Api-Roll 54: 2017-09-11

generated/googleapis/lib/prediction/v1_6.dart

 // This is a generated file (see the discoveryapis_generator project).
 
 library googleapis.prediction.v1_6;
 
 import 'dart:core' as core;
 import 'dart:async' as async;
 import 'dart:convert' as convert;
 
 import 'package:_discoveryapis_commons/_discoveryapis_commons.dart' as commons;
 import 'package:http/http.dart' as http;
 
-export 'package:_discoveryapis_commons/_discoveryapis_commons.dart' show
-    ApiRequestError, DetailedApiRequestError;
+export 'package:_discoveryapis_commons/_discoveryapis_commons.dart'
+    show ApiRequestError, DetailedApiRequestError;
 
 const core.String USER_AGENT = 'dart-api-client prediction/v1.6';
 
-/**
- * Lets you access a cloud hosted machine learning service that makes it easy to
- * build smart apps
- */
+/// Lets you access a cloud hosted machine learning service that makes it easy
+/// to build smart apps
 class PredictionApi {
-  /** View and manage your data across Google Cloud Platform services */
-  static const CloudPlatformScope = "https://www.googleapis.com/auth/cloud-platform";
+  /// View and manage your data across Google Cloud Platform services
+  static const CloudPlatformScope =
+      "https://www.googleapis.com/auth/cloud-platform";
 
-  /** Manage your data and permissions in Google Cloud Storage */
-  static const DevstorageFullControlScope = "https://www.googleapis.com/auth/devstorage.full_control";
+  /// Manage your data and permissions in Google Cloud Storage
+  static const DevstorageFullControlScope =
+      "https://www.googleapis.com/auth/devstorage.full_control";
 
-  /** View your data in Google Cloud Storage */
-  static const DevstorageReadOnlyScope = "https://www.googleapis.com/auth/devstorage.read_only";
+  /// View your data in Google Cloud Storage
+  static const DevstorageReadOnlyScope =
+      "https://www.googleapis.com/auth/devstorage.read_only";
 
-  /** Manage your data in Google Cloud Storage */
-  static const DevstorageReadWriteScope = "https://www.googleapis.com/auth/devstorage.read_write";
+  /// Manage your data in Google Cloud Storage
+  static const DevstorageReadWriteScope =
+      "https://www.googleapis.com/auth/devstorage.read_write";
 
-  /** Manage your data in the Google Prediction API */
+  /// Manage your data in the Google Prediction API
   static const PredictionScope = "https://www.googleapis.com/auth/prediction";
 
-
   final commons.ApiRequester _requester;
 
-  HostedmodelsResourceApi get hostedmodels => new HostedmodelsResourceApi(_requester);
-  TrainedmodelsResourceApi get trainedmodels => new TrainedmodelsResourceApi(_requester);
+  HostedmodelsResourceApi get hostedmodels =>
+      new HostedmodelsResourceApi(_requester);
+  TrainedmodelsResourceApi get trainedmodels =>
+      new TrainedmodelsResourceApi(_requester);
 
-  PredictionApi(http.Client client, {core.String rootUrl: "https://www.googleapis.com/", core.String servicePath: "prediction/v1.6/projects/"}) :
-      _requester = new commons.ApiRequester(client, rootUrl, servicePath, USER_AGENT);
+  PredictionApi(http.Client client,
+      {core.String rootUrl: "https://www.googleapis.com/",
+      core.String servicePath: "prediction/v1.6/projects/"})
+      : _requester =
+            new commons.ApiRequester(client, rootUrl, servicePath, USER_AGENT);
 }
 
-
 class HostedmodelsResourceApi {
   final commons.ApiRequester _requester;
 
-  HostedmodelsResourceApi(commons.ApiRequester client) : 
-      _requester = client;
+  HostedmodelsResourceApi(commons.ApiRequester client) : _requester = client;
 
-  /**
-   * Submit input and request an output against a hosted model.
-   *
-   * [request] - The metadata request object.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [hostedModelName] - The name of a hosted model.
-   *
-   * Completes with a [Output].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
-  async.Future<Output> predict(Input request, core.String project, core.String hostedModelName) {
+  /// Submit input and request an output against a hosted model.
+  ///
+  /// [request] - The metadata request object.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [hostedModelName] - The name of a hosted model.
+  ///
+  /// Completes with a [Output].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
+  async.Future<Output> predict(
+      Input request, core.String project, core.String hostedModelName) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (request != null) {
       _body = convert.JSON.encode((request).toJson());
     }
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (hostedModelName == null) {
       throw new core.ArgumentError("Parameter hostedModelName is required.");
     }
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/hostedmodels/' + commons.Escaper.ecapeVariable('$hostedModelName') + '/predict';
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/hostedmodels/' +
+        commons.Escaper.ecapeVariable('$hostedModelName') +
+        '/predict';
 
-    var _response = _requester.request(_url,
-                                       "POST",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "POST",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Output.fromJson(data));
   }
-
 }
 
-
 class TrainedmodelsResourceApi {
   final commons.ApiRequester _requester;
 
-  TrainedmodelsResourceApi(commons.ApiRequester client) : 
-      _requester = client;
+  TrainedmodelsResourceApi(commons.ApiRequester client) : _requester = client;
 
