Class v1beta1.AutoMlClient (2.5.2)

Version 2.5.2

• 4.0.1 (latest)
• 4.0.0
• 3.1.2
• 2.5.2
• 2.4.5

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. v1beta1

Package

@google-cloud/automl

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Construct an instance of AutoMlClient.

Parameter

Name	Description
opts	ClientOptions

Properties

apiEndpoint

static get apiEndpoint(): string;

The DNS address for this API service - same as servicePath(), exists for compatibility reasons.

auth

auth: gax.GoogleAuth;

autoMlStub

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

descriptors

descriptors: Descriptors;

innerApiCalls

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

operationsClient

operationsClient: gax.OperationsClient;

pathTemplates

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

port

static get port(): number;

The port for this API service.

scopes

static get scopes(): string[];

The scopes needed to make gRPC calls for every method defined in this service.

servicePath

static get servicePath(): string;

The DNS address for this API service.

warn

warn: (code: string, message: string, warnType?: string) => void;

Methods

annotationSpecPath(project, location, dataset, annotationSpec)

annotationSpecPath(project: string, location: string, dataset: string, annotationSpec: string): string;

Return a fully-qualified annotationSpec resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
annotationSpec	string

Returns

Type	Description
string	{string} Resource name string.

checkCreateModelProgress(name)

checkCreateModelProgress(name: string): Promise<LROperation<protos.google.cloud.automl.v1beta1.Model, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by createModel().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.cloud.automl.v1beta1.Model, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the parent project where the model is being created.
   */
  // const parent = 'abc123'
  /**
   *  Required. The model to create.
   */
  // const model = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callCreateModel();

checkDeleteDatasetProgress(name)

checkDeleteDatasetProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by deleteDataset().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset to delete.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeleteDataset();

checkDeleteModelProgress(name)

checkDeleteModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by deleteModel().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model being deleted.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeleteModel();

checkDeployModelProgress(name)

checkDeployModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by deployModel().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Model deployment metadata specific to Image Object Detection.
   */
  // const imageObjectDetectionModelDeploymentMetadata = {}
  /**
   *  Model deployment metadata specific to Image Classification.
   */
  // const imageClassificationModelDeploymentMetadata = {}
  /**
   *  Required. Resource name of the model to deploy.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeployModel();

checkExportDataProgress(name)

checkExportDataProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by exportData().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportData();

checkExportEvaluatedExamplesProgress(name)

checkExportEvaluatedExamplesProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by exportEvaluatedExamples().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the model whose evaluated examples are to
   *  be exported.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportEvaluatedExamples();

checkExportModelProgress(name)

checkExportModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by exportModel().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the model to export.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportModel();

checkImportDataProgress(name)

checkImportDataProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by importData().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Dataset name. Dataset must already exist. All imported
   *  annotations and examples will be added.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired input location and its domain specific semantics,
   *  if any.
   */
  // const inputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callImportData();

checkUndeployModelProgress(name)

checkUndeployModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>;

Check the status of the long running operation returned by undeployModel().

Parameter

Name	Description
name	string The operation name that will be passed.

Returns

Type	Description
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1beta1.OperationMetadata>>	{Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model to undeploy.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callUndeployModel();

close()

close(): Promise<void>;

Terminate the gRPC channel and close the client.

The client will no longer be usable and all future behavior is undefined.

Returns

Type	Description
Promise<void>	{Promise} A promise that resolves when the client is closed.

columnSpecPath(project, location, dataset, tableSpec, columnSpec)

columnSpecPath(project: string, location: string, dataset: string, tableSpec: string, columnSpec: string): string;

Return a fully-qualified columnSpec resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
tableSpec	string
columnSpec	string

Returns

Type	Description
string	{string} Resource name string.

createDataset(request, options)

createDataset(request?: protos.google.cloud.automl.v1beta1.ICreateDatasetRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | undefined, {} | undefined]>;

