Class v1beta1.TensorboardServiceClient (1.16.0)

Package

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Properties

apiEndpoint

static get apiEndpoint(): string;

auth

auth: gax.GoogleAuth;

descriptors

descriptors: Descriptors;

innerApiCalls

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

operationsClient

operationsClient: gax.OperationsClient;

pathTemplates

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

port

static get port(): number;

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

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

batchPredictionJobPath(project, location, batchPredictionJob)

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

  /**
   * 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;

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;

checkCreateTensorboardProgress(name)

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

  /**
   * 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>>;

  /**
   * 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>>;

  /**
   * 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>>;

  /**
   * 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>>;

  /**
   * 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>>;

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

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

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

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

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

  callUpdateTensorboard();

close()

close(): Promise<void>;

contextPath(project, location, metadataStore, context)

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

  /**
   * 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;

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;

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
    ]>;

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

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

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

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

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

  callCreateTensorboardExperiment();

createTensorboardExperiment(request, options, callback)

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

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;

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
    ]>;

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

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

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

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

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

  callCreateTensorboardRun();

createTensorboardRun(request, options, callback)

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

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;

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
    ]>;

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

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

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

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

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

  callCreateTensorboardTimeSeries();

createTensorboardTimeSeries(request, options, callback)

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

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;

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;

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
    ]>;

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

endpointPath(project, location, endpoint)

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

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

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;

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;

exportTensorboardTimeSeriesDataAsync(request, options)

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

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

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

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

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

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

  callExportTensorboardTimeSeriesData();

exportTensorboardTimeSeriesDataStream(request, options)

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

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

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

featurestorePath(project, location, featurestore)

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

getProjectId()

getProjectId(): Promise<string>;

getProjectId(callback)

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

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

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
    ]>;

  /**
   * 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;

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;

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;
    }>;

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
    ]>;

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;

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;

listTensorboardExperimentsAsync(request, options)

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

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

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

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

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

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

  callListTensorboardExperiments();

listTensorboardExperimentsStream(request, options)

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

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
    ]>;

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;

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;

listTensorboardRunsAsync(request, options)

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

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

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

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

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

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

  callListTensorboardRuns();

listTensorboardRunsStream(request, options)

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

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
    ]>;

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;

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;

listTensorboardsAsync(request, options)

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

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

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

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

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

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

  callListTensorboards();

listTensorboardsStream(request, options)

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

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
    ]>;

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;

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;

listTensorboardTimeSeriesAsync(request, options)

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

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

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

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

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

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

  callListTensorboardTimeSeries();

listTensorboardTimeSeriesStream(request, options)

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

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;

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: 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;

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: 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;

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

matchModelFromModelEvaluationName(modelEvaluationName)

matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

matchProjectFromEndpointName(endpointName)

matchProjectFromEndpointName(endpointName: string): string | number;

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

matchProjectFromFeatureName(featureName)

matchProjectFromFeatureName(featureName: string): string | number;

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;