-  /**
-   * Get analysis of the model and the data the model was trained on.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [id] - The unique name for the predictive model.
-   *
-   * Completes with a [Analyze].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
+  /// Get analysis of the model and the data the model was trained on.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [id] - The unique name for the predictive model.
+  ///
+  /// Completes with a [Analyze].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
   async.Future<Analyze> analyze(core.String project, core.String id) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (id == null) {
       throw new core.ArgumentError("Parameter id is required.");
     }
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id') + '/analyze';
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/trainedmodels/' +
+        commons.Escaper.ecapeVariable('$id') +
+        '/analyze';
 
-    var _response = _requester.request(_url,
-                                       "GET",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "GET",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Analyze.fromJson(data));
   }
 
-  /**
-   * Delete a trained model.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [id] - The unique name for the predictive model.
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
+  /// Delete a trained model.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [id] - The unique name for the predictive model.
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
   async.Future delete(core.String project, core.String id) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (id == null) {
       throw new core.ArgumentError("Parameter id is required.");
     }
 
     _downloadOptions = null;
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/trainedmodels/' +
+        commons.Escaper.ecapeVariable('$id');
 
-    var _response = _requester.request(_url,
-                                       "DELETE",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "DELETE",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => null);
   }
 
-  /**
-   * Check training status of your model.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [id] - The unique name for the predictive model.
-   *
-   * Completes with a [Insert2].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
+  /// Check training status of your model.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [id] - The unique name for the predictive model.
+  ///
+  /// Completes with a [Insert2].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
   async.Future<Insert2> get(core.String project, core.String id) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (id == null) {
       throw new core.ArgumentError("Parameter id is required.");
     }
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/trainedmodels/' +
+        commons.Escaper.ecapeVariable('$id');
 
-    var _response = _requester.request(_url,
-                                       "GET",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "GET",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Insert2.fromJson(data));
   }
 
-  /**
-   * Train a Prediction API model.
-   *
-   * [request] - The metadata request object.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * Completes with a [Insert2].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
+  /// Train a Prediction API model.
+  ///
+  /// [request] - The metadata request object.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// Completes with a [Insert2].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
   async.Future<Insert2> insert(Insert request, core.String project) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (request != null) {
       _body = convert.JSON.encode((request).toJson());
     }
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
 
     _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels';
 
-    var _response = _requester.request(_url,
-                                       "POST",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "POST",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Insert2.fromJson(data));
   }
 
-  /**
-   * List available models.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [maxResults] - Maximum number of results to return.
-   *
-   * [pageToken] - Pagination token.
-   *
-   * Completes with a [List].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
-  async.Future<List> list(core.String project, {core.int maxResults, core.String pageToken}) {
+  /// List available models.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [maxResults] - Maximum number of results to return.
+  ///
+  /// [pageToken] - Pagination token.
+  ///
+  /// Completes with a [List].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
+  async.Future<List> list(core.String project,
+      {core.int maxResults, core.String pageToken}) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (maxResults != null) {
       _queryParams["maxResults"] = ["${maxResults}"];
     }
     if (pageToken != null) {
       _queryParams["pageToken"] = [pageToken];
     }
 
     _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/list';
 
-    var _response = _requester.request(_url,
-                                       "GET",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "GET",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new List.fromJson(data));
   }
 
-  /**
-   * Submit model id and request a prediction.
-   *
-   * [request] - The metadata request object.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [id] - The unique name for the predictive model.
-   *
-   * Completes with a [Output].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
-  async.Future<Output> predict(Input request, core.String project, core.String id) {
+  /// Submit model id and request a prediction.
+  ///
+  /// [request] - The metadata request object.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [id] - The unique name for the predictive model.
+  ///
+  /// Completes with a [Output].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
+  async.Future<Output> predict(
+      Input request, core.String project, core.String id) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (request != null) {
       _body = convert.JSON.encode((request).toJson());
     }
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (id == null) {
       throw new core.ArgumentError("Parameter id is required.");
     }
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id') + '/predict';
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/trainedmodels/' +
+        commons.Escaper.ecapeVariable('$id') +
+        '/predict';
 
-    var _response = _requester.request(_url,
-                                       "POST",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "POST",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Output.fromJson(data));
   }
 
-  /**
-   * Add new data to a trained model.
-   *
-   * [request] - The metadata request object.
-   *
-   * Request parameters:
-   *
-   * [project] - The project associated with the model.
-   *
-   * [id] - The unique name for the predictive model.
-   *
-   * Completes with a [Insert2].
-   *
-   * Completes with a [commons.ApiRequestError] if the API endpoint returned an
-   * error.
-   *
-   * If the used [http.Client] completes with an error when making a REST call,
-   * this method will complete with the same error.
-   */
-  async.Future<Insert2> update(Update request, core.String project, core.String id) {
+  /// Add new data to a trained model.
+  ///
+  /// [request] - The metadata request object.
+  ///
+  /// Request parameters:
+  ///
+  /// [project] - The project associated with the model.
+  ///
+  /// [id] - The unique name for the predictive model.
+  ///
+  /// Completes with a [Insert2].
+  ///
+  /// Completes with a [commons.ApiRequestError] if the API endpoint returned
+  /// an error.
+  ///
+  /// If the used [http.Client] completes with an error when making a REST
+  /// call, this method will complete with the same error.
+  async.Future<Insert2> update(
+      Update request, core.String project, core.String id) {
     var _url = null;
     var _queryParams = new core.Map();
     var _uploadMedia = null;
     var _uploadOptions = null;
     var _downloadOptions = commons.DownloadOptions.Metadata;
     var _body = null;
 
     if (request != null) {
       _body = convert.JSON.encode((request).toJson());
     }
     if (project == null) {
       throw new core.ArgumentError("Parameter project is required.");
     }
     if (id == null) {
       throw new core.ArgumentError("Parameter id is required.");
     }
 