Creates a dataset.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateDatasetRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Dataset]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the project to create the dataset for.
   */
  // const parent = 'abc123'
  /**
   *  Required. The dataset to create.
   */
  // const dataset = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.createDataset(request);
    console.log(response);
  }

  callCreateDataset();

createDataset(request, options, callback)

createDataset(request: protos.google.cloud.automl.v1beta1.ICreateDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateDatasetRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createDataset(request, callback)

createDataset(request: protos.google.cloud.automl.v1beta1.ICreateDatasetRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateDatasetRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.ICreateDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createModel(request, options)

createModel(request?: protos.google.cloud.automl.v1beta1.ICreateModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Creates a model. Returns a Model in the 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.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the parent project where the model is being created.
   */
  // const parent = 'abc123'
  /**
   *  Required. The model to create.
   */
  // const model = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callCreateModel();

createModel(request, options, callback)

createModel(request: protos.google.cloud.automl.v1beta1.ICreateModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateModelRequest
options	CallOptions
callback	Callback<LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

createModel(request, callback)

createModel(request: protos.google.cloud.automl.v1beta1.ICreateModelRequest, callback: Callback<LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.ICreateModelRequest
callback	Callback<LROperation<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

datasetPath(project, location, dataset)

datasetPath(project: string, location: string, dataset: string): string;

Return a fully-qualified dataset resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string

Returns

Type	Description
string	{string} Resource name string.

deleteDataset(request, options)

deleteDataset(request?: protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Deletes a dataset and all of its contents. Returns empty response in the field when it completes, and delete_details in the field.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset to delete.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeleteDataset();

deleteDataset(request, options, callback)

deleteDataset(request: protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteDataset(request, callback)

deleteDataset(request: protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteDatasetRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteModel(request, options)

deleteModel(request?: protos.google.cloud.automl.v1beta1.IDeleteModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Deletes a model. Returns google.protobuf.Empty in the field when it completes, and delete_details in the field.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model being deleted.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeleteModel();

deleteModel(request, options, callback)

deleteModel(request: protos.google.cloud.automl.v1beta1.IDeleteModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteModelRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deleteModel(request, callback)

deleteModel(request: protos.google.cloud.automl.v1beta1.IDeleteModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeleteModelRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deployModel(request, options)

deployModel(request?: protos.google.cloud.automl.v1beta1.IDeployModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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

) will reset the deployment state without pausing the model's availability.

Only applicable for Text Classification, Image Object Detection , Tables, and Image Segmentation; all other domains manage deployment automatically.

Returns an empty response in the field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeployModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Model deployment metadata specific to Image Object Detection.
   */
  // const imageObjectDetectionModelDeploymentMetadata = {}
  /**
   *  Model deployment metadata specific to Image Classification.
   */
  // const imageClassificationModelDeploymentMetadata = {}
  /**
   *  Required. Resource name of the model to deploy.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callDeployModel();

deployModel(request, options, callback)

deployModel(request: protos.google.cloud.automl.v1beta1.IDeployModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeployModelRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

deployModel(request, callback)

deployModel(request: protos.google.cloud.automl.v1beta1.IDeployModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IDeployModelRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportData(request, options)

exportData(request?: protos.google.cloud.automl.v1beta1.IExportDataRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Exports dataset's data to the provided output location. Returns an empty response in the field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportDataRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportData();

exportData(request, options, callback)

exportData(request: protos.google.cloud.automl.v1beta1.IExportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportDataRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportData(request, callback)

exportData(request: protos.google.cloud.automl.v1beta1.IExportDataRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportDataRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportEvaluatedExamples(request, options)

exportEvaluatedExamples(request?: protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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 field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the model whose evaluated examples are to
   *  be exported.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportEvaluatedExamples();

exportEvaluatedExamples(request, options, callback)

exportEvaluatedExamples(request: protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportEvaluatedExamples(request, callback)

exportEvaluatedExamples(request: protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportEvaluatedExamplesRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportModel(request, options)

exportModel(request?: protos.google.cloud.automl.v1beta1.IExportModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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

.

