Class v1.DatasetServiceClient (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;

datasetServiceStub

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

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;

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;

batchPredictionJobPath(project, location, batchPredictionJob)

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

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: ''});

checkCreateDatasetProgress(name)

checkCreateDatasetProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Dataset, protos.google.cloud.aiplatform.v1.CreateDatasetOperationMetadata>>;

  /**
   * 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 Dataset in.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Dataset to create.
   */
  // const dataset = {}

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

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

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

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

  callCreateDataset();

checkCreateDatasetVersionProgress(name)

checkCreateDatasetVersionProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.DatasetVersion, protos.google.cloud.aiplatform.v1.CreateDatasetVersionOperationMetadata>>;

  /**
   * 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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The version to be created. The same CMEK policies with the
   *  original Dataset will be applied the dataset version. So here we don't need
   *  to specify the EncryptionSpecType here.
   */
  // const datasetVersion = {}

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

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

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

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

  callCreateDatasetVersion();

checkDeleteDatasetProgress(name)

checkDeleteDatasetProgress(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 resource name of the Dataset to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteDataset();

checkDeleteDatasetVersionProgress(name)

checkDeleteDatasetVersionProgress(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 resource name of the Dataset version to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteDatasetVersion();

checkDeleteSavedQueryProgress(name)

checkDeleteSavedQueryProgress(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 resource name of the SavedQuery to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteSavedQuery();

checkExportDataProgress(name)

checkExportDataProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportDataResponse, protos.google.cloud.aiplatform.v1.ExportDataOperationMetadata>>;

  /**
   * 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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location.
   */
  // const exportConfig = {}

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

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

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

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

  callExportData();

checkImportDataProgress(name)

checkImportDataProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportDataResponse, protos.google.cloud.aiplatform.v1.ImportDataOperationMetadata>>;

  /**
   * 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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'
  /**
   *  Required. The desired input locations. The contents of all input locations
   *  will be imported in one batch.
   */
  // const importConfigs = [1,2,3,4]

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

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

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

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

  callImportData();

checkRestoreDatasetVersionProgress(name)

checkRestoreDatasetVersionProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.DatasetVersion, protos.google.cloud.aiplatform.v1.RestoreDatasetVersionOperationMetadata>>;

  /**
   * 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 DatasetVersion resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`
   */
  // const name = 'abc123'

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

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

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

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

  callRestoreDatasetVersion();

close()

close(): Promise<void>;

contextPath(project, location, metadataStore, context)

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

createDataset(request, options)

createDataset(request?: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>,
        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 Dataset in.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Dataset to create.
   */
  // const dataset = {}

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

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

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

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

  callCreateDataset();

createDataset(request, options, callback)

createDataset(request: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

createDataset(request, callback)

createDataset(request: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

createDatasetVersion(request, options)

createDatasetVersion(request?: protos.google.cloud.aiplatform.v1.ICreateDatasetVersionRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IDatasetVersion, protos.google.cloud.aiplatform.v1.ICreateDatasetVersionOperationMetadata>,
        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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The version to be created. The same CMEK policies with the
   *  original Dataset will be applied the dataset version. So here we don't need
   *  to specify the EncryptionSpecType here.
   */
  // const datasetVersion = {}

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

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

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

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

  callCreateDatasetVersion();

createDatasetVersion(request, options, callback)

createDatasetVersion(request: protos.google.cloud.aiplatform.v1.ICreateDatasetVersionRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDatasetVersion, protos.google.cloud.aiplatform.v1.ICreateDatasetVersionOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

createDatasetVersion(request, callback)

createDatasetVersion(request: protos.google.cloud.aiplatform.v1.ICreateDatasetVersionRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDatasetVersion, protos.google.cloud.aiplatform.v1.ICreateDatasetVersionOperationMetadata>, protos.google.longrunning.IOperation | 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;

deleteDataset(request, options)

deleteDataset(request?: protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest, 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 resource name of the Dataset to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteDataset();

deleteDataset(request, options, callback)

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

deleteDataset(request, callback)

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

deleteDatasetVersion(request, options)

deleteDatasetVersion(request?: protos.google.cloud.aiplatform.v1.IDeleteDatasetVersionRequest, 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 resource name of the Dataset version to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteDatasetVersion();

deleteDatasetVersion(request, options, callback)

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

deleteDatasetVersion(request, callback)

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

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: ''});

deleteSavedQuery(request, options)

deleteSavedQuery(request?: protos.google.cloud.aiplatform.v1.IDeleteSavedQueryRequest, 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 resource name of the SavedQuery to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`
   */
  // const name = 'abc123'

