`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

modelEvaluationPath(project, location, model, evaluation)

modelEvaluationPath(project: string, location: string, model: string, evaluation: string): string;

Return a fully-qualified modelEvaluation resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`model`	`string`
`evaluation`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

modelEvaluationSlicePath(project, location, model, evaluation, slice)

modelEvaluationSlicePath(project: string, location: string, model: string, evaluation: string, slice: string): string;

Return a fully-qualified modelEvaluationSlice resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`model`	`string`
`evaluation`	`string`
`slice`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

modelPath(project, location, model)

modelPath(project: string, location: string, model: string): string;

Return a fully-qualified model resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`model`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

pipelineJobPath(project, location, pipelineJob)

pipelineJobPath(project: string, location: string, pipelineJob: string): string;

Return a fully-qualified pipelineJob resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`pipelineJob`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

projectPath(project)

projectPath(project: string): string;

Return a fully-qualified project resource name string.

Parameter

Name	Description
`project`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

readTensorboardBlobData(request, options)

readTensorboardBlobData(request?: protos.google.cloud.aiplatform.v1beta1.IReadTensorboardBlobDataRequest, options?: CallOptions): gax.CancellableStream;

Gets bytes of TensorboardBlobs. This is to allow reading blob data stored in consumer project's Cloud Storage bucket without users having to obtain Cloud Storage access permission.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardBlobDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`gax.CancellableStream`	{Stream} An object stream which emits [ReadTensorboardBlobDataResponse] on 'data' event. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#server-streaming) for more details and examples.

Example


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardTimeSeries to list Blobs.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const timeSeries = 'abc123'
  /**
   *  IDs of the blobs to read.
   */
  // const blobIds = 'abc123'

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

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

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

    // Run request
    const stream = await aiplatformClient.readTensorboardBlobData(request);
    stream.on('data', (response) => { console.log(response) });
    stream.on('error', (err) => { throw(err) });
    stream.on('end', () => { /* API call completed */ });
  }

  callReadTensorboardBlobData();

readTensorboardTimeSeriesData(request, options)

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

Reads a TensorboardTimeSeries' data. By default, if the number of data points stored is less than 1000, all data is returned. Otherwise, 1000 data points is randomly selected from this time series and returned. This value can be changed by changing max_data_points, which can't be greater than 10k.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataResponse, (protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest \| undefined), {} \| undefined ]>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [ReadTensorboardTimeSeriesDataResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardTimeSeries to read data from.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const tensorboardTimeSeries = 'abc123'
  /**
   *  The maximum number of TensorboardTimeSeries' data to return.
   *  This value should be a positive integer.
   *  This value can be set to -1 to return all data.
   */
  // const maxDataPoints = 1234
  /**
   *  Reads the TensorboardTimeSeries' data that match the filter expression.
   */
  // const filter = 'abc123'

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

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

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

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

  callReadTensorboardTimeSeriesData();

readTensorboardTimeSeriesData(request, options, callback)

readTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

readTensorboardTimeSeriesData(request, callback)

readTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardTimeSeriesDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

readTensorboardUsage(request, options)

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

Returns a list of monthly active users for a given TensorBoard instance.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageResponse, (protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest \| undefined), {} \| undefined ]>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [ReadTensorboardUsageResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The name of the Tensorboard resource.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}`
   */
  // const tensorboard = 'abc123'

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

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

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

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

  callReadTensorboardUsage();

readTensorboardUsage(request, options, callback)

readTensorboardUsage(request: protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

readTensorboardUsage(request, callback)

readTensorboardUsage(request: protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageResponse, protos.google.cloud.aiplatform.v1beta1.IReadTensorboardUsageRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

savedQueryPath(project, location, dataset, savedQuery)

savedQueryPath(project: string, location: string, dataset: string, savedQuery: string): string;

Return a fully-qualified savedQuery resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`dataset`	`string`
`savedQuery`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

setIamPolicy(request, options, callback)

setIamPolicy(request: IamProtos.google.iam.v1.SetIamPolicyRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.Policy>;

Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

Parameters

Name	Description
`request`	`IamProtos.google.iam.v1.SetIamPolicyRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest \| null \| undefined, {} \| null \| undefined>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details.
`callback`	`Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest \| null \| undefined, {} \| null \| undefined>` The function which will be called with the result of the API call. The second parameter to the callback is an object representing [TestIamPermissionsResponse].