Returns an empty response in the field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the model to export.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired output location and configuration.
   */
  // const outputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callExportModel();

exportModel(request, options, callback)

exportModel(request: protos.google.cloud.automl.v1beta1.IExportModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportModelRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

exportModel(request, callback)

exportModel(request: protos.google.cloud.automl.v1beta1.IExportModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IExportModelRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getAnnotationSpec(request, options)

getAnnotationSpec(request?: protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | undefined, {} | undefined]>;

Gets an annotation spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [AnnotationSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the annotation spec to retrieve.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callGetAnnotationSpec();

getAnnotationSpec(request, options, callback)

getAnnotationSpec(request: protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getAnnotationSpec(request, callback)

getAnnotationSpec(request: protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IAnnotationSpec, protos.google.cloud.automl.v1beta1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getColumnSpec(request, options)

getColumnSpec(request?: protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | undefined, {} | undefined]>;

Gets a column spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [ColumnSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the column spec to retrieve.
   */
  // const name = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const fieldMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.getColumnSpec(request);
    console.log(response);
  }

  callGetColumnSpec();

getColumnSpec(request, options, callback)

getColumnSpec(request: protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getColumnSpec(request, callback)

getColumnSpec(request: protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IGetColumnSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getDataset(request, options)

getDataset(request?: protos.google.cloud.automl.v1beta1.IGetDatasetRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | undefined, {} | undefined]>;

Gets a dataset.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetDatasetRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Dataset]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset to retrieve.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callGetDataset();

getDataset(request, options, callback)

getDataset(request: protos.google.cloud.automl.v1beta1.IGetDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetDatasetRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getDataset(request, callback)

getDataset(request: protos.google.cloud.automl.v1beta1.IGetDatasetRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetDatasetRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IGetDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getModel(request, options)

getModel(request?: protos.google.cloud.automl.v1beta1.IGetModelRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | undefined, {} | undefined]>;

Gets a model.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Model]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.getModel(request);
    console.log(response);
  }

  callGetModel();

getModel(request, options, callback)

getModel(request: protos.google.cloud.automl.v1beta1.IGetModelRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getModel(request, callback)

getModel(request: protos.google.cloud.automl.v1beta1.IGetModelRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IModel, protos.google.cloud.automl.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getModelEvaluation(request, options)

getModelEvaluation(request?: protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | undefined, {} | undefined]>;

Gets a model evaluation.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [ModelEvaluation]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name for the model evaluation.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.getModelEvaluation(request);
    console.log(response);
  }

  callGetModelEvaluation();

getModelEvaluation(request, options, callback)

getModelEvaluation(request: protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getModelEvaluation(request, callback)

getModelEvaluation(request: protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IModelEvaluation, protos.google.cloud.automl.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getProjectId()

getProjectId(): Promise<string>;

Returns

Type	Description
Promise<string>

getProjectId(callback)

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

Parameter

Name	Description
callback	Callback<string, undefined, undefined>

Returns

Type	Description
void

getTableSpec(request, options)

getTableSpec(request?: protos.google.cloud.automl.v1beta1.IGetTableSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | undefined, {} | undefined]>;

Gets a table spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetTableSpecRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TableSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the table spec to retrieve.
   */
  // const name = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const fieldMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.getTableSpec(request);
    console.log(response);
  }

  callGetTableSpec();

getTableSpec(request, options, callback)

getTableSpec(request: protos.google.cloud.automl.v1beta1.IGetTableSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetTableSpecRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

getTableSpec(request, callback)

getTableSpec(request: protos.google.cloud.automl.v1beta1.IGetTableSpecRequest, callback: Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IGetTableSpecRequest
callback	Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IGetTableSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

importData(request, options)

importData(request?: protos.google.cloud.automl.v1beta1.IImportDataRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Imports data into a dataset. For Tables this method can only be called on an empty Dataset.

For Tables: * A parameter must be explicitly set. Returns an empty response in the field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IImportDataRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Dataset name. Dataset must already exist. All imported
   *  annotations and examples will be added.
   */
  // const name = 'abc123'
  /**
   *  Required. The desired input location and its domain specific semantics,
   *  if any.
   */
  // const inputConfig = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callImportData();

importData(request, options, callback)

importData(request: protos.google.cloud.automl.v1beta1.IImportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IImportDataRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

importData(request, callback)

importData(request: protos.google.cloud.automl.v1beta1.IImportDataRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IImportDataRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

initialize()

initialize(): Promise<{
        [name: string]: Function;
    }>;

Initialize the client. Performs asynchronous operations (such as authentication) and prepares the client. This function will be called automatically when any class method is called for the first time, but if you need to initialize it before calling an actual method, feel free to call initialize() directly.

You can await on this method if you want to make sure the client is initialized.