-    _url = commons.Escaper.ecapeVariable('$project') + '/trainedmodels/' + commons.Escaper.ecapeVariable('$id');
+    _url = commons.Escaper.ecapeVariable('$project') +
+        '/trainedmodels/' +
+        commons.Escaper.ecapeVariable('$id');
 
-    var _response = _requester.request(_url,
-                                       "PUT",
-                                       body: _body,
-                                       queryParams: _queryParams,
-                                       uploadOptions: _uploadOptions,
-                                       uploadMedia: _uploadMedia,
-                                       downloadOptions: _downloadOptions);
+    var _response = _requester.request(_url, "PUT",
+        body: _body,
+        queryParams: _queryParams,
+        uploadOptions: _uploadOptions,
+        uploadMedia: _uploadMedia,
+        downloadOptions: _downloadOptions);
     return _response.then((data) => new Insert2.fromJson(data));
   }
-
 }
 
+class AnalyzeDataDescriptionFeaturesCategoricalValues {
+  /// Number of times this feature had this value.
+  core.String count;
 
-
-class AnalyzeDataDescriptionFeaturesCategoricalValues {
-  /** Number of times this feature had this value. */
-  core.String count;
-  /** The category name. */
+  /// The category name.
   core.String value;
 
   AnalyzeDataDescriptionFeaturesCategoricalValues();
 
   AnalyzeDataDescriptionFeaturesCategoricalValues.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
     if (_json.containsKey("value")) {
       value = _json["value"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     if (value != null) {
       _json["value"] = value;
     }
     return _json;
   }
 }
 
-/** Description of the categorical values of this feature. */
+/// Description of the categorical values of this feature.
 class AnalyzeDataDescriptionFeaturesCategorical {
-  /** Number of categorical values for this feature in the data. */
+  /// Number of categorical values for this feature in the data.
   core.String count;
-  /** List of all the categories for this feature in the data set. */
+
+  /// List of all the categories for this feature in the data set.
   core.List<AnalyzeDataDescriptionFeaturesCategoricalValues> values;
 
   AnalyzeDataDescriptionFeaturesCategorical();
 
   AnalyzeDataDescriptionFeaturesCategorical.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
     if (_json.containsKey("values")) {
-      values = _json["values"].map((value) => new AnalyzeDataDescriptionFeaturesCategoricalValues.fromJson(value)).toList();
+      values = _json["values"]
+          .map((value) =>
+              new AnalyzeDataDescriptionFeaturesCategoricalValues.fromJson(
+                  value))
+          .toList();
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     if (values != null) {
       _json["values"] = values.map((value) => (value).toJson()).toList();
     }
     return _json;
   }
 }
 
-/** Description of the numeric values of this feature. */
+/// Description of the numeric values of this feature.
 class AnalyzeDataDescriptionFeaturesNumeric {
-  /** Number of numeric values for this feature in the data set. */
+  /// Number of numeric values for this feature in the data set.
   core.String count;
-  /** Mean of the numeric values of this feature in the data set. */
+
+  /// Mean of the numeric values of this feature in the data set.
   core.String mean;
-  /** Variance of the numeric values of this feature in the data set. */
+
+  /// Variance of the numeric values of this feature in the data set.
   core.String variance;
 
   AnalyzeDataDescriptionFeaturesNumeric();
 
   AnalyzeDataDescriptionFeaturesNumeric.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
     if (_json.containsKey("mean")) {
       mean = _json["mean"];
     }
     if (_json.containsKey("variance")) {
       variance = _json["variance"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     if (mean != null) {
       _json["mean"] = mean;
     }
     if (variance != null) {
       _json["variance"] = variance;
     }
     return _json;
   }
 }
 
-/** Description of multiple-word text values of this feature. */
+/// Description of multiple-word text values of this feature.
 class AnalyzeDataDescriptionFeaturesText {
-  /** Number of multiple-word text values for this feature. */
+  /// Number of multiple-word text values for this feature.
   core.String count;
 
   AnalyzeDataDescriptionFeaturesText();
 
   AnalyzeDataDescriptionFeaturesText.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     return _json;
   }
 }
 
 class AnalyzeDataDescriptionFeatures {
-  /** Description of the categorical values of this feature. */
+  /// Description of the categorical values of this feature.
   AnalyzeDataDescriptionFeaturesCategorical categorical;
-  /** The feature index. */
+
+  /// The feature index.
   core.String index;
-  /** Description of the numeric values of this feature. */
+
+  /// Description of the numeric values of this feature.
   AnalyzeDataDescriptionFeaturesNumeric numeric;
-  /** Description of multiple-word text values of this feature. */
+
+  /// Description of multiple-word text values of this feature.
   AnalyzeDataDescriptionFeaturesText text;
 
   AnalyzeDataDescriptionFeatures();
 