Returns

Type	Description
`Promise<IamProtos.google.iam.v1.Policy>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TestIamPermissionsResponse]. The promise has a method named "cancel" which cancels the ongoing API call.

specialistPoolPath(project, location, specialistPool)

specialistPoolPath(project: string, location: string, specialistPool: string): string;

Return a fully-qualified specialistPool resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`specialistPool`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

studyPath(project, location, study)

studyPath(project: string, location: string, study: string): string;

Return a fully-qualified study resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`study`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

tensorboardExperimentPath(project, location, tensorboard, experiment)

tensorboardExperimentPath(project: string, location: string, tensorboard: string, experiment: string): string;

Return a fully-qualified tensorboardExperiment resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`tensorboard`	`string`
`experiment`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

tensorboardPath(project, location, tensorboard)

tensorboardPath(project: string, location: string, tensorboard: string): string;

Return a fully-qualified tensorboard resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`tensorboard`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

tensorboardRunPath(project, location, tensorboard, experiment, run)

tensorboardRunPath(project: string, location: string, tensorboard: string, experiment: string, run: string): string;

Return a fully-qualified tensorboardRun resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`tensorboard`	`string`
`experiment`	`string`
`run`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

tensorboardTimeSeriesPath(project, location, tensorboard, experiment, run, timeSeries)

tensorboardTimeSeriesPath(project: string, location: string, tensorboard: string, experiment: string, run: string, timeSeries: string): string;

Return a fully-qualified tensorboardTimeSeries resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`tensorboard`	`string`
`experiment`	`string`
`run`	`string`
`timeSeries`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

testIamPermissions(request, options, callback)

testIamPermissions(request: IamProtos.google.iam.v1.TestIamPermissionsRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.TestIamPermissionsResponse>;

Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.

Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.

Parameters

Name	Description
`request`	`IamProtos.google.iam.v1.TestIamPermissionsRequest` The request object that will be sent.
`options`	`gax.CallOptions \| Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest \| null \| undefined, {} \| null \| undefined>` Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details.
`callback`	`Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest \| null \| undefined, {} \| null \| undefined>` The function which will be called with the result of the API call. The second parameter to the callback is an object representing [TestIamPermissionsResponse].

Returns

Type	Description
`Promise<IamProtos.google.iam.v1.TestIamPermissionsResponse>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TestIamPermissionsResponse]. The promise has a method named "cancel" which cancels the ongoing API call.

trainingPipelinePath(project, location, trainingPipeline)

trainingPipelinePath(project: string, location: string, trainingPipeline: string): string;

Return a fully-qualified trainingPipeline resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`trainingPipeline`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

trialPath(project, location, study, trial)

trialPath(project: string, location: string, study: string, trial: string): string;

Return a fully-qualified trial resource name string.

Parameters

Name	Description
`project`	`string`
`location`	`string`
`study`	`string`
`trial`	`string`

Returns

Type	Description
`string`	{string} Resource name string.

updateTensorboard(request, options)

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

Updates a Tensorboard.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardOperationMetadata>, 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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * 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 is overwritten if it's in the mask. If the
   *  user does not provide a mask then all fields are 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();

updateTensorboard(request, options, callback)

updateTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRequest`
`options`	`CallOptions`
`callback`	`Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardOperationMetadata>, protos.google.longrunning.IOperation \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboard(request, callback)

updateTensorboard(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRequest`
`callback`	`Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ITensorboard, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardOperationMetadata>, protos.google.longrunning.IOperation \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardExperiment(request, options)

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

Updates a TensorboardExperiment.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, (protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest \| 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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Field mask is used to specify the fields to be overwritten in the
   *  TensorboardExperiment resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field is overwritten if it's in the mask. If the
   *  user does not provide a mask then all fields are overwritten if new
   *  values are specified.
   */
  // const updateMask = {}
  /**
   *  Required. The TensorboardExperiment's `name` field is used to identify the
   *  TensorboardExperiment to be updated. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const tensorboardExperiment = {}

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

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

  async function callUpdateTensorboardExperiment() {
    // Construct request
    const request = {
      updateMask,
      tensorboardExperiment,
    };

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

  callUpdateTensorboardExperiment();

updateTensorboardExperiment(request, options, callback)

updateTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardExperiment(request, callback)

updateTensorboardExperiment(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardExperimentRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardRun(request, options)

