// Copyright 2019 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.
'use strict';
const gapicConfig = require('./auto_ml_client_config.json');
const gax = require('google-gax');
const path = require('path');
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 v1beta1
*/
class AutoMlClient {
/**
* Construct an instance of AutoMlClient.
*
* @param {object} [options] - The configuration object. See the subsequent
* parameters for more details.
* @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 {function} [options.promise] - Custom promise module to use instead
* of native Promises.
* @param {string} [options.apiEndpoint] - The domain name of the
* API remote host.
*/
constructor(opts) {
opts = opts || {};
this._descriptors = {};
if (global.isBrowser) {
// If we're in browser, we use gRPC fallback.
opts.fallback = true;
}
// If we are in browser, we are already using fallback because of the
// "browser" field in package.json.
// But if we were explicitly requested to use fallback, let's do it now.
const gaxModule = !global.isBrowser && opts.fallback ? gax.fallback : gax;
const servicePath =
opts.servicePath || opts.apiEndpoint || this.constructor.servicePath;
// Ensure that options include the service address and port.
opts = Object.assign(
{
clientConfig: {},
port: this.constructor.port,
servicePath,
},
opts
);
// Create a `gaxGrpc` object, with any grpc-specific options
// sent to the client.
opts.scopes = this.constructor.scopes;
const gaxGrpc = new gaxModule.GrpcClient(opts);
// Save the auth object to the client, for use by other methods.
this.auth = gaxGrpc.auth;
// Determine the client header string.
const clientHeader = [];
if (typeof process !== 'undefined' && 'versions' in process) {
clientHeader.push(`gl-node/${process.versions.node}`);
}
clientHeader.push(`gax/${gaxModule.version}`);
if (opts.fallback) {
clientHeader.push(`gl-web/${gaxModule.version}`);
} else {
clientHeader.push(`grpc/${gaxGrpc.grpcVersion}`);
}
clientHeader.push(`gapic/${VERSION}`);
if (opts.libName && opts.libVersion) {
clientHeader.push(`${opts.libName}/${opts.libVersion}`);
}
// Load the applicable protos.
// For Node.js, pass the path to JSON proto file.
// For browsers, pass the JSON content.
const nodejsProtoPath = path.join(
__dirname,
'..',
'..',
'protos',
'protos.json'
);
const protos = gaxGrpc.loadProto(
opts.fallback ? require('../../protos/protos.json') : nodejsProtoPath
);
// 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 gaxModule.PathTemplate(
'projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}'
),
columnSpecPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}/datasets/{dataset}/tableSpecs/{table_spec}/columnSpecs/{column_spec}'
),
datasetPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}/datasets/{dataset}'
),
locationPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}'
),
modelPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}/models/{model}'
),
modelEvaluationPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}/models/{model}/modelEvaluations/{model_evaluation}'
),
tableSpecPathTemplate: new gaxModule.PathTemplate(
'projects/{project}/locations/{location}/datasets/{dataset}/tableSpecs/{table_spec}'
),
};
// 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 gaxModule.PageDescriptor(
'pageToken',
'nextPageToken',
'datasets'
),
listModels: new gaxModule.PageDescriptor(
'pageToken',
'nextPageToken',
'model'
),
listModelEvaluations: new gaxModule.PageDescriptor(
'pageToken',
'nextPageToken',
'modelEvaluation'
),
listTableSpecs: new gaxModule.PageDescriptor(
'pageToken',
'nextPageToken',
'tableSpecs'
),
listColumnSpecs: new gaxModule.PageDescriptor(
'pageToken',
'nextPageToken',
'columnSpecs'
),
};
const protoFilesRoot = opts.fallback
? gaxModule.protobuf.Root.fromJSON(require('../../protos/protos.json'))
: gaxModule.protobuf.loadSync(nodejsProtoPath);
// 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 = new gaxModule.lro({
auth: gaxGrpc.auth,
grpc: gaxGrpc.grpc,
}).operationsClient(opts);
const deleteDatasetResponse = protoFilesRoot.lookup(
'google.protobuf.Empty'
);
const deleteDatasetMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const importDataResponse = protoFilesRoot.lookup('google.protobuf.Empty');
const importDataMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const exportDataResponse = protoFilesRoot.lookup('google.protobuf.Empty');
const exportDataMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const createModelResponse = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.Model'
);
const createModelMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const deleteModelResponse = protoFilesRoot.lookup('google.protobuf.Empty');
const deleteModelMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const deployModelResponse = protoFilesRoot.lookup('google.protobuf.Empty');
const deployModelMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const undeployModelResponse = protoFilesRoot.lookup(
'google.protobuf.Empty'
);
const undeployModelMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const exportModelResponse = protoFilesRoot.lookup('google.protobuf.Empty');
const exportModelMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
const exportEvaluatedExamplesResponse = protoFilesRoot.lookup(
'google.protobuf.Empty'
);
const exportEvaluatedExamplesMetadata = protoFilesRoot.lookup(
'google.cloud.automl.v1beta1.OperationMetadata'
);
this._descriptors.longrunning = {
deleteDataset: new gaxModule.LongrunningDescriptor(
this.operationsClient,
deleteDatasetResponse.decode.bind(deleteDatasetResponse),
deleteDatasetMetadata.decode.bind(deleteDatasetMetadata)
),
importData: new gaxModule.LongrunningDescriptor(
this.operationsClient,
importDataResponse.decode.bind(importDataResponse),
importDataMetadata.decode.bind(importDataMetadata)
),
exportData: new gaxModule.LongrunningDescriptor(
this.operationsClient,
exportDataResponse.decode.bind(exportDataResponse),
exportDataMetadata.decode.bind(exportDataMetadata)
),
createModel: new gaxModule.LongrunningDescriptor(
this.operationsClient,
createModelResponse.decode.bind(createModelResponse),
createModelMetadata.decode.bind(createModelMetadata)
),
deleteModel: new gaxModule.LongrunningDescriptor(
this.operationsClient,
deleteModelResponse.decode.bind(deleteModelResponse),
deleteModelMetadata.decode.bind(deleteModelMetadata)
),
deployModel: new gaxModule.LongrunningDescriptor(
this.operationsClient,
deployModelResponse.decode.bind(deployModelResponse),
deployModelMetadata.decode.bind(deployModelMetadata)
),
undeployModel: new gaxModule.LongrunningDescriptor(
this.operationsClient,
undeployModelResponse.decode.bind(undeployModelResponse),
undeployModelMetadata.decode.bind(undeployModelMetadata)
),
exportModel: new gaxModule.LongrunningDescriptor(
this.operationsClient,
exportModelResponse.decode.bind(exportModelResponse),
exportModelMetadata.decode.bind(exportModelMetadata)
),
exportEvaluatedExamples: new gaxModule.LongrunningDescriptor(
this.operationsClient,
exportEvaluatedExamplesResponse.decode.bind(
exportEvaluatedExamplesResponse
),
exportEvaluatedExamplesMetadata.decode.bind(
exportEvaluatedExamplesMetadata
)
),
};
// Put together the default options sent with requests.