   AnalyzeDataDescriptionFeatures.fromJson(core.Map _json) {
     if (_json.containsKey("categorical")) {
-      categorical = new AnalyzeDataDescriptionFeaturesCategorical.fromJson(_json["categorical"]);
+      categorical = new AnalyzeDataDescriptionFeaturesCategorical.fromJson(
+          _json["categorical"]);
     }
     if (_json.containsKey("index")) {
       index = _json["index"];
     }
     if (_json.containsKey("numeric")) {
-      numeric = new AnalyzeDataDescriptionFeaturesNumeric.fromJson(_json["numeric"]);
+      numeric =
+          new AnalyzeDataDescriptionFeaturesNumeric.fromJson(_json["numeric"]);
     }
     if (_json.containsKey("text")) {
       text = new AnalyzeDataDescriptionFeaturesText.fromJson(_json["text"]);
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (categorical != null) {
       _json["categorical"] = (categorical).toJson();
     }
     if (index != null) {
       _json["index"] = index;
     }
     if (numeric != null) {
       _json["numeric"] = (numeric).toJson();
     }
     if (text != null) {
       _json["text"] = (text).toJson();
     }
     return _json;
   }
 }
 
-/** Description of the output values in the data set. */
+/// Description of the output values in the data set.
 class AnalyzeDataDescriptionOutputFeatureNumeric {
-  /** Number of numeric output values in the data set. */
+  /// Number of numeric output values in the data set.
   core.String count;
-  /** Mean of the output values in the data set. */
+
+  /// Mean of the output values in the data set.
   core.String mean;
-  /** Variance of the output values in the data set. */
+
+  /// Variance of the output values in the data set.
   core.String variance;
 
   AnalyzeDataDescriptionOutputFeatureNumeric();
 
   AnalyzeDataDescriptionOutputFeatureNumeric.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
     if (_json.containsKey("mean")) {
       mean = _json["mean"];
     }
     if (_json.containsKey("variance")) {
       variance = _json["variance"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     if (mean != null) {
       _json["mean"] = mean;
     }
     if (variance != null) {
       _json["variance"] = variance;
     }
     return _json;
   }
 }
 
 class AnalyzeDataDescriptionOutputFeatureText {
-  /** Number of times the output label occurred in the data set. */
+  /// Number of times the output label occurred in the data set.
   core.String count;
-  /** The output label. */
+
+  /// The output label.
   core.String value;
 
   AnalyzeDataDescriptionOutputFeatureText();
 
   AnalyzeDataDescriptionOutputFeatureText.fromJson(core.Map _json) {
     if (_json.containsKey("count")) {
       count = _json["count"];
     }
     if (_json.containsKey("value")) {
       value = _json["value"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (count != null) {
       _json["count"] = count;
     }
     if (value != null) {
       _json["value"] = value;
     }
     return _json;
   }
 }
 
-/** Description of the output value or label. */
+/// Description of the output value or label.
 class AnalyzeDataDescriptionOutputFeature {
-  /** Description of the output values in the data set. */
+  /// Description of the output values in the data set.
   AnalyzeDataDescriptionOutputFeatureNumeric numeric;
-  /** Description of the output labels in the data set. */
+
+  /// Description of the output labels in the data set.
   core.List<AnalyzeDataDescriptionOutputFeatureText> text;
 
   AnalyzeDataDescriptionOutputFeature();
 
   AnalyzeDataDescriptionOutputFeature.fromJson(core.Map _json) {
     if (_json.containsKey("numeric")) {
-      numeric = new AnalyzeDataDescriptionOutputFeatureNumeric.fromJson(_json["numeric"]);
+      numeric = new AnalyzeDataDescriptionOutputFeatureNumeric.fromJson(
+          _json["numeric"]);
     }
     if (_json.containsKey("text")) {
-      text = _json["text"].map((value) => new AnalyzeDataDescriptionOutputFeatureText.fromJson(value)).toList();
+      text = _json["text"]
+          .map((value) =>
+              new AnalyzeDataDescriptionOutputFeatureText.fromJson(value))
+          .toList();
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (numeric != null) {
       _json["numeric"] = (numeric).toJson();
     }
     if (text != null) {
       _json["text"] = text.map((value) => (value).toJson()).toList();
     }
     return _json;
   }
 }
 
-/** Description of the data the model was trained on. */
+/// Description of the data the model was trained on.
 class AnalyzeDataDescription {
-  /** Description of the input features in the data set. */
+  /// Description of the input features in the data set.
   core.List<AnalyzeDataDescriptionFeatures> features;
-  /** Description of the output value or label. */
+
+  /// Description of the output value or label.
   AnalyzeDataDescriptionOutputFeature outputFeature;
 
   AnalyzeDataDescription();
 
   AnalyzeDataDescription.fromJson(core.Map _json) {
     if (_json.containsKey("features")) {
-      features = _json["features"].map((value) => new AnalyzeDataDescriptionFeatures.fromJson(value)).toList();
+      features = _json["features"]
+          .map((value) => new AnalyzeDataDescriptionFeatures.fromJson(value))
+          .toList();
     }
     if (_json.containsKey("outputFeature")) {
-      outputFeature = new AnalyzeDataDescriptionOutputFeature.fromJson(_json["outputFeature"]);
+      outputFeature = new AnalyzeDataDescriptionOutputFeature.fromJson(
+          _json["outputFeature"]);
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (features != null) {
       _json["features"] = features.map((value) => (value).toJson()).toList();
     }
     if (outputFeature != null) {
       _json["outputFeature"] = (outputFeature).toJson();
     }
     return _json;
   }
 }
 
