Class v1.TensorboardServiceClient (3.7.0)

Package

Constructors

(constructor)(opts, gaxInstance)

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

Properties

apiEndpoint

static get apiEndpoint(): string;

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;

scopes

static get scopes(): string[];

servicePath

static get servicePath(): string;

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;

annotationSpecPath(project, location, dataset, annotationSpec)

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

artifactPath(project, location, metadataStore, artifact)

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

batchCreateTensorboardRuns(request, options)

batchCreateTensorboardRuns(request?: protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsResponse,
        (protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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 = [1,2,3,4]

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1;

  // 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.v1.IBatchCreateTensorboardRunsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>): void;

batchCreateTensorboardRuns(request, callback)

batchCreateTensorboardRuns(request: protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsResponse, protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardRunsRequest | null | undefined, {} | null | undefined>): void;

batchCreateTensorboardTimeSeries(request, options)

batchCreateTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesResponse,
        (protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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 = [1,2,3,4]

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1;

  // 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.v1.IBatchCreateTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

batchCreateTensorboardTimeSeries(request, callback)

batchCreateTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesResponse, protos.google.cloud.aiplatform.v1.IBatchCreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

batchPredictionJobPath(project, location, batchPredictionJob)

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

batchReadTensorboardTimeSeriesData(request, options)

batchReadTensorboardTimeSeriesData(request?: protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataResponse,
        (protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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.v1.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 = ['abc','def']

  // Imports the Aiplatform library
  const {TensorboardServiceClient} = require('@google-cloud/aiplatform').v1;

  // 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.v1.IBatchReadTensorboardTimeSeriesDataRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): void;

batchReadTensorboardTimeSeriesData(request, callback)

batchReadTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataResponse, protos.google.cloud.aiplatform.v1.IBatchReadTensorboardTimeSeriesDataRequest | null | undefined, {} | null | undefined>): 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>;

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

checkCreateTensorboardProgress(name)

checkCreateTensorboardProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Tensorboard, protos.google.cloud.aiplatform.v1.CreateTensorboardOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.DeleteOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.DeleteOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.DeleteOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.DeleteOperationMetadata>>;

  /**
   * 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').v1;

  // 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.v1.Tensorboard, protos.google.cloud.aiplatform.v1.UpdateTensorboardOperationMetadata>>;

  /**
   * 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').v1;

  // 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>;

contextPath(project, location, metadataStore, context)

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

createTensorboard(request, options)

createTensorboard(request?: protos.google.cloud.aiplatform.v1.ICreateTensorboardRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.ITensorboard, protos.google.cloud.aiplatform.v1.ICreateTensorboardOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.ICreateTensorboardRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.ITensorboard, protos.google.cloud.aiplatform.v1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

createTensorboard(request, callback)

createTensorboard(request: protos.google.cloud.aiplatform.v1.ICreateTensorboardRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.ITensorboard, protos.google.cloud.aiplatform.v1.ICreateTensorboardOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

createTensorboardExperiment(request, options)

createTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1.ICreateTensorboardExperimentRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardExperiment,
        (protos.google.cloud.aiplatform.v1.ICreateTensorboardExperimentRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.ICreateTensorboardExperimentRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

createTensorboardExperiment(request, callback)

createTensorboardExperiment(request: protos.google.cloud.aiplatform.v1.ICreateTensorboardExperimentRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1.ICreateTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

createTensorboardRun(request, options)

createTensorboardRun(request?: protos.google.cloud.aiplatform.v1.ICreateTensorboardRunRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardRun,
        (protos.google.cloud.aiplatform.v1.ICreateTensorboardRunRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.ICreateTensorboardRunRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardRun, protos.google.cloud.aiplatform.v1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

createTensorboardRun(request, callback)

createTensorboardRun(request: protos.google.cloud.aiplatform.v1.ICreateTensorboardRunRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardRun, protos.google.cloud.aiplatform.v1.ICreateTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

createTensorboardTimeSeries(request, options)

createTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1.ICreateTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries,
        (protos.google.cloud.aiplatform.v1.ICreateTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.ICreateTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

createTensorboardTimeSeries(request, callback)

createTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.ICreateTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1.ICreateTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

customJobPath(project, location, customJob)