const defaults = gaxGrpc.constructSettings(
'google.cloud.automl.v1beta1.AutoMl',
gapicConfig,
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 = {};
// Put together the "service stub" for
// google.cloud.automl.v1beta1.AutoMl.
const autoMlStub = gaxGrpc.createStub(
opts.fallback
? protos.lookupService('google.cloud.automl.v1beta1.AutoMl')
: protos.google.cloud.automl.v1beta1.AutoMl,
opts
);
// Iterate over each of the methods that the service provides
// and create an API call method for each.
const autoMlStubMethods = [
'createDataset',
'updateDataset',
'getDataset',
'listDatasets',
'deleteDataset',
'importData',
'exportData',
'createModel',
'getModel',
'listModels',
'deleteModel',
'deployModel',
'undeployModel',
'getModelEvaluation',
'exportModel',
'exportEvaluatedExamples',
'listModelEvaluations',
'getAnnotationSpec',
'getTableSpec',
'listTableSpecs',
'updateTableSpec',
'getColumnSpec',
'listColumnSpecs',
'updateColumnSpec',
];
for (const methodName of autoMlStubMethods) {
const innerCallPromise = autoMlStub.then(
stub => (...args) => {
return stub[methodName].apply(stub, args);
},
err => () => {
throw err;
}
);
this._innerApiCalls[methodName] = gaxModule.createApiCall(
innerCallPromise,
defaults[methodName],
this._descriptors.page[methodName] ||
this._descriptors.longrunning[methodName]
);
}
}
/**
* The DNS address for this API service.
*/
static get servicePath() {
return 'automl.googleapis.com';
}
/**
* The DNS address for this API service - same as servicePath(),
* exists for compatibility reasons.
*/
static get apiEndpoint() {
return 'automl.googleapis.com';
}
/**
* The port for this API service.
*/
static get port() {
return 443;
}
/**
* The scopes needed to make gRPC calls for every method defined
* in this service.
*/
static get scopes() {
return ['https://www.googleapis.com/auth/cloud-platform'];
}
/**
* Return the project ID used by this class.
* @param {function(Error, string)} callback - the callback to
* be called with the current project Id.
*/
getProjectId(callback) {
return this.auth.getProjectId(callback);
}
// -------------------
// -- Service calls --
// -------------------
/**
* Creates a dataset.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* The resource name of the project to create the dataset for.
* @param {Object} request.dataset
* The dataset to create.
*
* This object should have the same structure as [Dataset]{@link google.cloud.automl.v1beta1.Dataset}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* const dataset = {};
* const request = {
* parent: formattedParent,
* dataset: dataset,
* };
* client.createDataset(request)
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
createDataset(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.createDataset(request, options, callback);
}
/**
* Updates a dataset.
*
* @param {Object} request
* The request object that will be sent.
* @param {Object} request.dataset
* The dataset which replaces the resource on the server.
*
* This object should have the same structure as [Dataset]{@link google.cloud.automl.v1beta1.Dataset}
* @param {Object} [request.updateMask]
* The update mask applies to the resource.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const dataset = {};
* client.updateDataset({dataset: dataset})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
updateDataset(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.updateDataset(request, options, callback);
}
/**
* Gets a dataset.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* The resource name of the dataset to retrieve.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* client.getDataset({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getDataset(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getDataset(request, options, callback);
}
/**
* Lists datasets in a project.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Array, ?Object, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is Array of [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
*
* When autoPaginate: false is specified through options, it contains the result
* in a single response. If the response indicates the next page exists, the third
* parameter is set to be used for the next request object. The fourth parameter keeps
* the raw response object of an object representing [ListDatasetsResponse]{@link google.cloud.automl.v1beta1.ListDatasetsResponse}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is Array of [Dataset]{@link google.cloud.automl.v1beta1.Dataset}.
*
* When autoPaginate: false is specified through options, the array has three elements.
* The first element is Array of [Dataset]{@link google.cloud.automl.v1beta1.Dataset} in a single response.
* The second element is the next request object if the response
* indicates the next page exists, or null. The third element is
* an object representing [ListDatasetsResponse]{@link google.cloud.automl.v1beta1.ListDatasetsResponse}.
*
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* // Iterate over all elements.
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
*
* client.listDatasets({parent: formattedParent})
* .then(responses => {
* const resources = responses[0];
* for (const resource of resources) {
* // doThingsWith(resource)
* }
* })
* .catch(err => {
* console.error(err);
* });
*
* // Or obtain the paged response.
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
*
*
* const options = {autoPaginate: false};
* const callback = responses => {
* // The actual resources in a response.
* const resources = responses[0];
* // The next request if the response shows that there are more responses.