-/** Description of the model. */
+/// Description of the model.
 class AnalyzeModelDescription {
-  /**
-   * An output confusion matrix. This shows an estimate for how this model will
-   * do in predictions. This is first indexed by the true class label. For each
-   * true class label, this provides a pair {predicted_label, count}, where
-   * count is the estimated number of times the model will predict the predicted
-   * label given the true label. Will not output if more then 100 classes
-   * (Categorical models only).
-   */
+  /// An output confusion matrix. This shows an estimate for how this model
+  /// will do in predictions. This is first indexed by the true class label.
+  /// For each true class label, this provides a pair {predicted_label, count},
+  /// where count is the estimated number of times the model will predict the
+  /// predicted label given the true label. Will not output if more then 100
+  /// classes (Categorical models only).
   core.Map<core.String, core.Map<core.String, core.String>> confusionMatrix;
-  /** A list of the confusion matrix row totals. */
+
+  /// A list of the confusion matrix row totals.
   core.Map<core.String, core.String> confusionMatrixRowTotals;
-  /** Basic information about the model. */
+
+  /// Basic information about the model.
   Insert2 modelinfo;
 
   AnalyzeModelDescription();
 
   AnalyzeModelDescription.fromJson(core.Map _json) {
     if (_json.containsKey("confusionMatrix")) {
       confusionMatrix = _json["confusionMatrix"];
     }
     if (_json.containsKey("confusionMatrixRowTotals")) {
       confusionMatrixRowTotals = _json["confusionMatrixRowTotals"];
     }
     if (_json.containsKey("modelinfo")) {
       modelinfo = new Insert2.fromJson(_json["modelinfo"]);
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (confusionMatrix != null) {
       _json["confusionMatrix"] = confusionMatrix;
     }
     if (confusionMatrixRowTotals != null) {
       _json["confusionMatrixRowTotals"] = confusionMatrixRowTotals;
     }
     if (modelinfo != null) {
       _json["modelinfo"] = (modelinfo).toJson();
     }
     return _json;
   }
 }
 
 class Analyze {
-  /** Description of the data the model was trained on. */
+  /// Description of the data the model was trained on.
   AnalyzeDataDescription dataDescription;
-  /** List of errors with the data. */
+
+  /// List of errors with the data.
   core.List<core.Map<core.String, core.String>> errors;
-  /** The unique name for the predictive model. */
+
+  /// The unique name for the predictive model.
   core.String id;
-  /** What kind of resource this is. */
+
+  /// What kind of resource this is.
   core.String kind;
-  /** Description of the model. */
+
+  /// Description of the model.
   AnalyzeModelDescription modelDescription;
-  /** A URL to re-request this resource. */
+
+  /// A URL to re-request this resource.
   core.String selfLink;
 
   Analyze();
 
   Analyze.fromJson(core.Map _json) {
     if (_json.containsKey("dataDescription")) {
-      dataDescription = new AnalyzeDataDescription.fromJson(_json["dataDescription"]);
+      dataDescription =
+          new AnalyzeDataDescription.fromJson(_json["dataDescription"]);
     }
     if (_json.containsKey("errors")) {
       errors = _json["errors"];
     }
     if (_json.containsKey("id")) {
       id = _json["id"];
     }
     if (_json.containsKey("kind")) {
       kind = _json["kind"];
     }
     if (_json.containsKey("modelDescription")) {
-      modelDescription = new AnalyzeModelDescription.fromJson(_json["modelDescription"]);
+      modelDescription =
+          new AnalyzeModelDescription.fromJson(_json["modelDescription"]);
     }
     if (_json.containsKey("selfLink")) {
       selfLink = _json["selfLink"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (dataDescription != null) {
       _json["dataDescription"] = (dataDescription).toJson();
     }
     if (errors != null) {
       _json["errors"] = errors;
     }
     if (id != null) {
       _json["id"] = id;
     }
     if (kind != null) {
       _json["kind"] = kind;
     }
     if (modelDescription != null) {
       _json["modelDescription"] = (modelDescription).toJson();
     }
     if (selfLink != null) {
       _json["selfLink"] = selfLink;
     }
     return _json;
   }
 }
 
-/** Input to the model for a prediction. */
+/// Input to the model for a prediction.
 class InputInput {
-  /**
-   * A list of input features, these can be strings or doubles.
-   *
-   * The values for Object must be JSON objects. It can consist of `num`,
-   * `String`, `bool` and `null` as well as `Map` and `List` values.
-   */
+  /// A list of input features, these can be strings or doubles.
+  ///
+  /// The values for Object must be JSON objects. It can consist of `num`,
+  /// `String`, `bool` and `null` as well as `Map` and `List` values.
   core.List<core.Object> csvInstance;
 
   InputInput();
 
   InputInput.fromJson(core.Map _json) {
     if (_json.containsKey("csvInstance")) {
       csvInstance = _json["csvInstance"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (csvInstance != null) {
       _json["csvInstance"] = csvInstance;
     }
     return _json;
   }
 }
 
 class Input {
-  /** Input to the model for a prediction. */
+  /// Input to the model for a prediction.
   InputInput input;
 