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

dataItemPath(project, location, dataset, dataItem)

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

dataLabelingJobPath(project, location, dataLabelingJob)

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

datasetPath(project, location, dataset)

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

datasetVersionPath(project, location, dataset, datasetVersion)

datasetVersionPath(project: string, location: string, dataset: string, datasetVersion: string): 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>;

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

deleteTensorboard(request, options)

deleteTensorboard(request?: protos.google.cloud.aiplatform.v1.IDeleteTensorboardRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IDeleteTensorboardRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboard(request, callback)

deleteTensorboard(request: protos.google.cloud.aiplatform.v1.IDeleteTensorboardRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardExperiment(request, options)

deleteTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1.IDeleteTensorboardExperimentRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IDeleteTensorboardExperimentRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardExperiment(request, callback)

deleteTensorboardExperiment(request: protos.google.cloud.aiplatform.v1.IDeleteTensorboardExperimentRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardRun(request, options)

deleteTensorboardRun(request?: protos.google.cloud.aiplatform.v1.IDeleteTensorboardRunRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IDeleteTensorboardRunRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardRun(request, callback)

deleteTensorboardRun(request: protos.google.cloud.aiplatform.v1.IDeleteTensorboardRunRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardTimeSeries(request, options)

deleteTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1.IDeleteTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IDeleteTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

deleteTensorboardTimeSeries(request, callback)

deleteTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.IDeleteTensorboardTimeSeriesRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

entityTypePath(project, location, featurestore, entityType)

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

executionPath(project, location, metadataStore, execution)

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

exportTensorboardTimeSeriesData(request, options)

exportTensorboardTimeSeriesData(request?: protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITimeSeriesDataPoint[],
        protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest | null,
        protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataResponse
    ]>;

exportTensorboardTimeSeriesData(request, options, callback)

exportTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITimeSeriesDataPoint>): void;

exportTensorboardTimeSeriesData(request, callback)

exportTensorboardTimeSeriesData(request: protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITimeSeriesDataPoint>): void;

exportTensorboardTimeSeriesDataAsync(request, options)

exportTensorboardTimeSeriesDataAsync(request?: protos.google.cloud.aiplatform.v1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ITimeSeriesDataPoint>;

  /**
   * 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
   *  ExportTensorboardTimeSeriesData google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  ExportTensorboardTimeSeriesData google.cloud.aiplatform.v1.TensorboardService.ExportTensorboardTimeSeriesData 
   *  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').v1;

  // 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.v1.IExportTensorboardTimeSeriesDataRequest, options?: CallOptions): Transform;

featureGroupPath(project, location, featureGroup)

featureGroupPath(project: string, location: string, featureGroup: string): string;

featureOnlineStorePath(project, location, featureOnlineStore)

featureOnlineStorePath(project: string, location: string, featureOnlineStore: string): string;

featurestorePath(project, location, featurestore)

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

featureViewPath(project, location, featureOnlineStore, featureView)

featureViewPath(project: string, location: string, featureOnlineStore: string, featureView: string): string;

featureViewSyncPath(project, location, featureOnlineStore, featureView)

featureViewSyncPath(project: string, location: string, featureOnlineStore: string, featureView: string): 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]>;

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>;

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]>;

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

getProjectId()

getProjectId(): Promise<string>;

getProjectId(callback)