* const nextRequest = responses[1];
* // The actual response object, if necessary.
* // const rawResponse = responses[2];
* for (const resource of resources) {
* // doThingsWith(resource);
* }
* if (nextRequest) {
* // Fetch the next page.
* return client.listDatasets(nextRequest, options).then(callback);
* }
* }
* client.listDatasets({parent: formattedParent}, options)
* .then(callback)
* .catch(err => {
* console.error(err);
* });
*/
listDatasets(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.listDatasets(request, options, callback);
}
/**
* Equivalent to {@link listDatasets}, but returns a NodeJS Stream object.
*
* This fetches the paged responses for {@link listDatasets} continuously
* and invokes the callback registered for 'data' event for each element in the
* responses.
*
* The returned object has 'end' method when no more elements are required.
*
* autoPaginate option will be ignored.
*
* @see {@link https://nodejs.org/api/stream.html}
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @returns {Stream}
* An object stream which emits an object representing [Dataset]{@link google.cloud.automl.v1beta1.Dataset} on 'data' event.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* client.listDatasetsStream({parent: formattedParent})
* .on('data', element => {
* // doThingsWith(element)
* }).on('error', err => {
* console.log(err);
* });
*/
listDatasetsStream(request, options) {
options = options || {};
return this._descriptors.page.listDatasets.createStream(
this._innerApiCalls.listDatasets,
request,
options
);
}
/**
* Deletes a dataset and all of its contents.
* Returns empty response in the
* response field when it completes,
* and `delete_details` in the
* metadata field.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* The resource name of the dataset to delete.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
*
* // Handle the operation using the promise pattern.
* client.deleteDataset({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
*
* // Handle the operation using the event emitter pattern.
* client.deleteDataset({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
*
* // Handle the operation using the await pattern.
* const [operation] = await client.deleteDataset({name: formattedName});
*
* const [response] = await operation.promise();
*/
deleteDataset(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.deleteDataset(request, options, callback);
}
/**
* Imports data into a dataset.
* For Tables this method can only be called on an empty Dataset.
*
* For Tables:
* * A
* schema_inference_version
* parameter must be explicitly set.
* Returns an empty response in the
* 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 {Object} request.inputConfig
* Required. The desired input location and its domain specific semantics,
* if any.
*
* This object should have the same structure as [InputConfig]{@link google.cloud.automl.v1beta1.InputConfig}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const inputConfig = {};
* const request = {
* name: formattedName,
* inputConfig: inputConfig,
* };
*
* // Handle the operation using the promise pattern.
* client.importData(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const inputConfig = {};
* const request = {
* name: formattedName,
* inputConfig: inputConfig,
* };
*
* // Handle the operation using the event emitter pattern.
* client.importData(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const inputConfig = {};
* const request = {
* name: formattedName,
* inputConfig: inputConfig,
* };
*
* // Handle the operation using the await pattern.
* const [operation] = await client.importData(request);
*
* const [response] = await operation.promise();
*/
importData(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.importData(request, options, callback);
}
/**
* Exports dataset's data to the provided output location.
* Returns an empty response in the
* 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 {Object} request.outputConfig
* Required. The desired output location.
*
* This object should have the same structure as [OutputConfig]{@link google.cloud.automl.v1beta1.OutputConfig}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the promise pattern.
* client.exportData(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the event emitter pattern.
* client.exportData(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the await pattern.
* const [operation] = await client.exportData(request);
*
* const [response] = await operation.promise();
*/
exportData(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.exportData(request, options, callback);
}
/**
* Creates a model.
* Returns a Model in the 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
* Resource name of the parent project where the model is being created.
* @param {Object} request.model
* The model to create.
*
* This object should have the same structure as [Model]{@link google.cloud.automl.v1beta1.Model}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* const model = {};
* const request = {
* parent: formattedParent,
* model: model,
* };
*
* // Handle the operation using the promise pattern.
* client.createModel(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* const model = {};
* const request = {
* parent: formattedParent,
* model: model,
* };
*
* // Handle the operation using the event emitter pattern.
* client.createModel(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* const model = {};
* const request = {
* parent: formattedParent,
* model: model,
* };
*
* // Handle the operation using the await pattern.
* const [operation] = await client.createModel(request);
*
* const [response] = await operation.promise();
*/
createModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.createModel(request, options, callback);
}
/**
* Gets a model.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* Resource name of the model.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [Model]{@link google.cloud.automl.v1beta1.Model}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [Model]{@link google.cloud.automl.v1beta1.Model}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* client.getModel({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getModel(request, options, callback);
}
/**
* Lists models.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Array, ?Object, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is Array of [Model]{@link google.cloud.automl.v1beta1.Model}.
*
* When autoPaginate: false is specified through options, it contains the result
* in a single response. If the response indicates the next page exists, the third
* parameter is set to be used for the next request object. The fourth parameter keeps
* the raw response object of an object representing [ListModelsResponse]{@link google.cloud.automl.v1beta1.ListModelsResponse}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is Array of [Model]{@link google.cloud.automl.v1beta1.Model}.
*
* When autoPaginate: false is specified through options, the array has three elements.
* The first element is Array of [Model]{@link google.cloud.automl.v1beta1.Model} in a single response.
* The second element is the next request object if the response
* indicates the next page exists, or null. The third element is
* an object representing [ListModelsResponse]{@link google.cloud.automl.v1beta1.ListModelsResponse}.
*
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* // Iterate over all elements.
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
*
* client.listModels({parent: formattedParent})
* .then(responses => {
* const resources = responses[0];
* for (const resource of resources) {
* // doThingsWith(resource)
* }
* })
* .catch(err => {
* console.error(err);
* });
*
* // Or obtain the paged response.
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
*
*
* const options = {autoPaginate: false};
* const callback = responses => {
* // The actual resources in a response.
* const resources = responses[0];
* // The next request if the response shows that there are more responses.
