auto_ml_client.ts

// Copyright 2021 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
//
// ** This file is automatically generated by gapic-generator-typescript. **
// ** https://github.com/googleapis/gapic-generator-typescript **
// ** All changes to this file may be overwritten. **

/* global window */
import * as gax from 'google-gax';
import {
  Callback,
  CallOptions,
  Descriptors,
  ClientOptions,
  LROperation,
  PaginationCallback,
  GaxCall,
} from 'google-gax';

import {Transform} from 'stream';
import {RequestType} from 'google-gax/build/src/apitypes';
import * as protos from '../../protos/protos';
import jsonProtos = require('../../protos/protos.json');
/**
 * Client JSON configuration object, loaded from
 * `src/v1/auto_ml_client_config.json`.
 * This file defines retry strategy and timeouts for all API methods in this library.
 */
import * as gapicConfig from './auto_ml_client_config.json';
import {operationsProtos} from 'google-gax';
const version = require('../../../package.json').version;

/**
 *  AutoML Server API.
 *
 *  The resource names are assigned by the server.
 *  The server never reuses names that it has created after the resources with
 *  those names are deleted.
 *
 *  An ID of a resource is the last element of the item's resource name. For
 *  `projects/{project_id}/locations/{location_id}/datasets/{dataset_id}`, then
 *  the id for the item is `{dataset_id}`.
 *
 *  Currently the only supported `location_id` is "us-central1".
 *
 *  On any input that is documented to expect a string parameter in
 *  snake_case or kebab-case, either of those cases is accepted.
 * @class
 * @memberof v1
 */
export class AutoMlClient {
  private _terminated = false;
  private _opts: ClientOptions;
  private _providedCustomServicePath: boolean;
  private _gaxModule: typeof gax | typeof gax.fallback;
  private _gaxGrpc: gax.GrpcClient | gax.fallback.GrpcClient;
  private _protos: {};
  private _defaults: {[method: string]: gax.CallSettings};
  auth: gax.GoogleAuth;
  descriptors: Descriptors = {
    page: {},
    stream: {},
    longrunning: {},
    batching: {},
  };
  warn: (code: string, message: string, warnType?: string) => void;
  innerApiCalls: {[name: string]: Function};
  pathTemplates: {[name: string]: gax.PathTemplate};
  operationsClient: gax.OperationsClient;
  autoMlStub?: Promise<{[name: string]: Function}>;

  /**
   * Construct an instance of AutoMlClient.
   *
   * @param {object} [options] - The configuration object.
   * The options accepted by the constructor are described in detail
   * in [this document](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#creating-the-client-instance).
   * The common options are:
   * @param {object} [options.credentials] - Credentials object.
   * @param {string} [options.credentials.client_email]
   * @param {string} [options.credentials.private_key]
   * @param {string} [options.email] - Account email address. Required when
   *     using a .pem or .p12 keyFilename.
   * @param {string} [options.keyFilename] - Full path to the a .json, .pem, or
   *     .p12 key downloaded from the Google Developers Console. If you provide
   *     a path to a JSON file, the projectId option below is not necessary.
   *     NOTE: .pem and .p12 require you to specify options.email as well.
   * @param {number} [options.port] - The port on which to connect to
   *     the remote host.
   * @param {string} [options.projectId] - The project ID from the Google
   *     Developer's Console, e.g. 'grape-spaceship-123'. We will also check
   *     the environment variable GCLOUD_PROJECT for your project ID. If your
   *     app is running in an environment which supports
   *     {@link https://developers.google.com/identity/protocols/application-default-credentials Application Default Credentials},
   *     your project ID will be detected automatically.
   * @param {string} [options.apiEndpoint] - The domain name of the
   *     API remote host.
   * @param {gax.ClientConfig} [options.clientConfig] - Client configuration override.
   *     Follows the structure of {@link gapicConfig}.
   * @param {boolean} [options.fallback] - Use HTTP fallback mode.
   *     In fallback mode, a special browser-compatible transport implementation is used
   *     instead of gRPC transport. In browser context (if the `window` object is defined)
   *     the fallback mode is enabled automatically; set `options.fallback` to `false`
   *     if you need to override this behavior.
   */
  constructor(opts?: ClientOptions) {
    // Ensure that options include all the required fields.
    const staticMembers = this.constructor as typeof AutoMlClient;
    const servicePath =
      opts?.servicePath || opts?.apiEndpoint || staticMembers.servicePath;
    this._providedCustomServicePath = !!(
      opts?.servicePath || opts?.apiEndpoint
    );
    const port = opts?.port || staticMembers.port;
    const clientConfig = opts?.clientConfig ?? {};
    const fallback =
      opts?.fallback ??
      (typeof window !== 'undefined' && typeof window?.fetch === 'function');
    opts = Object.assign({servicePath, port, clientConfig, fallback}, opts);

    // If scopes are unset in options and we're connecting to a non-default endpoint, set scopes just in case.
    if (servicePath !== staticMembers.servicePath && !('scopes' in opts)) {
      opts['scopes'] = staticMembers.scopes;
    }

    // Choose either gRPC or proto-over-HTTP implementation of google-gax.
    this._gaxModule = opts.fallback ? gax.fallback : gax;

    // Create a `gaxGrpc` object, with any grpc-specific options sent to the client.
    this._gaxGrpc = new this._gaxModule.GrpcClient(opts);

    // Save options to use in initialize() method.
    this._opts = opts;

    // Save the auth object to the client, for use by other methods.
    this.auth = this._gaxGrpc.auth as gax.GoogleAuth;

    // Set useJWTAccessWithScope on the auth object.
    this.auth.useJWTAccessWithScope = true;

    // Set defaultServicePath on the auth object.
    this.auth.defaultServicePath = staticMembers.servicePath;

    // Set the default scopes in auth client if needed.
    if (servicePath === staticMembers.servicePath) {
      this.auth.defaultScopes = staticMembers.scopes;
    }

    // Determine the client header string.
    const clientHeader = [`gax/${this._gaxModule.version}`, `gapic/${version}`];
    if (typeof process !== 'undefined' && 'versions' in process) {
      clientHeader.push(`gl-node/${process.versions.node}`);
    } else {
      clientHeader.push(`gl-web/${this._gaxModule.version}`);
    }
    if (!opts.fallback) {
      clientHeader.push(`grpc/${this._gaxGrpc.grpcVersion}`);
    } else if (opts.fallback === 'rest') {
      clientHeader.push(`rest/${this._gaxGrpc.grpcVersion}`);
    }
    if (opts.libName && opts.libVersion) {
      clientHeader.push(`${opts.libName}/${opts.libVersion}`);
    }
    // Load the applicable protos.
    this._protos = this._gaxGrpc.loadProtoJSON(jsonProtos);

    // This API contains "path templates"; forward-slash-separated
    // identifiers to uniquely identify resources within the API.
    // Create useful helper objects for these.
    this.pathTemplates = {
      annotationSpecPathTemplate: new this._gaxModule.PathTemplate(
        'projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}'
      ),
      datasetPathTemplate: new this._gaxModule.PathTemplate(
        'projects/{project}/locations/{location}/datasets/{dataset}'
      ),
      locationPathTemplate: new this._gaxModule.PathTemplate(
        'projects/{project}/locations/{location}'
      ),
      modelPathTemplate: new this._gaxModule.PathTemplate(
        'projects/{project}/locations/{location}/models/{model}'
      ),
      modelEvaluationPathTemplate: new this._gaxModule.PathTemplate(
        'projects/{project}/locations/{location}/models/{model}/modelEvaluations/{model_evaluation}'
      ),
    };