Returns

Type	Description
Promise<{ [name: string]: Function; }>	{Promise} A promise that resolves to an authenticated service stub.

listColumnSpecs(request, options)

listColumnSpecs(request?: protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec[], protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest | null, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse]>;

Lists column specs in a table spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec[], protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest | null, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [ColumnSpec]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listColumnSpecsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listColumnSpecs(request, options, callback)

listColumnSpecs(request: protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IColumnSpec>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IColumnSpec>

Returns

Type	Description
void

listColumnSpecs(request, callback)

listColumnSpecs(request: protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IColumnSpec>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, protos.google.cloud.automl.v1beta1.IListColumnSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IColumnSpec>

Returns

Type	Description
void

listColumnSpecsAsync(request, options)

listColumnSpecsAsync(request?: protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1beta1.IColumnSpec>;

Equivalent to listColumnSpecs, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.automl.v1beta1.IColumnSpec>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [ColumnSpec]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the table spec to list column specs from.
   */
  // const parent = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const fieldMask = {}
  /**
   *  Filter expression, see go/filtering.
   */
  // const filter = 'abc123'
  /**
   *  Requested page size. The server can return fewer results than requested.
   *  If unspecified, the server will pick a default size.
   */
  // const pageSize = 1234
  /**
   *  A token identifying a page of results for the server to return.
   *  Typically obtained from the
   *  ListColumnSpecsResponse.next_page_token google.cloud.automl.v1beta1.ListColumnSpecsResponse.next_page_token  field of the previous
   *  AutoMl.ListColumnSpecs google.cloud.automl.v1beta1.AutoMl.ListColumnSpecs  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callListColumnSpecs();

listColumnSpecsStream(request, options)

listColumnSpecsStream(request?: protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListColumnSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [ColumnSpec] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listColumnSpecsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listDatasets(request, options)

listDatasets(request?: protos.google.cloud.automl.v1beta1.IListDatasetsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IDataset[], protos.google.cloud.automl.v1beta1.IListDatasetsRequest | null, protos.google.cloud.automl.v1beta1.IListDatasetsResponse]>;

Lists datasets in a project.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListDatasetsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[protos.google.cloud.automl.v1beta1.IDataset[], protos.google.cloud.automl.v1beta1.IListDatasetsRequest | null, protos.google.cloud.automl.v1beta1.IListDatasetsResponse]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Dataset]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listDatasetsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listDatasets(request, options, callback)

listDatasets(request: protos.google.cloud.automl.v1beta1.IListDatasetsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListDatasetsRequest, protos.google.cloud.automl.v1beta1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IDataset>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListDatasetsRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListDatasetsRequest, protos.google.cloud.automl.v1beta1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IDataset>

Returns

Type	Description
void

listDatasets(request, callback)

listDatasets(request: protos.google.cloud.automl.v1beta1.IListDatasetsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListDatasetsRequest, protos.google.cloud.automl.v1beta1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IDataset>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListDatasetsRequest
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListDatasetsRequest, protos.google.cloud.automl.v1beta1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IDataset>

Returns

Type	Description
void

listDatasetsAsync(request, options)

listDatasetsAsync(request?: protos.google.cloud.automl.v1beta1.IListDatasetsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1beta1.IDataset>;

Equivalent to listDatasets, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListDatasetsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.automl.v1beta1.IDataset>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Dataset]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the project from which to list datasets.
   */
  // const parent = 'abc123'
  /**
   *  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`.
   */
  // const filter = 'abc123'
  /**
   *  Requested page size. Server may return fewer results than requested.
   *  If unspecified, server will pick a default size.
   */
  // const pageSize = 1234
  /**
   *  A token identifying a page of results for the server to return
   *  Typically obtained via
   *  ListDatasetsResponse.next_page_token google.cloud.automl.v1beta1.ListDatasetsResponse.next_page_token  of the previous
   *  AutoMl.ListDatasets google.cloud.automl.v1beta1.AutoMl.ListDatasets  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callListDatasets();

listDatasetsStream(request, options)

listDatasetsStream(request?: protos.google.cloud.automl.v1beta1.IListDatasetsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListDatasetsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [Dataset] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listDatasetsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listModelEvaluations(request, options)

listModelEvaluations(request?: protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IModelEvaluation[], protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest | null, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse]>;