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

getTensorboard(request, options)

getTensorboard(request?: protos.google.cloud.aiplatform.v1.IGetTensorboardRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboard,
        protos.google.cloud.aiplatform.v1.IGetTensorboardRequest | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IGetTensorboardRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboard, protos.google.cloud.aiplatform.v1.IGetTensorboardRequest | null | undefined, {} | null | undefined>): void;

getTensorboard(request, callback)

getTensorboard(request: protos.google.cloud.aiplatform.v1.IGetTensorboardRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboard, protos.google.cloud.aiplatform.v1.IGetTensorboardRequest | null | undefined, {} | null | undefined>): void;

getTensorboardExperiment(request, options)

getTensorboardExperiment(request?: protos.google.cloud.aiplatform.v1.IGetTensorboardExperimentRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardExperiment,
        (protos.google.cloud.aiplatform.v1.IGetTensorboardExperimentRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IGetTensorboardExperimentRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

getTensorboardExperiment(request, callback)

getTensorboardExperiment(request: protos.google.cloud.aiplatform.v1.IGetTensorboardExperimentRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardExperiment, protos.google.cloud.aiplatform.v1.IGetTensorboardExperimentRequest | null | undefined, {} | null | undefined>): void;

getTensorboardRun(request, options)

getTensorboardRun(request?: protos.google.cloud.aiplatform.v1.IGetTensorboardRunRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardRun,
        protos.google.cloud.aiplatform.v1.IGetTensorboardRunRequest | undefined,
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IGetTensorboardRunRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardRun, protos.google.cloud.aiplatform.v1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

getTensorboardRun(request, callback)

getTensorboardRun(request: protos.google.cloud.aiplatform.v1.IGetTensorboardRunRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardRun, protos.google.cloud.aiplatform.v1.IGetTensorboardRunRequest | null | undefined, {} | null | undefined>): void;

getTensorboardTimeSeries(request, options)

getTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1.IGetTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries,
        (protos.google.cloud.aiplatform.v1.IGetTensorboardTimeSeriesRequest | undefined),
        {} | undefined
    ]>;

  /**
   * 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').v1;

  // 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.v1.IGetTensorboardTimeSeriesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

getTensorboardTimeSeries(request, callback)

getTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.IGetTensorboardTimeSeriesRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries, protos.google.cloud.aiplatform.v1.IGetTensorboardTimeSeriesRequest | null | undefined, {} | null | undefined>): void;

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

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

indexEndpointPath(project, location, indexEndpoint)

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

indexPath(project, location, index)

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

initialize()

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

listLocationsAsync(request, options)

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

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>;

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

listTensorboardExperiments(request, options)

listTensorboardExperiments(request?: protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardExperiment[],
        protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest | null,
        protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsResponse
    ]>;

listTensorboardExperiments(request, options, callback)

listTensorboardExperiments(request: protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardExperiment>): void;

listTensorboardExperiments(request, callback)

listTensorboardExperiments(request: protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardExperiment>): void;

listTensorboardExperimentsAsync(request, options)

listTensorboardExperimentsAsync(request?: protos.google.cloud.aiplatform.v1.IListTensorboardExperimentsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ITensorboardExperiment>;

  /**
   * 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.v1.TensorboardService.ListTensorboardExperiments 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardExperiments google.cloud.aiplatform.v1.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').v1;

  // 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.v1.IListTensorboardExperimentsRequest, options?: CallOptions): Transform;

listTensorboardRuns(request, options)

listTensorboardRuns(request?: protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardRun[],
        protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest | null,
        protos.google.cloud.aiplatform.v1.IListTensorboardRunsResponse
    ]>;

listTensorboardRuns(request, options, callback)

listTensorboardRuns(request: protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardRun>): void;

listTensorboardRuns(request, callback)

listTensorboardRuns(request: protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardRunsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardRun>): void;

listTensorboardRunsAsync(request, options)

listTensorboardRunsAsync(request?: protos.google.cloud.aiplatform.v1.IListTensorboardRunsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ITensorboardRun>;

  /**
   * 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.v1.TensorboardService.ListTensorboardRuns 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardRuns google.cloud.aiplatform.v1.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').v1;