    // Some of the methods on this service return "paged" results,
    // (e.g. 50 results at a time, with tokens to get subsequent
    // pages). Denote the keys used for pagination and results.
    this.descriptors.page = {
      listDatasets: new this._gaxModule.PageDescriptor(
        'pageToken',
        'nextPageToken',
        'datasets'
      ),
      listModels: new this._gaxModule.PageDescriptor(
        'pageToken',
        'nextPageToken',
        'model'
      ),
      listModelEvaluations: new this._gaxModule.PageDescriptor(
        'pageToken',
        'nextPageToken',
        'modelEvaluation'
      ),
    };

    const protoFilesRoot = this._gaxModule.protobuf.Root.fromJSON(jsonProtos);

    // This API contains "long-running operations", which return a
    // an Operation object that allows for tracking of the operation,
    // rather than holding a request open.

    this.operationsClient = this._gaxModule
      .lro({
        auth: this.auth,
        grpc: 'grpc' in this._gaxGrpc ? this._gaxGrpc.grpc : undefined,
      })
      .operationsClient(opts);
    const createDatasetResponse = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.Dataset'
    ) as gax.protobuf.Type;
    const createDatasetMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const deleteDatasetResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const deleteDatasetMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const importDataResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const importDataMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const exportDataResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const exportDataMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const createModelResponse = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.Model'
    ) as gax.protobuf.Type;
    const createModelMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const deleteModelResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const deleteModelMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const deployModelResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const deployModelMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const undeployModelResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const undeployModelMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;
    const exportModelResponse = protoFilesRoot.lookup(
      '.google.protobuf.Empty'
    ) as gax.protobuf.Type;
    const exportModelMetadata = protoFilesRoot.lookup(
      '.google.cloud.automl.v1.OperationMetadata'
    ) as gax.protobuf.Type;

    this.descriptors.longrunning = {
      createDataset: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        createDatasetResponse.decode.bind(createDatasetResponse),
        createDatasetMetadata.decode.bind(createDatasetMetadata)
      ),
      deleteDataset: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        deleteDatasetResponse.decode.bind(deleteDatasetResponse),
        deleteDatasetMetadata.decode.bind(deleteDatasetMetadata)
      ),
      importData: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        importDataResponse.decode.bind(importDataResponse),
        importDataMetadata.decode.bind(importDataMetadata)
      ),
      exportData: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        exportDataResponse.decode.bind(exportDataResponse),
        exportDataMetadata.decode.bind(exportDataMetadata)
      ),
      createModel: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        createModelResponse.decode.bind(createModelResponse),
        createModelMetadata.decode.bind(createModelMetadata)
      ),
      deleteModel: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        deleteModelResponse.decode.bind(deleteModelResponse),
        deleteModelMetadata.decode.bind(deleteModelMetadata)
      ),
      deployModel: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        deployModelResponse.decode.bind(deployModelResponse),
        deployModelMetadata.decode.bind(deployModelMetadata)
      ),
      undeployModel: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        undeployModelResponse.decode.bind(undeployModelResponse),
        undeployModelMetadata.decode.bind(undeployModelMetadata)
      ),
      exportModel: new this._gaxModule.LongrunningDescriptor(
        this.operationsClient,
        exportModelResponse.decode.bind(exportModelResponse),
        exportModelMetadata.decode.bind(exportModelMetadata)
      ),
    };

    // Put together the default options sent with requests.
    this._defaults = this._gaxGrpc.constructSettings(
      'google.cloud.automl.v1.AutoMl',
      gapicConfig as gax.ClientConfig,
      opts.clientConfig || {},
      {'x-goog-api-client': clientHeader.join(' ')}
    );

    // Set up a dictionary of "inner API calls"; the core implementation
    // of calling the API is handled in `google-gax`, with this code
    // merely providing the destination and request information.
    this.innerApiCalls = {};

    // Add a warn function to the client constructor so it can be easily tested.
    this.warn = gax.warn;
  }

  /**
   * Initialize the client.
   * Performs asynchronous operations (such as authentication) and prepares the client.
   * This function will be called automatically when any class method is called for the
   * first time, but if you need to initialize it before calling an actual method,
   * feel free to call initialize() directly.
   *
   * You can await on this method if you want to make sure the client is initialized.
   *
   * @returns {Promise} A promise that resolves to an authenticated service stub.
   */
  initialize() {
    // If the client stub promise is already initialized, return immediately.
    if (this.autoMlStub) {
      return this.autoMlStub;
    }

    // Put together the "service stub" for
    // google.cloud.automl.v1.AutoMl.
    this.autoMlStub = this._gaxGrpc.createStub(
      this._opts.fallback
        ? (this._protos as protobuf.Root).lookupService(
            'google.cloud.automl.v1.AutoMl'
          )
        : // eslint-disable-next-line @typescript-eslint/no-explicit-any
          (this._protos as any).google.cloud.automl.v1.AutoMl,
      this._opts,
      this._providedCustomServicePath
    ) as Promise<{[method: string]: Function}>;

    // Iterate over each of the methods that the service provides
    // and create an API call method for each.
    const autoMlStubMethods = [
      'createDataset',
      'getDataset',
      'listDatasets',
      'updateDataset',
      'deleteDataset',
      'importData',
      'exportData',
      'getAnnotationSpec',
      'createModel',
      'getModel',
      'listModels',
      'deleteModel',
      'updateModel',
      'deployModel',
      'undeployModel',
      'exportModel',
      'getModelEvaluation',
      'listModelEvaluations',
    ];
    for (const methodName of autoMlStubMethods) {
      const callPromise = this.autoMlStub.then(
        stub =>
          (...args: Array<{}>) => {
            if (this._terminated) {
              return Promise.reject('The client has already been closed.');
            }
            const func = stub[methodName];
            return func.apply(stub, args);
          },
        (err: Error | null | undefined) => () => {
          throw err;
        }
      );

      const descriptor =
        this.descriptors.page[methodName] ||
        this.descriptors.longrunning[methodName] ||
        undefined;
      const apiCall = this._gaxModule.createApiCall(
        callPromise,
        this._defaults[methodName],
        descriptor
      );

      this.innerApiCalls[methodName] = apiCall;
    }

    return this.autoMlStub;
  }

  /**
   * The DNS address for this API service.
   * @returns {string} The DNS address for this service.
   */
  static get servicePath() {
    return 'automl.googleapis.com';
  }

  /**
   * The DNS address for this API service - same as servicePath(),
   * exists for compatibility reasons.
   * @returns {string} The DNS address for this service.
   */
  static get apiEndpoint() {
    return 'automl.googleapis.com';
  }

  /**
   * The port for this API service.
   * @returns {number} The default port for this service.
   */
  static get port() {
    return 443;
  }