   Input();
 
   Input.fromJson(core.Map _json) {
     if (_json.containsKey("input")) {
       input = new InputInput.fromJson(_json["input"]);
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (input != null) {
       _json["input"] = (input).toJson();
     }
     return _json;
   }
 }
 
 class InsertTrainingInstances {
-  /**
-   * The input features for this instance.
-   *
-   * The values for Object must be JSON objects. It can consist of `num`,
-   * `String`, `bool` and `null` as well as `Map` and `List` values.
-   */
+  /// The input features for this instance.
+  ///
+  /// The values for Object must be JSON objects. It can consist of `num`,
+  /// `String`, `bool` and `null` as well as `Map` and `List` values.
   core.List<core.Object> csvInstance;
-  /** The generic output value - could be regression or class label. */
+
+  /// The generic output value - could be regression or class label.
   core.String output;
 
   InsertTrainingInstances();
 
   InsertTrainingInstances.fromJson(core.Map _json) {
     if (_json.containsKey("csvInstance")) {
       csvInstance = _json["csvInstance"];
     }
     if (_json.containsKey("output")) {
       output = _json["output"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (csvInstance != null) {
       _json["csvInstance"] = csvInstance;
     }
     if (output != null) {
       _json["output"] = output;
     }
     return _json;
   }
 }
 
 class Insert {
-  /** The unique name for the predictive model. */
+  /// The unique name for the predictive model.
   core.String id;
-  /** Type of predictive model (classification or regression). */
+
+  /// Type of predictive model (classification or regression).
   core.String modelType;
-  /** The Id of the model to be copied over. */
+
+  /// The Id of the model to be copied over.
   core.String sourceModel;
-  /** Google storage location of the training data file. */
+
+  /// Google storage location of the training data file.
   core.String storageDataLocation;
-  /** Google storage location of the preprocessing pmml file. */
+
+  /// Google storage location of the preprocessing pmml file.
   core.String storagePMMLLocation;
-  /** Google storage location of the pmml model file. */
+
+  /// Google storage location of the pmml model file.
   core.String storagePMMLModelLocation;
-  /** Instances to train model on. */
+
+  /// Instances to train model on.
   core.List<InsertTrainingInstances> trainingInstances;
-  /**
-   * A class weighting function, which allows the importance weights for class
-   * labels to be specified (Categorical models only).
-   */
+
+  /// A class weighting function, which allows the importance weights for class
+  /// labels to be specified (Categorical models only).
   core.List<core.Map<core.String, core.double>> utility;
 
   Insert();
 
   Insert.fromJson(core.Map _json) {
     if (_json.containsKey("id")) {
       id = _json["id"];
     }
     if (_json.containsKey("modelType")) {
       modelType = _json["modelType"];
     }
     if (_json.containsKey("sourceModel")) {
       sourceModel = _json["sourceModel"];
     }
     if (_json.containsKey("storageDataLocation")) {
       storageDataLocation = _json["storageDataLocation"];
     }
     if (_json.containsKey("storagePMMLLocation")) {
       storagePMMLLocation = _json["storagePMMLLocation"];
     }
     if (_json.containsKey("storagePMMLModelLocation")) {
       storagePMMLModelLocation = _json["storagePMMLModelLocation"];
     }
     if (_json.containsKey("trainingInstances")) {
-      trainingInstances = _json["trainingInstances"].map((value) => new InsertTrainingInstances.fromJson(value)).toList();
+      trainingInstances = _json["trainingInstances"]
+          .map((value) => new InsertTrainingInstances.fromJson(value))
+          .toList();
     }
     if (_json.containsKey("utility")) {
       utility = _json["utility"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (id != null) {
       _json["id"] = id;
     }
     if (modelType != null) {
       _json["modelType"] = modelType;
     }
     if (sourceModel != null) {
       _json["sourceModel"] = sourceModel;
     }
     if (storageDataLocation != null) {
       _json["storageDataLocation"] = storageDataLocation;
     }
     if (storagePMMLLocation != null) {
       _json["storagePMMLLocation"] = storagePMMLLocation;
     }
     if (storagePMMLModelLocation != null) {
       _json["storagePMMLModelLocation"] = storagePMMLModelLocation;
     }
     if (trainingInstances != null) {
-      _json["trainingInstances"] = trainingInstances.map((value) => (value).toJson()).toList();
+      _json["trainingInstances"] =
+          trainingInstances.map((value) => (value).toJson()).toList();
     }
     if (utility != null) {
       _json["utility"] = utility;
     }
     return _json;
   }
 }
 