* const nextRequest = responses[1];
* // The actual response object, if necessary.
* // const rawResponse = responses[2];
* for (const resource of resources) {
* // doThingsWith(resource);
* }
* if (nextRequest) {
* // Fetch the next page.
* return client.listModels(nextRequest, options).then(callback);
* }
* }
* client.listModels({parent: formattedParent}, options)
* .then(callback)
* .catch(err => {
* console.error(err);
* });
*/
listModels(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.listModels(request, options, callback);
}
/**
* Equivalent to {@link listModels}, but returns a NodeJS Stream object.
*
* This fetches the paged responses for {@link listModels} continuously
* and invokes the callback registered for 'data' event for each element in the
* responses.
*
* The returned object has 'end' method when no more elements are required.
*
* autoPaginate option will be ignored.
*
* @see {@link https://nodejs.org/api/stream.html}
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @returns {Stream}
* An object stream which emits an object representing [Model]{@link google.cloud.automl.v1beta1.Model} on 'data' event.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.locationPath('[PROJECT]', '[LOCATION]');
* client.listModelsStream({parent: formattedParent})
* .on('data', element => {
* // doThingsWith(element)
* }).on('error', err => {
* console.log(err);
* });
*/
listModelsStream(request, options) {
options = options || {};
return this._descriptors.page.listModels.createStream(
this._innerApiCalls.listModels,
request,
options
);
}
/**
* Deletes a model.
* Returns `google.protobuf.Empty` in the
* response field when it completes,
* and `delete_details` in the
* metadata field.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* Resource name of the model being deleted.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the promise pattern.
* client.deleteModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the event emitter pattern.
* client.deleteModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the await pattern.
* const [operation] = await client.deleteModel({name: formattedName});
*
* const [response] = await operation.promise();
*/
deleteModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.deleteModel(request, options, callback);
}
/**
* 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
*
* node_number)
* will reset the deployment state without pausing the model's availability.
*
* Only applicable for Text Classification, Image Object Detection and Tables; all other domains manage deployment automatically.
*
* Returns an empty response in the
* response field when it completes.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* Resource name of the model to deploy.
* @param {Object} [request.imageObjectDetectionModelDeploymentMetadata]
* Model deployment metadata specific to Image Object Detection.
*
* This object should have the same structure as [ImageObjectDetectionModelDeploymentMetadata]{@link google.cloud.automl.v1beta1.ImageObjectDetectionModelDeploymentMetadata}
* @param {Object} [request.imageClassificationModelDeploymentMetadata]
* Model deployment metadata specific to Image Classification.
*
* This object should have the same structure as [ImageClassificationModelDeploymentMetadata]{@link google.cloud.automl.v1beta1.ImageClassificationModelDeploymentMetadata}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the promise pattern.
* client.deployModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the event emitter pattern.
* client.deployModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the await pattern.
* const [operation] = await client.deployModel({name: formattedName});
*
* const [response] = await operation.promise();
*/
deployModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.deployModel(request, options, callback);
}
/**
* 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
* response field when it completes.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* Resource name of the model to undeploy.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the promise pattern.
* client.undeployModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the event emitter pattern.
* client.undeployModel({name: formattedName})
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* // Handle the operation using the await pattern.
* const [operation] = await client.undeployModel({name: formattedName});
*
* const [response] = await operation.promise();
*/
undeployModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.undeployModel(request, options, callback);
}
/**
* Gets a model evaluation.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* Resource name for the model evaluation.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelEvaluationPath('[PROJECT]', '[LOCATION]', '[MODEL]', '[MODEL_EVALUATION]');
* client.getModelEvaluation({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getModelEvaluation(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getModelEvaluation(request, options, callback);
}
/**
* 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
*
* ModelExportOutputConfig.
*
* Returns an empty response in the
* 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 {Object} request.outputConfig
* Required. The desired output location and configuration.
*
* This object should have the same structure as [ModelExportOutputConfig]{@link google.cloud.automl.v1beta1.ModelExportOutputConfig}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the promise pattern.
* client.exportModel(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the event emitter pattern.
* client.exportModel(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the await pattern.
* const [operation] = await client.exportModel(request);
*
* const [response] = await operation.promise();
*/
exportModel(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.exportModel(request, options, callback);
}
/**
* Exports examples on which the model was evaluated (i.e. which were in the
* TEST set of the dataset the model was created from), together with their
* ground truth annotations and the annotations created (predicted) by the
* model.
* The examples, ground truth and predictions are exported in the state
* they were at the moment the model was evaluated.
*
* This export is available only for 30 days since the model evaluation is
* created.
*
* Currently only available for Tables.
*
* Returns an empty response in the
* 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 whose evaluated examples are to
* be exported.
* @param {Object} request.outputConfig
* Required. The desired output location and configuration.
*
* This object should have the same structure as [ExportEvaluatedExamplesOutputConfig]{@link google.cloud.automl.v1beta1.ExportEvaluatedExamplesOutputConfig}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is a [gax.Operation]{@link https://googleapis.github.io/gax-nodejs/classes/Operation.html} object.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the promise pattern.
* client.exportEvaluatedExamples(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Operation#promise starts polling for the completion of the LRO.
* return operation.promise();
* })
* .then(responses => {
* const result = responses[0];
* const metadata = responses[1];
* const finalApiResponse = responses[2];
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the event emitter pattern.
* client.exportEvaluatedExamples(request)
* .then(responses => {
* const [operation, initialApiResponse] = responses;
*
* // Adding a listener for the "complete" event starts polling for the
* // completion of the operation.
* operation.on('complete', (result, metadata, finalApiResponse) => {
* // doSomethingWith(result);
* });
*
* // Adding a listener for the "progress" event causes the callback to be
* // called on any change in metadata when the operation is polled.
* operation.on('progress', (metadata, apiResponse) => {
* // doSomethingWith(metadata)
* });
*
* // Adding a listener for the "error" event handles any errors found during polling.