  /**
   * The scopes needed to make gRPC calls for every method defined
   * in this service.
   * @returns {string[]} List of default scopes.
   */
  static get scopes() {
    return ['https://www.googleapis.com/auth/cloud-platform'];
  }

  getProjectId(): Promise<string>;
  getProjectId(callback: Callback<string, undefined, undefined>): void;
  /**
   * Return the project ID used by this class.
   * @returns {Promise} A promise that resolves to string containing the project ID.
   */
  getProjectId(
    callback?: Callback<string, undefined, undefined>
  ): Promise<string> | void {
    if (callback) {
      this.auth.getProjectId(callback);
      return;
    }
    return this.auth.getProjectId();
  }

  // -------------------
  // -- Service calls --
  // -------------------
  getDataset(
    request?: protos.google.cloud.automl.v1.IGetDatasetRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IGetDatasetRequest | undefined,
      {} | undefined
    ]
  >;
  getDataset(
    request: protos.google.cloud.automl.v1.IGetDatasetRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  getDataset(
    request: protos.google.cloud.automl.v1.IGetDatasetRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Gets a dataset.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. The resource name of the dataset to retrieve.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [Dataset]{@link google.cloud.automl.v1.Dataset}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.getDataset(request);
   */
  getDataset(
    request?: protos.google.cloud.automl.v1.IGetDatasetRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IDataset,
          protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IGetDatasetRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.getDataset(request, options, callback);
  }
  updateDataset(
    request?: protos.google.cloud.automl.v1.IUpdateDatasetRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IUpdateDatasetRequest | undefined,
      {} | undefined
    ]
  >;
  updateDataset(
    request: protos.google.cloud.automl.v1.IUpdateDatasetRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  updateDataset(
    request: protos.google.cloud.automl.v1.IUpdateDatasetRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Updates a dataset.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {google.cloud.automl.v1.Dataset} request.dataset
   *   Required. The dataset which replaces the resource on the server.
   * @param {google.protobuf.FieldMask} request.updateMask
   *   Required. The update mask applies to the resource.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [Dataset]{@link google.cloud.automl.v1.Dataset}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.updateDataset(request);
   */
  updateDataset(
    request?: protos.google.cloud.automl.v1.IUpdateDatasetRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IDataset,
          | protos.google.cloud.automl.v1.IUpdateDatasetRequest
          | null
          | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset,
      protos.google.cloud.automl.v1.IUpdateDatasetRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        'dataset.name': request.dataset!.name || '',
      });
    this.initialize();
    return this.innerApiCalls.updateDataset(request, options, callback);
  }
  getAnnotationSpec(
    request?: protos.google.cloud.automl.v1.IGetAnnotationSpecRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IAnnotationSpec,
      protos.google.cloud.automl.v1.IGetAnnotationSpecRequest | undefined,
      {} | undefined
    ]
  >;
  getAnnotationSpec(
    request: protos.google.cloud.automl.v1.IGetAnnotationSpecRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IAnnotationSpec,
      | protos.google.cloud.automl.v1.IGetAnnotationSpecRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): void;
  getAnnotationSpec(
    request: protos.google.cloud.automl.v1.IGetAnnotationSpecRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IAnnotationSpec,
      | protos.google.cloud.automl.v1.IGetAnnotationSpecRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Gets an annotation spec.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. The resource name of the annotation spec to retrieve.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [AnnotationSpec]{@link google.cloud.automl.v1.AnnotationSpec}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.getAnnotationSpec(request);
   */
  getAnnotationSpec(
    request?: protos.google.cloud.automl.v1.IGetAnnotationSpecRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IAnnotationSpec,
          | protos.google.cloud.automl.v1.IGetAnnotationSpecRequest
          | null
          | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IAnnotationSpec,
      | protos.google.cloud.automl.v1.IGetAnnotationSpecRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IAnnotationSpec,
      protos.google.cloud.automl.v1.IGetAnnotationSpecRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.getAnnotationSpec(request, options, callback);
  }
  getModel(
    request?: protos.google.cloud.automl.v1.IGetModelRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IGetModelRequest | undefined,
      {} | undefined
    ]
  >;
  getModel(
    request: protos.google.cloud.automl.v1.IGetModelRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IGetModelRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  getModel(
    request: protos.google.cloud.automl.v1.IGetModelRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IGetModelRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Gets a model.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. Resource name of the model.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [Model]{@link google.cloud.automl.v1.Model}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.getModel(request);
   */
  getModel(
    request?: protos.google.cloud.automl.v1.IGetModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IModel,
          protos.google.cloud.automl.v1.IGetModelRequest | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IGetModelRequest | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IGetModelRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.getModel(request, options, callback);
  }
  updateModel(
    request?: protos.google.cloud.automl.v1.IUpdateModelRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IUpdateModelRequest | undefined,
      {} | undefined
    ]
  >;
  updateModel(
    request: protos.google.cloud.automl.v1.IUpdateModelRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  updateModel(
    request: protos.google.cloud.automl.v1.IUpdateModelRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Updates a model.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {google.cloud.automl.v1.Model} request.model
   *   Required. The model which replaces the resource on the server.
   * @param {google.protobuf.FieldMask} request.updateMask
   *   Required. The update mask applies to the resource.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [Model]{@link google.cloud.automl.v1.Model}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.updateModel(request);
   */
  updateModel(
    request?: protos.google.cloud.automl.v1.IUpdateModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IModel,
          protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel,
      protos.google.cloud.automl.v1.IUpdateModelRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        'model.name': request.model!.name || '',
      });
    this.initialize();
    return this.innerApiCalls.updateModel(request, options, callback);
  }
  getModelEvaluation(
    request?: protos.google.cloud.automl.v1.IGetModelEvaluationRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModelEvaluation,
      protos.google.cloud.automl.v1.IGetModelEvaluationRequest | undefined,
      {} | undefined
    ]
  >;
  getModelEvaluation(
    request: protos.google.cloud.automl.v1.IGetModelEvaluationRequest,
    options: CallOptions,
    callback: Callback<
      protos.google.cloud.automl.v1.IModelEvaluation,
      | protos.google.cloud.automl.v1.IGetModelEvaluationRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): void;
  getModelEvaluation(
    request: protos.google.cloud.automl.v1.IGetModelEvaluationRequest,
    callback: Callback<
      protos.google.cloud.automl.v1.IModelEvaluation,
      | protos.google.cloud.automl.v1.IGetModelEvaluationRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Gets a model evaluation.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. Resource name for the model evaluation.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing [ModelEvaluation]{@link google.cloud.automl.v1.ModelEvaluation}.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods)
   *   for more details and examples.
   * @example
   * const [response] = await client.getModelEvaluation(request);
   */
  getModelEvaluation(
    request?: protos.google.cloud.automl.v1.IGetModelEvaluationRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          protos.google.cloud.automl.v1.IModelEvaluation,
          | protos.google.cloud.automl.v1.IGetModelEvaluationRequest
          | null
          | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      protos.google.cloud.automl.v1.IModelEvaluation,
      | protos.google.cloud.automl.v1.IGetModelEvaluationRequest
      | null
      | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModelEvaluation,
      protos.google.cloud.automl.v1.IGetModelEvaluationRequest | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.getModelEvaluation(request, options, callback);
  }