  // 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.v1.IListTensorboardRunsRequest, options?: CallOptions): Transform;

listTensorboards(request, options)

listTensorboards(request?: protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboard[],
        protos.google.cloud.aiplatform.v1.IListTensorboardsRequest | null,
        protos.google.cloud.aiplatform.v1.IListTensorboardsResponse
    ]>;

listTensorboards(request, options, callback)

listTensorboards(request: protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboard>): void;

listTensorboards(request, callback)

listTensorboards(request: protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, protos.google.cloud.aiplatform.v1.IListTensorboardsResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboard>): void;

listTensorboardsAsync(request, options)

listTensorboardsAsync(request?: protos.google.cloud.aiplatform.v1.IListTensorboardsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ITensorboard>;

  /**
   * 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.v1.TensorboardService.ListTensorboards 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboards google.cloud.aiplatform.v1.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').v1;

  // 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.v1.IListTensorboardsRequest, options?: CallOptions): Transform;

listTensorboardTimeSeries(request, options)

listTensorboardTimeSeries(request?: protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries[],
        protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest | null,
        protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesResponse
    ]>;

listTensorboardTimeSeries(request, options, callback)

listTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries>): void;

listTensorboardTimeSeries(request, callback)

listTensorboardTimeSeries(request: protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries>): void;

listTensorboardTimeSeriesAsync(request, options)

listTensorboardTimeSeriesAsync(request?: protos.google.cloud.aiplatform.v1.IListTensorboardTimeSeriesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ITensorboardTimeSeries>;

  /**
   * 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.v1.TensorboardService.ListTensorboardTimeSeries 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other parameters provided to
   *  TensorboardService.ListTensorboardTimeSeries google.cloud.aiplatform.v1.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').v1;

  // 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.v1.IListTensorboardTimeSeriesRequest, options?: CallOptions): Transform;

locationPath(project, location)

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

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

matchDatasetFromDatasetVersionName(datasetVersionName)

matchDatasetFromDatasetVersionName(datasetVersionName: string): string | number;

matchDatasetFromSavedQueryName(savedQueryName)

matchDatasetFromSavedQueryName(savedQueryName: string): string | number;

matchDatasetVersionFromDatasetVersionName(datasetVersionName)

matchDatasetVersionFromDatasetVersionName(datasetVersionName: string): string | number;

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName)

matchEndpointFromProjectLocationEndpointName(projectLocationEndpointName: string): string | number;

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchEntityTypeFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeatureFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchFeatureGroupFromFeatureGroupName(featureGroupName)

matchFeatureGroupFromFeatureGroupName(featureGroupName: string): string | number;

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName)

matchFeatureGroupFromProjectLocationFeatureGroupFeatureName(projectLocationFeatureGroupFeatureName: string): string | number;

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName)

matchFeatureOnlineStoreFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;

matchFeatureOnlineStoreFromFeatureViewName(featureViewName)

matchFeatureOnlineStoreFromFeatureViewName(featureViewName: string): string | number;

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName)

matchFeatureOnlineStoreFromFeatureViewSyncName(featureViewSyncName: string): string | number;

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName)

matchFeaturestoreFromProjectLocationFeaturestoreEntityTypeFeatureName(projectLocationFeaturestoreEntityTypeFeatureName: string): string | number;

matchFeatureViewFromFeatureViewName(featureViewName)

matchFeatureViewFromFeatureViewName(featureViewName: string): string | number;

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName)

matchFeatureViewFromFeatureViewSyncName(featureViewSyncName: string): string | number;

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

matchIndexEndpointFromIndexEndpointName(indexEndpointName)

matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

matchLocationFromDatasetVersionName(datasetVersionName)

matchLocationFromDatasetVersionName(datasetVersionName: string): string | number;

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

matchLocationFromFeatureGroupName(featureGroupName)

matchLocationFromFeatureGroupName(featureGroupName: string): string | number;

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName)

matchLocationFromFeatureOnlineStoreName(featureOnlineStoreName: string): string | number;