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

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

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

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

  callDeleteSavedQuery();

deleteSavedQuery(request, options, callback)

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

deleteSavedQuery(request, callback)

deleteSavedQuery(request: protos.google.cloud.aiplatform.v1.IDeleteSavedQueryRequest, 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;

exportData(request, options)

exportData(request?: protos.google.cloud.aiplatform.v1.IExportDataRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>,
        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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location.
   */
  // const exportConfig = {}

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

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

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

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

  callExportData();

exportData(request, options, callback)

exportData(request: protos.google.cloud.aiplatform.v1.IExportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

exportData(request, callback)

exportData(request: protos.google.cloud.aiplatform.v1.IExportDataRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

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;

getAnnotationSpec(request, options)

getAnnotationSpec(request?: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IAnnotationSpec,
        protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | 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 AnnotationSpec resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`
   */
  // const name = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

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

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

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

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

  callGetAnnotationSpec();

getAnnotationSpec(request, options, callback)

getAnnotationSpec(request: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;

getAnnotationSpec(request, callback)

getAnnotationSpec(request: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;

getDataset(request, options)

getDataset(request?: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IDataset,
        protos.google.cloud.aiplatform.v1.IGetDatasetRequest | 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 Dataset resource.
   */
  // const name = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

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

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

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

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

  callGetDataset();

getDataset(request, options, callback)

getDataset(request: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;

getDataset(request, callback)

getDataset(request: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;

getDatasetVersion(request, options)

getDatasetVersion(request?: protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IDatasetVersion,
        protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest | 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 Dataset version to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/datasetVersions/{dataset_version}`
   */
  // const name = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}

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

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

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

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

  callGetDatasetVersion();

getDatasetVersion(request, options, callback)

getDatasetVersion(request: protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IDatasetVersion, protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest | null | undefined, {} | null | undefined>): void;

getDatasetVersion(request, callback)

getDatasetVersion(request: protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IDatasetVersion, protos.google.cloud.aiplatform.v1.IGetDatasetVersionRequest | null | undefined, {} | null | undefined>): void;

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;

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

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

importData(request, options)

importData(request?: protos.google.cloud.aiplatform.v1.IImportDataRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>,
        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 Dataset resource.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const name = 'abc123'
  /**
   *  Required. The desired input locations. The contents of all input locations
   *  will be imported in one batch.
   */
  // const importConfigs = [1,2,3,4]

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

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

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

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

  callImportData();

importData(request, options, callback)

importData(request: protos.google.cloud.aiplatform.v1.IImportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

importData(request, callback)

importData(request: protos.google.cloud.aiplatform.v1.IImportDataRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

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;
    }>;

listAnnotations(request, options)

listAnnotations(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IAnnotation[],
        protos.google.cloud.aiplatform.v1.IListAnnotationsRequest | null,
        protos.google.cloud.aiplatform.v1.IListAnnotationsResponse
    ]>;

listAnnotations(request, options, callback)

listAnnotations(request: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>): void;

listAnnotations(request, callback)

listAnnotations(request: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>): void;

listAnnotationsAsync(request, options)

listAnnotationsAsync(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IAnnotation>;

  /**
   * 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 DataItem to list Annotations from.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`
   */
  // const parent = 'abc123'
  /**
   *  The standard list filter.
   */
  // const filter = 'abc123'
  /**
   *  The standard list page size.
   */
  // const pageSize = 1234
  /**
   *  The standard list page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   */
  // const orderBy = 'abc123'

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

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

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

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

  callListAnnotations();

listAnnotationsStream(request, options)

listAnnotationsStream(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): Transform;

listDataItems(request, options)

listDataItems(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IDataItem[],
        protos.google.cloud.aiplatform.v1.IListDataItemsRequest | null,
        protos.google.cloud.aiplatform.v1.IListDataItemsResponse
    ]>;

listDataItems(request, options, callback)

listDataItems(request: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>): void;

listDataItems(request, callback)

listDataItems(request: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>): void;

listDataItemsAsync(request, options)

listDataItemsAsync(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDataItem>;

  /**
   * 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 Dataset to list DataItems from.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const parent = 'abc123'
  /**
   *  The standard list filter.
   */
  // const filter = 'abc123'
  /**
   *  The standard list page size.
   */
  // const pageSize = 1234
  /**
   *  The standard list page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   */
  // const orderBy = 'abc123'