  createDataset(
    request?: protos.google.cloud.automl.v1.ICreateDatasetRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.cloud.automl.v1.IDataset,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  createDataset(
    request: protos.google.cloud.automl.v1.ICreateDatasetRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IDataset,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  createDataset(
    request: protos.google.cloud.automl.v1.ICreateDatasetRequest,
    callback: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IDataset,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Creates a dataset.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. The resource name of the project to create the dataset for.
   * @param {google.cloud.automl.v1.Dataset} request.dataset
   *   Required. The dataset to create.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.createDataset(request);
   * const [response] = await operation.promise();
   */
  createDataset(
    request?: protos.google.cloud.automl.v1.ICreateDatasetRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.cloud.automl.v1.IDataset,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IDataset,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.cloud.automl.v1.IDataset,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    this.initialize();
    return this.innerApiCalls.createDataset(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `createDataset()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkCreateDatasetProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkCreateDatasetProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.cloud.automl.v1.Dataset,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.createDataset,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.cloud.automl.v1.Dataset,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  deleteDataset(
    request?: protos.google.cloud.automl.v1.IDeleteDatasetRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  deleteDataset(
    request: protos.google.cloud.automl.v1.IDeleteDatasetRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  deleteDataset(
    request: protos.google.cloud.automl.v1.IDeleteDatasetRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Deletes a dataset and all of its contents.
   * Returns empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes,
   * and `delete_details` in the
   * {@link google.longrunning.Operation.metadata|metadata} field.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. The resource name of the dataset to delete.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.deleteDataset(request);
   * const [response] = await operation.promise();
   */
  deleteDataset(
    request?: protos.google.cloud.automl.v1.IDeleteDatasetRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.deleteDataset(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `deleteDataset()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkDeleteDatasetProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkDeleteDatasetProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.deleteDataset,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  importData(
    request?: protos.google.cloud.automl.v1.IImportDataRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  importData(
    request: protos.google.cloud.automl.v1.IImportDataRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  importData(
    request: protos.google.cloud.automl.v1.IImportDataRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Imports data into a dataset.
   * For Tables this method can only be called on an empty Dataset.
   *
   * For Tables:
   * *   A
   * {@link google.cloud.automl.v1.InputConfig.params|schema_inference_version}
   *     parameter must be explicitly set.
   * Returns an empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. Dataset name. Dataset must already exist. All imported
   *   annotations and examples will be added.
   * @param {google.cloud.automl.v1.InputConfig} request.inputConfig
   *   Required. The desired input location and its domain specific semantics,
   *   if any.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.importData(request);
   * const [response] = await operation.promise();
   */
  importData(
    request?: protos.google.cloud.automl.v1.IImportDataRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.importData(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `importData()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkImportDataProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkImportDataProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.importData,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  exportData(
    request?: protos.google.cloud.automl.v1.IExportDataRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  exportData(
    request: protos.google.cloud.automl.v1.IExportDataRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  exportData(
    request: protos.google.cloud.automl.v1.IExportDataRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Exports dataset's data to the provided output location.
   * Returns an empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. The resource name of the dataset.
   * @param {google.cloud.automl.v1.OutputConfig} request.outputConfig
   *   Required. The desired output location.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.exportData(request);
   * const [response] = await operation.promise();
   */
  exportData(
    request?: protos.google.cloud.automl.v1.IExportDataRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.exportData(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `exportData()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkExportDataProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkExportDataProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.exportData,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  createModel(
    request?: protos.google.cloud.automl.v1.ICreateModelRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.cloud.automl.v1.IModel,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  createModel(
    request: protos.google.cloud.automl.v1.ICreateModelRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IModel,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  createModel(
    request: protos.google.cloud.automl.v1.ICreateModelRequest,
    callback: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IModel,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Creates a model.
   * Returns a Model in the {@link google.longrunning.Operation.response|response}
   * field when it completes.
   * When you create a model, several model evaluations are created for it:
   * a global evaluation, and one evaluation for each annotation spec.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the parent project where the model is being created.
   * @param {google.cloud.automl.v1.Model} request.model
   *   Required. The model to create.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.createModel(request);
   * const [response] = await operation.promise();
   */
  createModel(
    request?: protos.google.cloud.automl.v1.ICreateModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.cloud.automl.v1.IModel,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.cloud.automl.v1.IModel,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.cloud.automl.v1.IModel,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    this.initialize();
    return this.innerApiCalls.createModel(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `createModel()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkCreateModelProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkCreateModelProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.cloud.automl.v1.Model,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.createModel,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.cloud.automl.v1.Model,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  deleteModel(
    request?: protos.google.cloud.automl.v1.IDeleteModelRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  deleteModel(
    request: protos.google.cloud.automl.v1.IDeleteModelRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  deleteModel(
    request: protos.google.cloud.automl.v1.IDeleteModelRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Deletes a model.
   * Returns `google.protobuf.Empty` in the
   * {@link google.longrunning.Operation.response|response} field when it completes,
   * and `delete_details` in the
   * {@link google.longrunning.Operation.metadata|metadata} field.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. Resource name of the model being deleted.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.deleteModel(request);
   * const [response] = await operation.promise();
   */
  deleteModel(
    request?: protos.google.cloud.automl.v1.IDeleteModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.deleteModel(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `deleteModel()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkDeleteModelProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkDeleteModelProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.deleteModel,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  deployModel(
    request?: protos.google.cloud.automl.v1.IDeployModelRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  deployModel(
    request: protos.google.cloud.automl.v1.IDeployModelRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  deployModel(