* operation.on('error', err => {
* // throw(err);
* });
* })
* .catch(err => {
* console.error(err);
* });
*
* const formattedName = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* const outputConfig = {};
* const request = {
* name: formattedName,
* outputConfig: outputConfig,
* };
*
* // Handle the operation using the await pattern.
* const [operation] = await client.exportEvaluatedExamples(request);
*
* const [response] = await operation.promise();
*/
exportEvaluatedExamples(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.exportEvaluatedExamples(
request,
options,
callback
);
}
/**
* Lists model evaluations.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Array, ?Object, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is Array of [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation}.
*
* When autoPaginate: false is specified through options, it contains the result
* in a single response. If the response indicates the next page exists, the third
* parameter is set to be used for the next request object. The fourth parameter keeps
* the raw response object of an object representing [ListModelEvaluationsResponse]{@link google.cloud.automl.v1beta1.ListModelEvaluationsResponse}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is Array of [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation}.
*
* When autoPaginate: false is specified through options, the array has three elements.
* The first element is Array of [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation} in a single response.
* The second element is the next request object if the response
* indicates the next page exists, or null. The third element is
* an object representing [ListModelEvaluationsResponse]{@link google.cloud.automl.v1beta1.ListModelEvaluationsResponse}.
*
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* // Iterate over all elements.
* const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
* client.listModelEvaluations({parent: formattedParent})
* .then(responses => {
* const resources = responses[0];
* for (const resource of resources) {
* // doThingsWith(resource)
* }
* })
* .catch(err => {
* console.error(err);
* });
*
* // Or obtain the paged response.
* const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
*
*
* const options = {autoPaginate: false};
* const callback = responses => {
* // The actual resources in a response.
* const resources = responses[0];
* // The next request if the response shows that there are more responses.
* const nextRequest = responses[1];
* // The actual response object, if necessary.
* // const rawResponse = responses[2];
* for (const resource of resources) {
* // doThingsWith(resource);
* }
* if (nextRequest) {
* // Fetch the next page.
* return client.listModelEvaluations(nextRequest, options).then(callback);
* }
* }
* client.listModelEvaluations({parent: formattedParent}, options)
* .then(callback)
* .catch(err => {
* console.error(err);
* });
*/
listModelEvaluations(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.listModelEvaluations(request, options, callback);
}
/**
* Equivalent to {@link listModelEvaluations}, but returns a NodeJS Stream object.
*
* This fetches the paged responses for {@link listModelEvaluations} continuously
* and invokes the callback registered for 'data' event for each element in the
* responses.
*
* The returned object has 'end' method when no more elements are required.
*
* autoPaginate option will be ignored.
*
* @see {@link https://nodejs.org/api/stream.html}
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* 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]
* 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]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @returns {Stream}
* An object stream which emits an object representing [ModelEvaluation]{@link google.cloud.automl.v1beta1.ModelEvaluation} on 'data' event.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.modelPath('[PROJECT]', '[LOCATION]', '[MODEL]');
* client.listModelEvaluationsStream({parent: formattedParent})
* .on('data', element => {
* // doThingsWith(element)
* }).on('error', err => {
* console.log(err);
* });
*/
listModelEvaluationsStream(request, options) {
options = options || {};
return this._descriptors.page.listModelEvaluations.createStream(
this._innerApiCalls.listModelEvaluations,
request,
options
);
}
/**
* Gets an annotation spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* The resource name of the annotation spec to retrieve.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [AnnotationSpec]{@link google.cloud.automl.v1beta1.AnnotationSpec}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [AnnotationSpec]{@link google.cloud.automl.v1beta1.AnnotationSpec}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.annotationSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[ANNOTATION_SPEC]');
* client.getAnnotationSpec({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getAnnotationSpec(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getAnnotationSpec(request, options, callback);
}
/**
* Gets a table spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* The resource name of the table spec to retrieve.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
* client.getTableSpec({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getTableSpec(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getTableSpec(request, options, callback);
}
/**
* Lists table specs in a dataset.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* The resource name of the dataset to list table specs from.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {string} [request.filter]
* Filter expression, see go/filtering.
* @param {number} [request.pageSize]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Array, ?Object, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is Array of [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
*
* When autoPaginate: false is specified through options, it contains the result
* in a single response. If the response indicates the next page exists, the third
* parameter is set to be used for the next request object. The fourth parameter keeps
* the raw response object of an object representing [ListTableSpecsResponse]{@link google.cloud.automl.v1beta1.ListTableSpecsResponse}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is Array of [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
*
* When autoPaginate: false is specified through options, the array has three elements.
* The first element is Array of [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec} in a single response.
* The second element is the next request object if the response
* indicates the next page exists, or null. The third element is
* an object representing [ListTableSpecsResponse]{@link google.cloud.automl.v1beta1.ListTableSpecsResponse}.
*
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* // Iterate over all elements.
* const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
*
* client.listTableSpecs({parent: formattedParent})
* .then(responses => {
* const resources = responses[0];
* for (const resource of resources) {
* // doThingsWith(resource)
* }
* })
* .catch(err => {
* console.error(err);
* });
*
* // Or obtain the paged response.
* const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
*
*
* const options = {autoPaginate: false};
* const callback = responses => {
* // The actual resources in a response.
* const resources = responses[0];
* // The next request if the response shows that there are more responses.
* const nextRequest = responses[1];
* // The actual response object, if necessary.
* // const rawResponse = responses[2];
* for (const resource of resources) {
* // doThingsWith(resource);
* }
* if (nextRequest) {
* // Fetch the next page.
* return client.listTableSpecs(nextRequest, options).then(callback);
* }
* }
* client.listTableSpecs({parent: formattedParent}, options)
* .then(callback)
* .catch(err => {
* console.error(err);
* });
*/
listTableSpecs(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.listTableSpecs(request, options, callback);
}
/**
* Equivalent to {@link listTableSpecs}, but returns a NodeJS Stream object.