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

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

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

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

  callListDataItems();

listDataItemsStream(request, options)

listDataItemsStream(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): Transform;

listDatasets(request, options)

listDatasets(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IDataset[],
        protos.google.cloud.aiplatform.v1.IListDatasetsRequest | null,
        protos.google.cloud.aiplatform.v1.IListDatasetsResponse
    ]>;

listDatasets(request, options, callback)

listDatasets(request: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>): void;

listDatasets(request, callback)

listDatasets(request: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>): void;

listDatasetsAsync(request, options)

listDatasetsAsync(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDataset>;

  /**
   * 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 Dataset's parent resource.
   *  Format: `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  An expression for filtering the results of the request. For field names
   *  both snake_case and camelCase are supported.
   *    * `display_name`: supports = and !=
   *    * `metadata_schema_uri`: supports = and !=
   *    * `labels` supports general map functions that is:
   *      * `labels.key=value` - key:value equality
   *      * `labels.key:* or labels:key - key existence
   *      * A key including a space must be quoted. `labels."a key"`.
   *  Some examples:
   *    * `displayName="myDisplayName"`
   *    * `labels.myKey="myValue"`
   */
  // const filter = 'abc123'
  /**
   *  The standard list page size.
   */
  // const pageSize = 1234
  /**
   *  The standard list page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   *  Supported fields:
   *    * `display_name`
   *    * `create_time`
   *    * `update_time`
   */
  // const orderBy = 'abc123'

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

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

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

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

  callListDatasets();

listDatasetsStream(request, options)

listDatasetsStream(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): Transform;

listDatasetVersions(request, options)

listDatasetVersions(request?: protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IDatasetVersion[],
        protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest | null,
        protos.google.cloud.aiplatform.v1.IListDatasetVersionsResponse
    ]>;

listDatasetVersions(request, options, callback)

listDatasetVersions(request: protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, protos.google.cloud.aiplatform.v1.IListDatasetVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDatasetVersion>): void;

listDatasetVersions(request, callback)

listDatasetVersions(request: protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, protos.google.cloud.aiplatform.v1.IListDatasetVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDatasetVersion>): void;

listDatasetVersionsAsync(request, options)

listDatasetVersionsAsync(request?: protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDatasetVersion>;

  /**
   * 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 Dataset to list DatasetVersions from.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const parent = 'abc123'
  /**
   *  Optional. The standard list filter.
   */
  // const filter = 'abc123'
  /**
   *  Optional. The standard list page size.
   */
  // const pageSize = 1234
  /**
   *  Optional. The standard list page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Optional. Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  Optional. A comma-separated list of fields to order by, sorted in ascending
   *  order. Use "desc" after a field name for descending.
   */
  // const orderBy = 'abc123'

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

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

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

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

  callListDatasetVersions();

listDatasetVersionsStream(request, options)

listDatasetVersionsStream(request?: protos.google.cloud.aiplatform.v1.IListDatasetVersionsRequest, options?: CallOptions): Transform;

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)

listSavedQueries(request, options)

listSavedQueries(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ISavedQuery[],
        protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest | null,
        protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse
    ]>;

listSavedQueries(request, options, callback)

listSavedQueries(request: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>): void;

listSavedQueries(request, callback)

listSavedQueries(request: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>): void;

listSavedQueriesAsync(request, options)

listSavedQueriesAsync(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ISavedQuery>;

  /**
   * 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 Dataset to list SavedQueries from.
   *  Format:
   *  `projects/{project}/locations/{location}/datasets/{dataset}`
   */
  // const parent = 'abc123'
  /**
   *  The standard list filter.
   */
  // const filter = 'abc123'
  /**
   *  The standard list page size.
   */
  // const pageSize = 1234
  /**
   *  The standard list page token.
   */
  // const pageToken = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const readMask = {}
  /**
   *  A comma-separated list of fields to order by, sorted in ascending order.
   *  Use "desc" after a field name for descending.
   */
  // const orderBy = 'abc123'

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

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

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

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

  callListSavedQueries();

listSavedQueriesStream(request, options)

listSavedQueriesStream(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, 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;

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

matchLocationFromFeatureViewName(featureViewName)

matchLocationFromFeatureViewName(featureViewName: string): string | number;

matchLocationFromFeatureViewSyncName(featureViewSyncName)

matchLocationFromFeatureViewSyncName(featureViewSyncName: 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;

matchLocationFromNasJobName(nasJobName)

matchLocationFromNasJobName(nasJobName: string): string | number;

matchLocationFromNasTrialDetailName(nasTrialDetailName)

matchLocationFromNasTrialDetailName(nasTrialDetailName: string): string | number;

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;