    request: protos.google.cloud.automl.v1.IDeployModelRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Deploys a model. If a model is already deployed, deploying it with the
   * same parameters has no effect. Deploying with different parametrs
   * (as e.g. changing
   *
   * {@link google.cloud.automl.v1p1beta.ImageObjectDetectionModelDeploymentMetadata.node_number|node_number})
   *  will reset the deployment state without pausing the model's availability.
   *
   * Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage
   * deployment automatically.
   *
   * Returns an empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {google.cloud.automl.v1.ImageObjectDetectionModelDeploymentMetadata} request.imageObjectDetectionModelDeploymentMetadata
   *   Model deployment metadata specific to Image Object Detection.
   * @param {google.cloud.automl.v1.ImageClassificationModelDeploymentMetadata} request.imageClassificationModelDeploymentMetadata
   *   Model deployment metadata specific to Image Classification.
   * @param {string} request.name
   *   Required. Resource name of the model to deploy.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.deployModel(request);
   * const [response] = await operation.promise();
   */
  deployModel(
    request?: protos.google.cloud.automl.v1.IDeployModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.deployModel(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `deployModel()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkDeployModelProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkDeployModelProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.deployModel,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  undeployModel(
    request?: protos.google.cloud.automl.v1.IUndeployModelRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  undeployModel(
    request: protos.google.cloud.automl.v1.IUndeployModelRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  undeployModel(
    request: protos.google.cloud.automl.v1.IUndeployModelRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Undeploys a model. If the model is not deployed this method has no effect.
   *
   * Only applicable for Text Classification, Image Object Detection and Tables;
   * all other domains manage deployment automatically.
   *
   * Returns an empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. Resource name of the model to undeploy.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.undeployModel(request);
   * const [response] = await operation.promise();
   */
  undeployModel(
    request?: protos.google.cloud.automl.v1.IUndeployModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.undeployModel(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `undeployModel()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkUndeployModelProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkUndeployModelProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.undeployModel,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  exportModel(
    request?: protos.google.cloud.automl.v1.IExportModelRequest,
    options?: CallOptions
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  >;
  exportModel(
    request: protos.google.cloud.automl.v1.IExportModelRequest,
    options: CallOptions,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  exportModel(
    request: protos.google.cloud.automl.v1.IExportModelRequest,
    callback: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): void;
  /**
   * Exports a trained, "export-able", model to a user specified Google Cloud
   * Storage location. A model is considered export-able if and only if it has
   * an export format defined for it in
   * {@link google.cloud.automl.v1.ModelExportOutputConfig|ModelExportOutputConfig}.
   *
   * Returns an empty response in the
   * {@link google.longrunning.Operation.response|response} field when it completes.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.name
   *   Required. The resource name of the model to export.
   * @param {google.cloud.automl.v1.ModelExportOutputConfig} request.outputConfig
   *   Required. The desired output location and configuration.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is an object representing
   *   a long running operation. Its `promise()` method returns a promise
   *   you can `await` for.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const [operation] = await client.exportModel(request);
   * const [response] = await operation.promise();
   */
  exportModel(
    request?: protos.google.cloud.automl.v1.IExportModelRequest,
    optionsOrCallback?:
      | CallOptions
      | Callback<
          LROperation<
            protos.google.protobuf.IEmpty,
            protos.google.cloud.automl.v1.IOperationMetadata
          >,
          protos.google.longrunning.IOperation | null | undefined,
          {} | null | undefined
        >,
    callback?: Callback<
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | null | undefined,
      {} | null | undefined
    >
  ): Promise<
    [
      LROperation<
        protos.google.protobuf.IEmpty,
        protos.google.cloud.automl.v1.IOperationMetadata
      >,
      protos.google.longrunning.IOperation | undefined,
      {} | undefined
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        name: request.name || '',
      });
    this.initialize();
    return this.innerApiCalls.exportModel(request, options, callback);
  }
  /**
   * Check the status of the long running operation returned by `exportModel()`.
   * @param {String} name
   *   The operation name that will be passed.
   * @returns {Promise} - The promise which resolves to an object.
   *   The decoded operation object has result and metadata field to get information from.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations)
   *   for more details and examples.
   * @example
   * const decodedOperation = await checkExportModelProgress(name);
   * console.log(decodedOperation.result);
   * console.log(decodedOperation.done);
   * console.log(decodedOperation.metadata);
   */
  async checkExportModelProgress(
    name: string
  ): Promise<
    LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >
  > {
    const request = new operationsProtos.google.longrunning.GetOperationRequest(
      {name}
    );
    const [operation] = await this.operationsClient.getOperation(request);
    const decodeOperation = new gax.Operation(
      operation,
      this.descriptors.longrunning.exportModel,
      gax.createDefaultBackoffSettings()
    );
    return decodeOperation as LROperation<
      protos.google.protobuf.Empty,
      protos.google.cloud.automl.v1.OperationMetadata
    >;
  }
  listDatasets(
    request?: protos.google.cloud.automl.v1.IListDatasetsRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset[],
      protos.google.cloud.automl.v1.IListDatasetsRequest | null,
      protos.google.cloud.automl.v1.IListDatasetsResponse
    ]
  >;
  listDatasets(
    request: protos.google.cloud.automl.v1.IListDatasetsRequest,
    options: CallOptions,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListDatasetsRequest,
      protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined,
      protos.google.cloud.automl.v1.IDataset
    >
  ): void;
  listDatasets(
    request: protos.google.cloud.automl.v1.IListDatasetsRequest,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListDatasetsRequest,
      protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined,
      protos.google.cloud.automl.v1.IDataset
    >
  ): void;
  /**
   * Lists datasets in a project.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. The resource name of the project from which to list datasets.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `dataset_metadata` - for existence of the case (e.g.
   *               image_classification_dataset_metadata:*). Some examples of using the filter are:
   *
   *     * `translation_dataset_metadata:*` --> The dataset has
   *                                            translation_dataset_metadata.
   * @param {number} request.pageSize
   *   Requested page size. Server may return fewer results than requested.
   *   If unspecified, server will pick a default size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListDatasetsResponse.next_page_token|ListDatasetsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListDatasets|AutoMl.ListDatasets} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is Array of [Dataset]{@link google.cloud.automl.v1.Dataset}.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed and will merge results from all the pages into this array.
   *   Note that it can affect your quota.
   *   We recommend using `listDatasetsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listDatasets(
    request?: protos.google.cloud.automl.v1.IListDatasetsRequest,
    optionsOrCallback?:
      | CallOptions
      | PaginationCallback<
          protos.google.cloud.automl.v1.IListDatasetsRequest,
          | protos.google.cloud.automl.v1.IListDatasetsResponse
          | null
          | undefined,
          protos.google.cloud.automl.v1.IDataset
        >,
    callback?: PaginationCallback<
      protos.google.cloud.automl.v1.IListDatasetsRequest,
      protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined,
      protos.google.cloud.automl.v1.IDataset
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IDataset[],
      protos.google.cloud.automl.v1.IListDatasetsRequest | null,
      protos.google.cloud.automl.v1.IListDatasetsResponse
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    this.initialize();
    return this.innerApiCalls.listDatasets(request, options, callback);
  }