*
* This fetches the paged responses for {@link listTableSpecs} continuously
* and invokes the callback registered for 'data' event for each element in the
* responses.
*
* The returned object has 'end' method when no more elements are required.
*
* autoPaginate option will be ignored.
*
* @see {@link https://nodejs.org/api/stream.html}
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* The resource name of the dataset to list table specs from.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {string} [request.filter]
* Filter expression, see go/filtering.
* @param {number} [request.pageSize]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @returns {Stream}
* An object stream which emits an object representing [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec} on 'data' event.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.datasetPath('[PROJECT]', '[LOCATION]', '[DATASET]');
* client.listTableSpecsStream({parent: formattedParent})
* .on('data', element => {
* // doThingsWith(element)
* }).on('error', err => {
* console.log(err);
* });
*/
listTableSpecsStream(request, options) {
options = options || {};
return this._descriptors.page.listTableSpecs.createStream(
this._innerApiCalls.listTableSpecs,
request,
options
);
}
/**
* Updates a table spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {Object} request.tableSpec
* The table spec which replaces the resource on the server.
*
* This object should have the same structure as [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}
* @param {Object} [request.updateMask]
* The update mask applies to the resource.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [TableSpec]{@link google.cloud.automl.v1beta1.TableSpec}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const tableSpec = {};
* client.updateTableSpec({tableSpec: tableSpec})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
updateTableSpec(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
options = options || {};
options.otherArgs = options.otherArgs || {};
options.otherArgs.headers = options.otherArgs.headers || {};
options.otherArgs.headers[
'x-goog-request-params'
] = gax.routingHeader.fromParams({
'table_spec.name': request.tableSpec.name,
});
return this._innerApiCalls.updateTableSpec(request, options, callback);
}
/**
* Gets a column spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.name
* The resource name of the column spec to retrieve.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedName = client.columnSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]', '[COLUMN_SPEC]');
* client.getColumnSpec({name: formattedName})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
getColumnSpec(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
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,
});
return this._innerApiCalls.getColumnSpec(request, options, callback);
}
/**
* Lists column specs in a table spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* The resource name of the table spec to list column specs from.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {string} [request.filter]
* Filter expression, see go/filtering.
* @param {number} [request.pageSize]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Array, ?Object, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is Array of [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
*
* When autoPaginate: false is specified through options, it contains the result
* in a single response. If the response indicates the next page exists, the third
* parameter is set to be used for the next request object. The fourth parameter keeps
* the raw response object of an object representing [ListColumnSpecsResponse]{@link google.cloud.automl.v1beta1.ListColumnSpecsResponse}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is Array of [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
*
* When autoPaginate: false is specified through options, the array has three elements.
* The first element is Array of [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec} in a single response.
* The second element is the next request object if the response
* indicates the next page exists, or null. The third element is
* an object representing [ListColumnSpecsResponse]{@link google.cloud.automl.v1beta1.ListColumnSpecsResponse}.
*
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* // Iterate over all elements.
* const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
*
* client.listColumnSpecs({parent: formattedParent})
* .then(responses => {
* const resources = responses[0];
* for (const resource of resources) {
* // doThingsWith(resource)
* }
* })
* .catch(err => {
* console.error(err);
* });
*
* // Or obtain the paged response.
* const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
*
*
* const options = {autoPaginate: false};
* const callback = responses => {
* // The actual resources in a response.
* const resources = responses[0];
* // The next request if the response shows that there are more responses.
* const nextRequest = responses[1];
* // The actual response object, if necessary.
* // const rawResponse = responses[2];
* for (const resource of resources) {
* // doThingsWith(resource);
* }
* if (nextRequest) {
* // Fetch the next page.
* return client.listColumnSpecs(nextRequest, options).then(callback);
* }
* }
* client.listColumnSpecs({parent: formattedParent}, options)
* .then(callback)
* .catch(err => {
* console.error(err);
* });
*/
listColumnSpecs(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
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,
});
return this._innerApiCalls.listColumnSpecs(request, options, callback);
}
/**
* Equivalent to {@link listColumnSpecs}, but returns a NodeJS Stream object.
*
* This fetches the paged responses for {@link listColumnSpecs} continuously
* and invokes the callback registered for 'data' event for each element in the
* responses.
*
* The returned object has 'end' method when no more elements are required.
*
* autoPaginate option will be ignored.
*
* @see {@link https://nodejs.org/api/stream.html}
*
* @param {Object} request
* The request object that will be sent.
* @param {string} request.parent
* The resource name of the table spec to list column specs from.
* @param {Object} [request.fieldMask]
* Mask specifying which fields to read.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {string} [request.filter]
* Filter expression, see go/filtering.
* @param {number} [request.pageSize]
* The maximum number of resources contained in the underlying API
* response. If page streaming is performed per-resource, this
* parameter does not affect the return value. If page streaming is
* performed per-page, this determines the maximum number of
* resources in a page.
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @returns {Stream}
* An object stream which emits an object representing [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec} on 'data' event.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const formattedParent = client.tableSpecPath('[PROJECT]', '[LOCATION]', '[DATASET]', '[TABLE_SPEC]');
* client.listColumnSpecsStream({parent: formattedParent})
* .on('data', element => {
* // doThingsWith(element)
* }).on('error', err => {
* console.log(err);
* });
*/
listColumnSpecsStream(request, options) {
options = options || {};
return this._descriptors.page.listColumnSpecs.createStream(
this._innerApiCalls.listColumnSpecs,
request,
options
);
}
/**
* Updates a column spec.
*
* @param {Object} request
* The request object that will be sent.
* @param {Object} request.columnSpec
* The column spec which replaces the resource on the server.
*
* This object should have the same structure as [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}
* @param {Object} [request.updateMask]
* The update mask applies to the resource.