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

Updates a TensorboardRun.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, (protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest \| 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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Field mask is used to specify the fields to be overwritten in the
   *  TensorboardRun resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field is overwritten if it's in the mask. If the
   *  user does not provide a mask then all fields are overwritten if new
   *  values are specified.
   */
  // const updateMask = {}
  /**
   *  Required. The TensorboardRun's `name` field is used to identify the
   *  TensorboardRun to be updated. Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const tensorboardRun = {}

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

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

  async function callUpdateTensorboardRun() {
    // Construct request
    const request = {
      updateMask,
      tensorboardRun,
    };

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

  callUpdateTensorboardRun();

updateTensorboardRun(request, options, callback)

updateTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardRun(request, callback)

updateTensorboardRun(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardRun, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardRunRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardTimeSeries(request, options)

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

Updates a TensorboardTimeSeries.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, (protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest \| 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


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Field mask is used to specify the fields to be overwritten in the
   *  TensorboardTimeSeries resource by the update.
   *  The fields specified in the update_mask are relative to the resource, not
   *  the full request. A field is overwritten if it's in the mask. If the
   *  user does not provide a mask then all fields are overwritten if new
   *  values are specified.
   */
  // const updateMask = {}
  /**
   *  Required. The TensorboardTimeSeries' `name` field is used to identify the
   *  TensorboardTimeSeries to be updated.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}/timeSeries/{time_series}`
   */
  // const tensorboardTimeSeries = {}

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

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

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

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

  callUpdateTensorboardTimeSeries();

updateTensorboardTimeSeries(request, options, callback)

updateTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

updateTensorboardTimeSeries(request, callback)

updateTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1beta1.IUpdateTensorboardTimeSeriesRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

writeTensorboardExperimentData(request, options)

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

Write time series data points of multiple TensorboardTimeSeries in multiple TensorboardRun's. If any data fail to be ingested, an error is returned.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataResponse, (protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest \| undefined), {} \| undefined ]>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [WriteTensorboardExperimentDataResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardExperiment to write data to.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}`
   */
  // const tensorboardExperiment = 'abc123'
  /**
   *  Required. Requests containing per-run TensorboardTimeSeries data to write.
   */
  // const writeRunDataRequests = 1234

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

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

  async function callWriteTensorboardExperimentData() {
    // Construct request
    const request = {
      tensorboardExperiment,
      writeRunDataRequests,
    };

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

  callWriteTensorboardExperimentData();

writeTensorboardExperimentData(request, options, callback)

writeTensorboardExperimentData(request: protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

writeTensorboardExperimentData(request, callback)

writeTensorboardExperimentData(request: protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardExperimentDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

writeTensorboardRunData(request, options)

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

Write time series data points into multiple TensorboardTimeSeries under a TensorboardRun. If any data fail to be ingested, an error is returned.

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest` The request object that will be sent.
`options`	`CallOptions` Call options. See CallOptions for more details.

Returns

Type	Description
`Promise<[ protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataResponse, (protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest \| undefined), {} \| undefined ]>`	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [WriteTensorboardRunDataResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example


  /**
   * This snippet has been automatically generated and should be regarded as a code template only.
   * It will require modifications to work.
   * It may require correct/in-range values for request initialization.
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the TensorboardRun to write data to.
   *  Format:
   *  `projects/{project}/locations/{location}/tensorboards/{tensorboard}/experiments/{experiment}/runs/{run}`
   */
  // const tensorboardRun = 'abc123'
  /**
   *  Required. The TensorboardTimeSeries data to write.
   *  Values with in a time series are indexed by their step value.
   *  Repeated writes to the same step will overwrite the existing value for that
   *  step.
   *  The upper limit of data points per write request is 5000.
   */
  // const timeSeriesData = 1234

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

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

  async function callWriteTensorboardRunData() {
    // Construct request
    const request = {
      tensorboardRun,
      timeSeriesData,
    };

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

  callWriteTensorboardRunData();

writeTensorboardRunData(request, options, callback)

writeTensorboardRunData(request: protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest`
`options`	`CallOptions`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`

writeTensorboardRunData(request, callback)

writeTensorboardRunData(request: protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
`request`	`protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest`
`callback`	`Callback<protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataResponse, protos.google.cloud.aiplatform.v1beta1.IWriteTensorboardRunDataRequest \| null \| undefined, {} \| null \| undefined>`

Returns

Type	Description
`void`