  /**
   * Equivalent to `method.name.toCamelCase()`, but returns a NodeJS Stream object.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. The resource name of the project from which to list datasets.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `dataset_metadata` - for existence of the case (e.g.
   *               image_classification_dataset_metadata:*). Some examples of using the filter are:
   *
   *     * `translation_dataset_metadata:*` --> The dataset has
   *                                            translation_dataset_metadata.
   * @param {number} request.pageSize
   *   Requested page size. Server may return fewer results than requested.
   *   If unspecified, server will pick a default size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListDatasetsResponse.next_page_token|ListDatasetsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListDatasets|AutoMl.ListDatasets} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Stream}
   *   An object stream which emits an object representing [Dataset]{@link google.cloud.automl.v1.Dataset} on 'data' event.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed. Note that it can affect your quota.
   *   We recommend using `listDatasetsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listDatasetsStream(
    request?: protos.google.cloud.automl.v1.IListDatasetsRequest,
    options?: CallOptions
  ): Transform {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listDatasets.createStream(
      this.innerApiCalls.listDatasets as gax.GaxCall,
      request,
      callSettings
    );
  }

  /**
   * Equivalent to `listDatasets`, but returns an iterable object.
   *
   * `for`-`await`-`of` syntax is used with the iterable to get response elements on-demand.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. The resource name of the project from which to list datasets.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `dataset_metadata` - for existence of the case (e.g.
   *               image_classification_dataset_metadata:*). Some examples of using the filter are:
   *
   *     * `translation_dataset_metadata:*` --> The dataset has
   *                                            translation_dataset_metadata.
   * @param {number} request.pageSize
   *   Requested page size. Server may return fewer results than requested.
   *   If unspecified, server will pick a default size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListDatasetsResponse.next_page_token|ListDatasetsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListDatasets|AutoMl.ListDatasets} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Object}
   *   An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols).
   *   When you iterate the returned iterable, each element will be an object representing
   *   [Dataset]{@link google.cloud.automl.v1.Dataset}. The API will be called under the hood as needed, once per the page,
   *   so you can stop the iteration when you don't need more results.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   * @example
   * const iterable = client.listDatasetsAsync(request);
   * for await (const response of iterable) {
   *   // process response
   * }
   */
  listDatasetsAsync(
    request?: protos.google.cloud.automl.v1.IListDatasetsRequest,
    options?: CallOptions
  ): AsyncIterable<protos.google.cloud.automl.v1.IDataset> {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    options = options || {};
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listDatasets.asyncIterate(
      this.innerApiCalls['listDatasets'] as GaxCall,
      request as unknown as RequestType,
      callSettings
    ) as AsyncIterable<protos.google.cloud.automl.v1.IDataset>;
  }
  listModels(
    request?: protos.google.cloud.automl.v1.IListModelsRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel[],
      protos.google.cloud.automl.v1.IListModelsRequest | null,
      protos.google.cloud.automl.v1.IListModelsResponse
    ]
  >;
  listModels(
    request: protos.google.cloud.automl.v1.IListModelsRequest,
    options: CallOptions,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelsRequest,
      protos.google.cloud.automl.v1.IListModelsResponse | null | undefined,
      protos.google.cloud.automl.v1.IModel
    >
  ): void;
  listModels(
    request: protos.google.cloud.automl.v1.IListModelsRequest,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelsRequest,
      protos.google.cloud.automl.v1.IListModelsResponse | null | undefined,
      protos.google.cloud.automl.v1.IModel
    >
  ): void;
  /**
   * Lists models.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the project, from which to list the models.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `model_metadata` - for existence of the case (e.g.
   *               video_classification_model_metadata:*).
   *     * `dataset_id` - for = or !=. Some examples of using the filter are:
   *
   *     * `image_classification_model_metadata:*` --> The model has
   *                                          image_classification_model_metadata.
   *     * `dataset_id=5` --> The model was created from a dataset with ID 5.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelsResponse.next_page_token|ListModelsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModels|AutoMl.ListModels} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is Array of [Model]{@link google.cloud.automl.v1.Model}.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed and will merge results from all the pages into this array.
   *   Note that it can affect your quota.
   *   We recommend using `listModelsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listModels(
    request?: protos.google.cloud.automl.v1.IListModelsRequest,
    optionsOrCallback?:
      | CallOptions
      | PaginationCallback<
          protos.google.cloud.automl.v1.IListModelsRequest,
          protos.google.cloud.automl.v1.IListModelsResponse | null | undefined,
          protos.google.cloud.automl.v1.IModel
        >,
    callback?: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelsRequest,
      protos.google.cloud.automl.v1.IListModelsResponse | null | undefined,
      protos.google.cloud.automl.v1.IModel
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModel[],
      protos.google.cloud.automl.v1.IListModelsRequest | null,
      protos.google.cloud.automl.v1.IListModelsResponse
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    this.initialize();
    return this.innerApiCalls.listModels(request, options, callback);
  }

  /**
   * Equivalent to `method.name.toCamelCase()`, but returns a NodeJS Stream object.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the project, from which to list the models.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `model_metadata` - for existence of the case (e.g.
   *               video_classification_model_metadata:*).
   *     * `dataset_id` - for = or !=. Some examples of using the filter are:
   *
   *     * `image_classification_model_metadata:*` --> The model has
   *                                          image_classification_model_metadata.
   *     * `dataset_id=5` --> The model was created from a dataset with ID 5.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelsResponse.next_page_token|ListModelsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModels|AutoMl.ListModels} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Stream}
   *   An object stream which emits an object representing [Model]{@link google.cloud.automl.v1.Model} on 'data' event.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed. Note that it can affect your quota.
   *   We recommend using `listModelsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listModelsStream(
    request?: protos.google.cloud.automl.v1.IListModelsRequest,
    options?: CallOptions
  ): Transform {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listModels.createStream(
      this.innerApiCalls.listModels as gax.GaxCall,
      request,
      callSettings
    );
  }

  /**
   * Equivalent to `listModels`, but returns an iterable object.
   *
   * `for`-`await`-`of` syntax is used with the iterable to get response elements on-demand.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the project, from which to list the models.
   * @param {string} request.filter
   *   An expression for filtering the results of the request.
   *
   *     * `model_metadata` - for existence of the case (e.g.
   *               video_classification_model_metadata:*).
   *     * `dataset_id` - for = or !=. Some examples of using the filter are:
   *
   *     * `image_classification_model_metadata:*` --> The model has
   *                                          image_classification_model_metadata.
   *     * `dataset_id=5` --> The model was created from a dataset with ID 5.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelsResponse.next_page_token|ListModelsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModels|AutoMl.ListModels} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Object}
   *   An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols).
   *   When you iterate the returned iterable, each element will be an object representing
   *   [Model]{@link google.cloud.automl.v1.Model}. The API will be called under the hood as needed, once per the page,
   *   so you can stop the iteration when you don't need more results.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   * @example
   * const iterable = client.listModelsAsync(request);
   * for await (const response of iterable) {
   *   // process response
   * }
   */
  listModelsAsync(
    request?: protos.google.cloud.automl.v1.IListModelsRequest,
    options?: CallOptions
  ): AsyncIterable<protos.google.cloud.automl.v1.IModel> {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    options = options || {};
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listModels.asyncIterate(
      this.innerApiCalls['listModels'] as GaxCall,
      request as unknown as RequestType,
      callSettings
    ) as AsyncIterable<protos.google.cloud.automl.v1.IModel>;
  }
  listModelEvaluations(
    request?: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    options?: CallOptions
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModelEvaluation[],
      protos.google.cloud.automl.v1.IListModelEvaluationsRequest | null,
      protos.google.cloud.automl.v1.IListModelEvaluationsResponse
    ]
  >;
  listModelEvaluations(
    request: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    options: CallOptions,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
      | protos.google.cloud.automl.v1.IListModelEvaluationsResponse
      | null
      | undefined,
      protos.google.cloud.automl.v1.IModelEvaluation
    >
  ): void;
  listModelEvaluations(
    request: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    callback: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
      | protos.google.cloud.automl.v1.IListModelEvaluationsResponse
      | null
      | undefined,
      protos.google.cloud.automl.v1.IModelEvaluation
    >
  ): void;
  /**
   * Lists model evaluations.
   *
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the model to list the model evaluations for.
   *   If modelId is set as "-", this will list model evaluations from across all
   *   models of the parent location.
   * @param {string} request.filter
   *   Required. An expression for filtering the results of the request.
   *
   *     * `annotation_spec_id` - for =, !=  or existence. See example below for
   *                            the last.
   *
   *   Some examples of using the filter are:
   *
   *     * `annotation_spec_id!=4` --> The model evaluation was done for
   *                               annotation spec with ID different than 4.
   *     * `NOT annotation_spec_id:*` --> The model evaluation was done for
   *                                  aggregate of all annotation specs.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return.
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelEvaluationsResponse.next_page_token|ListModelEvaluationsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModelEvaluations|AutoMl.ListModelEvaluations} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Promise} - The promise which resolves to an array.
   *   The first element of the array is Array of [ModelEvaluation]{@link google.cloud.automl.v1.ModelEvaluation}.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed and will merge results from all the pages into this array.
   *   Note that it can affect your quota.
   *   We recommend using `listModelEvaluationsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listModelEvaluations(
    request?: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    optionsOrCallback?:
      | CallOptions
      | PaginationCallback<
          protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
          | protos.google.cloud.automl.v1.IListModelEvaluationsResponse
          | null
          | undefined,
          protos.google.cloud.automl.v1.IModelEvaluation
        >,
    callback?: PaginationCallback<
      protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
      | protos.google.cloud.automl.v1.IListModelEvaluationsResponse
      | null
      | undefined,
      protos.google.cloud.automl.v1.IModelEvaluation
    >
  ): Promise<
    [
      protos.google.cloud.automl.v1.IModelEvaluation[],
      protos.google.cloud.automl.v1.IListModelEvaluationsRequest | null,
      protos.google.cloud.automl.v1.IListModelEvaluationsResponse
    ]
  > | void {
    request = request || {};
    let options: CallOptions;
    if (typeof optionsOrCallback === 'function' && callback === undefined) {
      callback = optionsOrCallback;
      options = {};
    } else {
      options = optionsOrCallback as CallOptions;
    }
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    this.initialize();
    return this.innerApiCalls.listModelEvaluations(request, options, callback);
  }