-/** Model metadata. */
+/// Model metadata.
 class Insert2ModelInfo {
-  /**
-   * Estimated accuracy of model taking utility weights into account
-   * (Categorical models only).
-   */
+  /// Estimated accuracy of model taking utility weights into account
+  /// (Categorical models only).
   core.String classWeightedAccuracy;
-  /**
-   * A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an
-   * estimate, based on the amount and quality of the training data, of the
-   * estimated prediction accuracy. You can use this is a guide to decide
-   * whether the results are accurate enough for your needs. This estimate will
-   * be more reliable if your real input data is similar to your training data
-   * (Categorical models only).
-   */
+
+  /// A number between 0.0 and 1.0, where 1.0 is 100% accurate. This is an
+  /// estimate, based on the amount and quality of the training data, of the
+  /// estimated prediction accuracy. You can use this is a guide to decide
+  /// whether the results are accurate enough for your needs. This estimate
+  /// will be more reliable if your real input data is similar to your training
+  /// data (Categorical models only).
   core.String classificationAccuracy;
-  /**
-   * An estimated mean squared error. The can be used to measure the quality of
-   * the predicted model (Regression models only).
-   */
+
+  /// An estimated mean squared error. The can be used to measure the quality
+  /// of the predicted model (Regression models only).
   core.String meanSquaredError;
-  /** Type of predictive model (CLASSIFICATION or REGRESSION). */
+
+  /// Type of predictive model (CLASSIFICATION or REGRESSION).
   core.String modelType;
-  /** Number of valid data instances used in the trained model. */
+
+  /// Number of valid data instances used in the trained model.
   core.String numberInstances;
-  /** Number of class labels in the trained model (Categorical models only). */
+
+  /// Number of class labels in the trained model (Categorical models only).
   core.String numberLabels;
 
   Insert2ModelInfo();
 
   Insert2ModelInfo.fromJson(core.Map _json) {
     if (_json.containsKey("classWeightedAccuracy")) {
       classWeightedAccuracy = _json["classWeightedAccuracy"];
     }
     if (_json.containsKey("classificationAccuracy")) {
       classificationAccuracy = _json["classificationAccuracy"];
     }
     if (_json.containsKey("meanSquaredError")) {
       meanSquaredError = _json["meanSquaredError"];
     }
     if (_json.containsKey("modelType")) {
       modelType = _json["modelType"];
     }
     if (_json.containsKey("numberInstances")) {
       numberInstances = _json["numberInstances"];
     }
     if (_json.containsKey("numberLabels")) {
       numberLabels = _json["numberLabels"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (classWeightedAccuracy != null) {
       _json["classWeightedAccuracy"] = classWeightedAccuracy;
     }
     if (classificationAccuracy != null) {
       _json["classificationAccuracy"] = classificationAccuracy;
     }
     if (meanSquaredError != null) {
       _json["meanSquaredError"] = meanSquaredError;
     }
     if (modelType != null) {
       _json["modelType"] = modelType;
     }
     if (numberInstances != null) {
       _json["numberInstances"] = numberInstances;
     }
     if (numberLabels != null) {
       _json["numberLabels"] = numberLabels;
     }
     return _json;
   }
 }
 
 class Insert2 {
-  /** Insert time of the model (as a RFC 3339 timestamp). */
+  /// Insert time of the model (as a RFC 3339 timestamp).
   core.DateTime created;
-  /** The unique name for the predictive model. */
+
+  /// The unique name for the predictive model.
   core.String id;
-  /** What kind of resource this is. */
+
+  /// What kind of resource this is.
   core.String kind;
-  /** Model metadata. */
+
+  /// Model metadata.
   Insert2ModelInfo modelInfo;
-  /** Type of predictive model (CLASSIFICATION or REGRESSION). */
+
+  /// Type of predictive model (CLASSIFICATION or REGRESSION).
   core.String modelType;
-  /** A URL to re-request this resource. */
+
+  /// A URL to re-request this resource.
   core.String selfLink;
-  /** Google storage location of the training data file. */
+
+  /// Google storage location of the training data file.
   core.String storageDataLocation;
-  /** Google storage location of the preprocessing pmml file. */
+
+  /// Google storage location of the preprocessing pmml file.
   core.String storagePMMLLocation;
-  /** Google storage location of the pmml model file. */
+
+  /// Google storage location of the pmml model file.
   core.String storagePMMLModelLocation;
-  /** Training completion time (as a RFC 3339 timestamp). */
+
+  /// Training completion time (as a RFC 3339 timestamp).
   core.DateTime trainingComplete;
-  /**
-   * The current status of the training job. This can be one of following:
-   * RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
-   */
+
+  /// The current status of the training job. This can be one of following:
+  /// RUNNING; DONE; ERROR; ERROR: TRAINING JOB NOT FOUND
   core.String trainingStatus;
 
   Insert2();
 
   Insert2.fromJson(core.Map _json) {
     if (_json.containsKey("created")) {
       created = core.DateTime.parse(_json["created"]);
     }
     if (_json.containsKey("id")) {
       id = _json["id"];
@@ skipping 21 matching lines @@
     }
     if (_json.containsKey("trainingComplete")) {
       trainingComplete = core.DateTime.parse(_json["trainingComplete"]);
     }
     if (_json.containsKey("trainingStatus")) {
       trainingStatus = _json["trainingStatus"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (created != null) {
       _json["created"] = (created).toIso8601String();
     }
     if (id != null) {
       _json["id"] = id;
     }
     if (kind != null) {
       _json["kind"] = kind;
     }
     if (modelInfo != null) {
@@ skipping 18 matching lines @@
       _json["trainingComplete"] = (trainingComplete).toIso8601String();
     }
     if (trainingStatus != null) {
       _json["trainingStatus"] = trainingStatus;
     }
     return _json;
   }
 }
 
 class List {
-  /** List of models. */
+  /// List of models.
   core.List<Insert2> items;
-  /** What kind of resource this is. */
+
+  /// What kind of resource this is.
   core.String kind;
-  /** Pagination token to fetch the next page, if one exists. */
+
+  /// Pagination token to fetch the next page, if one exists.
   core.String nextPageToken;
-  /** A URL to re-request this resource. */
+
+  /// A URL to re-request this resource.
   core.String selfLink;
 