*
* This object should have the same structure as [FieldMask]{@link google.protobuf.FieldMask}
* @param {Object} [options]
* Optional parameters. You can override the default settings for this call, e.g, timeout,
* retries, paginations, etc. See [gax.CallOptions]{@link https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html} for the details.
* @param {function(?Error, ?Object)} [callback]
* The function which will be called with the result of the API call.
*
* The second parameter to the callback is an object representing [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
* @returns {Promise} - The promise which resolves to an array.
* The first element of the array is an object representing [ColumnSpec]{@link google.cloud.automl.v1beta1.ColumnSpec}.
* The promise has a method named "cancel" which cancels the ongoing API call.
*
* @example
*
* const automl = require('@google-cloud/automl');
*
* const client = new automl.v1beta1.AutoMlClient({
* // optional auth parameters.
* });
*
* const columnSpec = {};
* client.updateColumnSpec({columnSpec: columnSpec})
* .then(responses => {
* const response = responses[0];
* // doThingsWith(response)
* })
* .catch(err => {
* console.error(err);
* });
*/
updateColumnSpec(request, options, callback) {
if (options instanceof Function && callback === undefined) {
callback = options;
options = {};
}
request = request || {};
options = options || {};
options.otherArgs = options.otherArgs || {};
options.otherArgs.headers = options.otherArgs.headers || {};
options.otherArgs.headers[
'x-goog-request-params'
] = gax.routingHeader.fromParams({
'column_spec.name': request.columnSpec.name,
});
return this._innerApiCalls.updateColumnSpec(request, options, callback);
}
// --------------------
// -- Path templates --
// --------------------
/**
* Return a fully-qualified annotation_spec resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} dataset
* @param {String} annotationSpec
* @returns {String}
*/
annotationSpecPath(project, location, dataset, annotationSpec) {
return this._pathTemplates.annotationSpecPathTemplate.render({
project: project,
location: location,
dataset: dataset,
annotation_spec: annotationSpec,
});
}
/**
* Return a fully-qualified column_spec resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} dataset
* @param {String} tableSpec
* @param {String} columnSpec
* @returns {String}
*/
columnSpecPath(project, location, dataset, tableSpec, columnSpec) {
return this._pathTemplates.columnSpecPathTemplate.render({
project: project,
location: location,
dataset: dataset,
table_spec: tableSpec,
column_spec: columnSpec,
});
}
/**
* Return a fully-qualified dataset resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} dataset
* @returns {String}
*/
datasetPath(project, location, dataset) {
return this._pathTemplates.datasetPathTemplate.render({
project: project,
location: location,
dataset: dataset,
});
}
/**
* Return a fully-qualified location resource name string.
*
* @param {String} project
* @param {String} location
* @returns {String}
*/
locationPath(project, location) {
return this._pathTemplates.locationPathTemplate.render({
project: project,
location: location,
});
}
/**
* Return a fully-qualified model resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} model
* @returns {String}
*/
modelPath(project, location, model) {
return this._pathTemplates.modelPathTemplate.render({
project: project,
location: location,
model: model,
});
}
/**
* Return a fully-qualified model_evaluation resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} model
* @param {String} modelEvaluation
* @returns {String}
*/
modelEvaluationPath(project, location, model, modelEvaluation) {
return this._pathTemplates.modelEvaluationPathTemplate.render({
project: project,
location: location,
model: model,
model_evaluation: modelEvaluation,
});
}
/**
* Return a fully-qualified table_spec resource name string.
*
* @param {String} project
* @param {String} location
* @param {String} dataset
* @param {String} tableSpec
* @returns {String}
*/
tableSpecPath(project, location, dataset, tableSpec) {
return this._pathTemplates.tableSpecPathTemplate.render({
project: project,
location: location,
dataset: dataset,
table_spec: tableSpec,
});
}
/**
* Parse the annotationSpecName from a annotation_spec resource.
*
* @param {String} annotationSpecName
* A fully-qualified path representing a annotation_spec resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromAnnotationSpecName(annotationSpecName) {
return this._pathTemplates.annotationSpecPathTemplate.match(
annotationSpecName
).project;
}
/**
* Parse the annotationSpecName from a annotation_spec resource.
*
* @param {String} annotationSpecName
* A fully-qualified path representing a annotation_spec resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromAnnotationSpecName(annotationSpecName) {
return this._pathTemplates.annotationSpecPathTemplate.match(
annotationSpecName
).location;
}
/**
* Parse the annotationSpecName from a annotation_spec resource.
*
* @param {String} annotationSpecName
* A fully-qualified path representing a annotation_spec resources.
* @returns {String} - A string representing the dataset.
*/
matchDatasetFromAnnotationSpecName(annotationSpecName) {
return this._pathTemplates.annotationSpecPathTemplate.match(
annotationSpecName
).dataset;
}
/**
* Parse the annotationSpecName from a annotation_spec resource.
*
* @param {String} annotationSpecName
* A fully-qualified path representing a annotation_spec resources.
* @returns {String} - A string representing the annotation_spec.
*/
matchAnnotationSpecFromAnnotationSpecName(annotationSpecName) {
return this._pathTemplates.annotationSpecPathTemplate.match(
annotationSpecName
).annotation_spec;
}
/**
* Parse the columnSpecName from a column_spec resource.
*
* @param {String} columnSpecName
* A fully-qualified path representing a column_spec resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromColumnSpecName(columnSpecName) {
return this._pathTemplates.columnSpecPathTemplate.match(columnSpecName)
.project;
}
/**
* Parse the columnSpecName from a column_spec resource.
*
* @param {String} columnSpecName
* A fully-qualified path representing a column_spec resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromColumnSpecName(columnSpecName) {
return this._pathTemplates.columnSpecPathTemplate.match(columnSpecName)
.location;
}
/**
* Parse the columnSpecName from a column_spec resource.