  /**
   * Equivalent to `method.name.toCamelCase()`, but returns a NodeJS Stream object.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the model to list the model evaluations for.
   *   If modelId is set as "-", this will list model evaluations from across all
   *   models of the parent location.
   * @param {string} request.filter
   *   Required. An expression for filtering the results of the request.
   *
   *     * `annotation_spec_id` - for =, !=  or existence. See example below for
   *                            the last.
   *
   *   Some examples of using the filter are:
   *
   *     * `annotation_spec_id!=4` --> The model evaluation was done for
   *                               annotation spec with ID different than 4.
   *     * `NOT annotation_spec_id:*` --> The model evaluation was done for
   *                                  aggregate of all annotation specs.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return.
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelEvaluationsResponse.next_page_token|ListModelEvaluationsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModelEvaluations|AutoMl.ListModelEvaluations} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Stream}
   *   An object stream which emits an object representing [ModelEvaluation]{@link google.cloud.automl.v1.ModelEvaluation} on 'data' event.
   *   The client library will perform auto-pagination by default: it will call the API as many
   *   times as needed. Note that it can affect your quota.
   *   We recommend using `listModelEvaluationsAsync()`
   *   method described below for async iteration which you can stop as needed.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   */
  listModelEvaluationsStream(
    request?: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    options?: CallOptions
  ): Transform {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listModelEvaluations.createStream(
      this.innerApiCalls.listModelEvaluations as gax.GaxCall,
      request,
      callSettings
    );
  }

  /**
   * Equivalent to `listModelEvaluations`, but returns an iterable object.
   *
   * `for`-`await`-`of` syntax is used with the iterable to get response elements on-demand.
   * @param {Object} request
   *   The request object that will be sent.
   * @param {string} request.parent
   *   Required. Resource name of the model to list the model evaluations for.
   *   If modelId is set as "-", this will list model evaluations from across all
   *   models of the parent location.
   * @param {string} request.filter
   *   Required. An expression for filtering the results of the request.
   *
   *     * `annotation_spec_id` - for =, !=  or existence. See example below for
   *                            the last.
   *
   *   Some examples of using the filter are:
   *
   *     * `annotation_spec_id!=4` --> The model evaluation was done for
   *                               annotation spec with ID different than 4.
   *     * `NOT annotation_spec_id:*` --> The model evaluation was done for
   *                                  aggregate of all annotation specs.
   * @param {number} request.pageSize
   *   Requested page size.
   * @param {string} request.pageToken
   *   A token identifying a page of results for the server to return.
   *   Typically obtained via
   *   {@link google.cloud.automl.v1.ListModelEvaluationsResponse.next_page_token|ListModelEvaluationsResponse.next_page_token} of the previous
   *   {@link google.cloud.automl.v1.AutoMl.ListModelEvaluations|AutoMl.ListModelEvaluations} call.
   * @param {object} [options]
   *   Call options. See {@link https://googleapis.dev/nodejs/google-gax/latest/interfaces/CallOptions.html|CallOptions} for more details.
   * @returns {Object}
   *   An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols).
   *   When you iterate the returned iterable, each element will be an object representing
   *   [ModelEvaluation]{@link google.cloud.automl.v1.ModelEvaluation}. The API will be called under the hood as needed, once per the page,
   *   so you can stop the iteration when you don't need more results.
   *   Please see the
   *   [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination)
   *   for more details and examples.
   * @example
   * const iterable = client.listModelEvaluationsAsync(request);
   * for await (const response of iterable) {
   *   // process response
   * }
   */
  listModelEvaluationsAsync(
    request?: protos.google.cloud.automl.v1.IListModelEvaluationsRequest,
    options?: CallOptions
  ): AsyncIterable<protos.google.cloud.automl.v1.IModelEvaluation> {
    request = request || {};
    options = options || {};
    options.otherArgs = options.otherArgs || {};
    options.otherArgs.headers = options.otherArgs.headers || {};
    options.otherArgs.headers['x-goog-request-params'] =
      gax.routingHeader.fromParams({
        parent: request.parent || '',
      });
    options = options || {};
    const callSettings = new gax.CallSettings(options);
    this.initialize();
    return this.descriptors.page.listModelEvaluations.asyncIterate(
      this.innerApiCalls['listModelEvaluations'] as GaxCall,
      request as unknown as RequestType,
      callSettings
    ) as AsyncIterable<protos.google.cloud.automl.v1.IModelEvaluation>;
  }
  // --------------------
  // -- Path templates --
  // --------------------

  /**
   * Return a fully-qualified annotationSpec resource name string.
   *
   * @param {string} project
   * @param {string} location
   * @param {string} dataset
   * @param {string} annotation_spec
   * @returns {string} Resource name string.
   */
  annotationSpecPath(
    project: string,
    location: string,
    dataset: string,
    annotationSpec: string
  ) {
    return this.pathTemplates.annotationSpecPathTemplate.render({
      project: project,
      location: location,
      dataset: dataset,
      annotation_spec: annotationSpec,
    });
  }

  /**
   * Parse the project from AnnotationSpec resource.
   *
   * @param {string} annotationSpecName
   *   A fully-qualified path representing AnnotationSpec resource.
   * @returns {string} A string representing the project.
   */
  matchProjectFromAnnotationSpecName(annotationSpecName: string) {
    return this.pathTemplates.annotationSpecPathTemplate.match(
      annotationSpecName
    ).project;
  }