   List();
 
   List.fromJson(core.Map _json) {
     if (_json.containsKey("items")) {
-      items = _json["items"].map((value) => new Insert2.fromJson(value)).toList();
+      items =
+          _json["items"].map((value) => new Insert2.fromJson(value)).toList();
     }
     if (_json.containsKey("kind")) {
       kind = _json["kind"];
     }
     if (_json.containsKey("nextPageToken")) {
       nextPageToken = _json["nextPageToken"];
     }
     if (_json.containsKey("selfLink")) {
       selfLink = _json["selfLink"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (items != null) {
       _json["items"] = items.map((value) => (value).toJson()).toList();
     }
     if (kind != null) {
       _json["kind"] = kind;
     }
     if (nextPageToken != null) {
       _json["nextPageToken"] = nextPageToken;
     }
     if (selfLink != null) {
       _json["selfLink"] = selfLink;
     }
     return _json;
   }
 }
 
 class OutputOutputMulti {
-  /** The class label. */
+  /// The class label.
   core.String label;
-  /** The probability of the class label. */
+
+  /// The probability of the class label.
   core.String score;
 
   OutputOutputMulti();
 
   OutputOutputMulti.fromJson(core.Map _json) {
     if (_json.containsKey("label")) {
       label = _json["label"];
     }
     if (_json.containsKey("score")) {
       score = _json["score"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (label != null) {
       _json["label"] = label;
     }
     if (score != null) {
       _json["score"] = score;
     }
     return _json;
   }
 }
 
 class Output {
-  /** The unique name for the predictive model. */
+  /// The unique name for the predictive model.
   core.String id;
-  /** What kind of resource this is. */
+
+  /// What kind of resource this is.
   core.String kind;
-  /** The most likely class label (Categorical models only). */
+
+  /// The most likely class label (Categorical models only).
   core.String outputLabel;
-  /**
-   * A list of class labels with their estimated probabilities (Categorical
-   * models only).
-   */
+
+  /// A list of class labels with their estimated probabilities (Categorical
+  /// models only).
   core.List<OutputOutputMulti> outputMulti;
-  /** The estimated regression value (Regression models only). */
+
+  /// The estimated regression value (Regression models only).
   core.String outputValue;
-  /** A URL to re-request this resource. */
+
+  /// A URL to re-request this resource.
   core.String selfLink;
 
   Output();
 
   Output.fromJson(core.Map _json) {
     if (_json.containsKey("id")) {
       id = _json["id"];
     }
     if (_json.containsKey("kind")) {
       kind = _json["kind"];
     }
     if (_json.containsKey("outputLabel")) {
       outputLabel = _json["outputLabel"];
     }
     if (_json.containsKey("outputMulti")) {
-      outputMulti = _json["outputMulti"].map((value) => new OutputOutputMulti.fromJson(value)).toList();
+      outputMulti = _json["outputMulti"]
+          .map((value) => new OutputOutputMulti.fromJson(value))
+          .toList();
     }
     if (_json.containsKey("outputValue")) {
       outputValue = _json["outputValue"];
     }
     if (_json.containsKey("selfLink")) {
       selfLink = _json["selfLink"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (id != null) {
       _json["id"] = id;
     }
     if (kind != null) {
       _json["kind"] = kind;
     }
     if (outputLabel != null) {
       _json["outputLabel"] = outputLabel;
     }
     if (outputMulti != null) {
-      _json["outputMulti"] = outputMulti.map((value) => (value).toJson()).toList();
+      _json["outputMulti"] =
+          outputMulti.map((value) => (value).toJson()).toList();
     }
     if (outputValue != null) {
       _json["outputValue"] = outputValue;
     }
     if (selfLink != null) {
       _json["selfLink"] = selfLink;
     }
     return _json;
   }
 }
 
 class Update {
-  /**
-   * The input features for this instance.
-   *
-   * The values for Object must be JSON objects. It can consist of `num`,
-   * `String`, `bool` and `null` as well as `Map` and `List` values.
-   */
+  /// The input features for this instance.
+  ///
+  /// The values for Object must be JSON objects. It can consist of `num`,
+  /// `String`, `bool` and `null` as well as `Map` and `List` values.
   core.List<core.Object> csvInstance;
-  /** The generic output value - could be regression or class label. */
+
+  /// The generic output value - could be regression or class label.
   core.String output;
 
   Update();
 
   Update.fromJson(core.Map _json) {
     if (_json.containsKey("csvInstance")) {
       csvInstance = _json["csvInstance"];
     }
     if (_json.containsKey("output")) {
       output = _json["output"];
     }
   }
 
   core.Map<core.String, core.Object> toJson() {
-    final core.Map<core.String, core.Object> _json = new core.Map<core.String, core.Object>();
+    final core.Map<core.String, core.Object> _json =
+        new core.Map<core.String, core.Object>();
     if (csvInstance != null) {
       _json["csvInstance"] = csvInstance;
     }
     if (output != null) {
       _json["output"] = output;
     }
     return _json;
   }
 }