*
* @param {String} columnSpecName
* A fully-qualified path representing a column_spec resources.
* @returns {String} - A string representing the dataset.
*/
matchDatasetFromColumnSpecName(columnSpecName) {
return this._pathTemplates.columnSpecPathTemplate.match(columnSpecName)
.dataset;
}
/**
* Parse the columnSpecName from a column_spec resource.
*
* @param {String} columnSpecName
* A fully-qualified path representing a column_spec resources.
* @returns {String} - A string representing the table_spec.
*/
matchTableSpecFromColumnSpecName(columnSpecName) {
return this._pathTemplates.columnSpecPathTemplate.match(columnSpecName)
.table_spec;
}
/**
* Parse the columnSpecName from a column_spec resource.
*
* @param {String} columnSpecName
* A fully-qualified path representing a column_spec resources.
* @returns {String} - A string representing the column_spec.
*/
matchColumnSpecFromColumnSpecName(columnSpecName) {
return this._pathTemplates.columnSpecPathTemplate.match(columnSpecName)
.column_spec;
}
/**
* Parse the datasetName from a dataset resource.
*
* @param {String} datasetName
* A fully-qualified path representing a dataset resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromDatasetName(datasetName) {
return this._pathTemplates.datasetPathTemplate.match(datasetName).project;
}
/**
* Parse the datasetName from a dataset resource.
*
* @param {String} datasetName
* A fully-qualified path representing a dataset resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromDatasetName(datasetName) {
return this._pathTemplates.datasetPathTemplate.match(datasetName).location;
}
/**
* Parse the datasetName from a dataset resource.
*
* @param {String} datasetName
* A fully-qualified path representing a dataset resources.
* @returns {String} - A string representing the dataset.
*/
matchDatasetFromDatasetName(datasetName) {
return this._pathTemplates.datasetPathTemplate.match(datasetName).dataset;
}
/**
* Parse the locationName from a location resource.
*
* @param {String} locationName
* A fully-qualified path representing a location resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromLocationName(locationName) {
return this._pathTemplates.locationPathTemplate.match(locationName).project;
}
/**
* Parse the locationName from a location resource.
*
* @param {String} locationName
* A fully-qualified path representing a location resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromLocationName(locationName) {
return this._pathTemplates.locationPathTemplate.match(locationName)
.location;
}
/**
* Parse the modelName from a model resource.
*
* @param {String} modelName
* A fully-qualified path representing a model resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromModelName(modelName) {
return this._pathTemplates.modelPathTemplate.match(modelName).project;
}
/**
* Parse the modelName from a model resource.
*
* @param {String} modelName
* A fully-qualified path representing a model resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromModelName(modelName) {
return this._pathTemplates.modelPathTemplate.match(modelName).location;
}
/**
* Parse the modelName from a model resource.
*
* @param {String} modelName
* A fully-qualified path representing a model resources.
* @returns {String} - A string representing the model.
*/
matchModelFromModelName(modelName) {
return this._pathTemplates.modelPathTemplate.match(modelName).model;
}
/**
* Parse the modelEvaluationName from a model_evaluation resource.
*
* @param {String} modelEvaluationName
* A fully-qualified path representing a model_evaluation resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromModelEvaluationName(modelEvaluationName) {
return this._pathTemplates.modelEvaluationPathTemplate.match(
modelEvaluationName
).project;
}
/**
* Parse the modelEvaluationName from a model_evaluation resource.
*
* @param {String} modelEvaluationName
* A fully-qualified path representing a model_evaluation resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromModelEvaluationName(modelEvaluationName) {
return this._pathTemplates.modelEvaluationPathTemplate.match(
modelEvaluationName
).location;
}
/**
* Parse the modelEvaluationName from a model_evaluation resource.
*
* @param {String} modelEvaluationName
* A fully-qualified path representing a model_evaluation resources.
* @returns {String} - A string representing the model.
*/
matchModelFromModelEvaluationName(modelEvaluationName) {
return this._pathTemplates.modelEvaluationPathTemplate.match(
modelEvaluationName
).model;
}
/**
* Parse the modelEvaluationName from a model_evaluation resource.
*
* @param {String} modelEvaluationName
* A fully-qualified path representing a model_evaluation resources.
* @returns {String} - A string representing the model_evaluation.
*/
matchModelEvaluationFromModelEvaluationName(modelEvaluationName) {
return this._pathTemplates.modelEvaluationPathTemplate.match(
modelEvaluationName
).model_evaluation;
}
/**
* Parse the tableSpecName from a table_spec resource.
*
* @param {String} tableSpecName
* A fully-qualified path representing a table_spec resources.
* @returns {String} - A string representing the project.
*/
matchProjectFromTableSpecName(tableSpecName) {
return this._pathTemplates.tableSpecPathTemplate.match(tableSpecName)
.project;
}
/**
* Parse the tableSpecName from a table_spec resource.
*
* @param {String} tableSpecName
* A fully-qualified path representing a table_spec resources.
* @returns {String} - A string representing the location.
*/
matchLocationFromTableSpecName(tableSpecName) {
return this._pathTemplates.tableSpecPathTemplate.match(tableSpecName)
.location;
}
/**
* Parse the tableSpecName from a table_spec resource.
*
* @param {String} tableSpecName
* A fully-qualified path representing a table_spec resources.
* @returns {String} - A string representing the dataset.
*/
matchDatasetFromTableSpecName(tableSpecName) {
return this._pathTemplates.tableSpecPathTemplate.match(tableSpecName)
.dataset;
}
/**
* Parse the tableSpecName from a table_spec resource.
*
* @param {String} tableSpecName
* A fully-qualified path representing a table_spec resources.
* @returns {String} - A string representing the table_spec.
*/
matchTableSpecFromTableSpecName(tableSpecName) {
return this._pathTemplates.tableSpecPathTemplate.match(tableSpecName)
.table_spec;
}
}
module.exports = AutoMlClient;