  /**
   * Parse the location from AnnotationSpec resource.
   *
   * @param {string} annotationSpecName
   *   A fully-qualified path representing AnnotationSpec resource.
   * @returns {string} A string representing the location.
   */
  matchLocationFromAnnotationSpecName(annotationSpecName: string) {
    return this.pathTemplates.annotationSpecPathTemplate.match(
      annotationSpecName
    ).location;
  }

  /**
   * Parse the dataset from AnnotationSpec resource.
   *
   * @param {string} annotationSpecName
   *   A fully-qualified path representing AnnotationSpec resource.
   * @returns {string} A string representing the dataset.
   */
  matchDatasetFromAnnotationSpecName(annotationSpecName: string) {
    return this.pathTemplates.annotationSpecPathTemplate.match(
      annotationSpecName
    ).dataset;
  }

  /**
   * Parse the annotation_spec from AnnotationSpec resource.
   *
   * @param {string} annotationSpecName
   *   A fully-qualified path representing AnnotationSpec resource.
   * @returns {string} A string representing the annotation_spec.
   */
  matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string) {
    return this.pathTemplates.annotationSpecPathTemplate.match(
      annotationSpecName
    ).annotation_spec;
  }

  /**
   * Return a fully-qualified dataset resource name string.
   *
   * @param {string} project
   * @param {string} location
   * @param {string} dataset
   * @returns {string} Resource name string.
   */
  datasetPath(project: string, location: string, dataset: string) {
    return this.pathTemplates.datasetPathTemplate.render({
      project: project,
      location: location,
      dataset: dataset,
    });
  }

  /**
   * Parse the project from Dataset resource.
   *
   * @param {string} datasetName
   *   A fully-qualified path representing Dataset resource.
   * @returns {string} A string representing the project.
   */
  matchProjectFromDatasetName(datasetName: string) {
    return this.pathTemplates.datasetPathTemplate.match(datasetName).project;
  }

  /**
   * Parse the location from Dataset resource.
   *
   * @param {string} datasetName
   *   A fully-qualified path representing Dataset resource.
   * @returns {string} A string representing the location.
   */
  matchLocationFromDatasetName(datasetName: string) {
    return this.pathTemplates.datasetPathTemplate.match(datasetName).location;
  }

  /**
   * Parse the dataset from Dataset resource.
   *
   * @param {string} datasetName
   *   A fully-qualified path representing Dataset resource.
   * @returns {string} A string representing the dataset.
   */
  matchDatasetFromDatasetName(datasetName: string) {
    return this.pathTemplates.datasetPathTemplate.match(datasetName).dataset;
  }

  /**
   * Return a fully-qualified location resource name string.
   *
   * @param {string} project
   * @param {string} location
   * @returns {string} Resource name string.
   */
  locationPath(project: string, location: string) {
    return this.pathTemplates.locationPathTemplate.render({
      project: project,
      location: location,
    });
  }

  /**
   * Parse the project from Location resource.
   *
   * @param {string} locationName
   *   A fully-qualified path representing Location resource.
   * @returns {string} A string representing the project.
   */
  matchProjectFromLocationName(locationName: string) {
    return this.pathTemplates.locationPathTemplate.match(locationName).project;
  }

  /**
   * Parse the location from Location resource.
   *
   * @param {string} locationName
   *   A fully-qualified path representing Location resource.
   * @returns {string} A string representing the location.
   */
  matchLocationFromLocationName(locationName: string) {
    return this.pathTemplates.locationPathTemplate.match(locationName).location;
  }

  /**
   * Return a fully-qualified model resource name string.
   *
   * @param {string} project
   * @param {string} location
   * @param {string} model
   * @returns {string} Resource name string.
   */
  modelPath(project: string, location: string, model: string) {
    return this.pathTemplates.modelPathTemplate.render({
      project: project,
      location: location,
      model: model,
    });
  }

  /**
   * Parse the project from Model resource.
   *
   * @param {string} modelName
   *   A fully-qualified path representing Model resource.
   * @returns {string} A string representing the project.
   */
  matchProjectFromModelName(modelName: string) {
    return this.pathTemplates.modelPathTemplate.match(modelName).project;
  }

  /**
   * Parse the location from Model resource.
   *
   * @param {string} modelName
   *   A fully-qualified path representing Model resource.
   * @returns {string} A string representing the location.
   */
  matchLocationFromModelName(modelName: string) {
    return this.pathTemplates.modelPathTemplate.match(modelName).location;
  }

  /**
   * Parse the model from Model resource.
   *
   * @param {string} modelName
   *   A fully-qualified path representing Model resource.
   * @returns {string} A string representing the model.
   */
  matchModelFromModelName(modelName: string) {
    return this.pathTemplates.modelPathTemplate.match(modelName).model;
  }

  /**
   * Return a fully-qualified modelEvaluation resource name string.
   *
   * @param {string} project
   * @param {string} location
   * @param {string} model
   * @param {string} model_evaluation
   * @returns {string} Resource name string.
   */
  modelEvaluationPath(
    project: string,
    location: string,
    model: string,
    modelEvaluation: string
  ) {
    return this.pathTemplates.modelEvaluationPathTemplate.render({
      project: project,
      location: location,
      model: model,
      model_evaluation: modelEvaluation,
    });
  }

  /**
   * Parse the project from ModelEvaluation resource.
   *
   * @param {string} modelEvaluationName
   *   A fully-qualified path representing ModelEvaluation resource.
   * @returns {string} A string representing the project.
   */
  matchProjectFromModelEvaluationName(modelEvaluationName: string) {
    return this.pathTemplates.modelEvaluationPathTemplate.match(
      modelEvaluationName
    ).project;
  }

  /**
   * Parse the location from ModelEvaluation resource.
   *
   * @param {string} modelEvaluationName
   *   A fully-qualified path representing ModelEvaluation resource.
   * @returns {string} A string representing the location.
   */
  matchLocationFromModelEvaluationName(modelEvaluationName: string) {
    return this.pathTemplates.modelEvaluationPathTemplate.match(
      modelEvaluationName
    ).location;
  }

  /**
   * Parse the model from ModelEvaluation resource.
   *
   * @param {string} modelEvaluationName
   *   A fully-qualified path representing ModelEvaluation resource.
   * @returns {string} A string representing the model.
   */
  matchModelFromModelEvaluationName(modelEvaluationName: string) {
    return this.pathTemplates.modelEvaluationPathTemplate.match(
      modelEvaluationName
    ).model;
  }

  /**
   * Parse the model_evaluation from ModelEvaluation resource.
   *
   * @param {string} modelEvaluationName
   *   A fully-qualified path representing ModelEvaluation resource.
   * @returns {string} A string representing the model_evaluation.
   */
  matchModelEvaluationFromModelEvaluationName(modelEvaluationName: string) {
    return this.pathTemplates.modelEvaluationPathTemplate.match(
      modelEvaluationName
    ).model_evaluation;
  }

  /**
   * Terminate the gRPC channel and close the client.
   *
   * The client will no longer be usable and all future behavior is undefined.
   * @returns {Promise} A promise that resolves when the client is closed.
   */
  close(): Promise<void> {
    this.initialize();
    if (!this._terminated) {
      return this.autoMlStub!.then(stub => {
        this._terminated = true;
        stub.close();
        this.operationsClient.close();
      });
    }
    return Promise.resolve();
  }
}