Lists model evaluations.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[protos.google.cloud.automl.v1beta1.IModelEvaluation[], protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest | null, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [ModelEvaluation]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listModelEvaluationsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listModelEvaluations(request, options, callback)

listModelEvaluations(request: protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModelEvaluation>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModelEvaluation>

Returns

Type	Description
void

listModelEvaluations(request, callback)

listModelEvaluations(request: protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModelEvaluation>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModelEvaluation>

Returns

Type	Description
void

listModelEvaluationsAsync(request, options)

listModelEvaluationsAsync(request?: protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1beta1.IModelEvaluation>;

Equivalent to listModelEvaluations, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.automl.v1beta1.IModelEvaluation>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [ModelEvaluation]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model to list the model evaluations for.
   *  If modelId is set as "-", this will list model evaluations from across all
   *  models of the parent location.
   */
  // const parent = 'abc123'
  /**
   *  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.
   */
  // const filter = 'abc123'
  /**
   *  Requested page size.
   */
  // const pageSize = 1234
  /**
   *  A token identifying a page of results for the server to return.
   *  Typically obtained via
   *  ListModelEvaluationsResponse.next_page_token google.cloud.automl.v1beta1.ListModelEvaluationsResponse.next_page_token  of the previous
   *  AutoMl.ListModelEvaluations google.cloud.automl.v1beta1.AutoMl.ListModelEvaluations  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callListModelEvaluations();

listModelEvaluationsStream(request, options)

listModelEvaluationsStream(request?: protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelEvaluationsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [ModelEvaluation] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listModelEvaluationsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listModels(request, options)

listModels(request?: protos.google.cloud.automl.v1beta1.IListModelsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IModel[], protos.google.cloud.automl.v1beta1.IListModelsRequest | null, protos.google.cloud.automl.v1beta1.IListModelsResponse]>;

Lists models.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[protos.google.cloud.automl.v1beta1.IModel[], protos.google.cloud.automl.v1beta1.IListModelsRequest | null, protos.google.cloud.automl.v1beta1.IListModelsResponse]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Model]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listModelsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listModels(request, options, callback)

listModels(request: protos.google.cloud.automl.v1beta1.IListModelsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelsRequest, protos.google.cloud.automl.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModel>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelsRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelsRequest, protos.google.cloud.automl.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModel>

Returns

Type	Description
void

listModels(request, callback)

listModels(request: protos.google.cloud.automl.v1beta1.IListModelsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelsRequest, protos.google.cloud.automl.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModel>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelsRequest
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListModelsRequest, protos.google.cloud.automl.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1beta1.IModel>

Returns

Type	Description
void

listModelsAsync(request, options)

listModelsAsync(request?: protos.google.cloud.automl.v1beta1.IListModelsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1beta1.IModel>;

Equivalent to listModels, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.automl.v1beta1.IModel>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Model]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the project, from which to list the models.
   */
  // const parent = 'abc123'
  /**
   *  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.
   */
  // const filter = 'abc123'
  /**
   *  Requested page size.
   */
  // const pageSize = 1234
  /**
   *  A token identifying a page of results for the server to return
   *  Typically obtained via
   *  ListModelsResponse.next_page_token google.cloud.automl.v1beta1.ListModelsResponse.next_page_token  of the previous
   *  AutoMl.ListModels google.cloud.automl.v1beta1.AutoMl.ListModels  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callListModels();

listModelsStream(request, options)

listModelsStream(request?: protos.google.cloud.automl.v1beta1.IListModelsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListModelsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [Model] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listModelsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTableSpecs(request, options)

listTableSpecs(request?: protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.ITableSpec[], protos.google.cloud.automl.v1beta1.IListTableSpecsRequest | null, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse]>;

Lists table specs in a dataset.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListTableSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Promise<[protos.google.cloud.automl.v1beta1.ITableSpec[], protos.google.cloud.automl.v1beta1.IListTableSpecsRequest | null, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [TableSpec]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using listTableSpecsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

listTableSpecs(request, options, callback)

listTableSpecs(request: protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.ITableSpec>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListTableSpecsRequest
options	CallOptions
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.ITableSpec>

Returns

Type	Description
void

listTableSpecs(request, callback)

listTableSpecs(request: protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.ITableSpec>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListTableSpecsRequest
callback	PaginationCallback<protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, protos.google.cloud.automl.v1beta1.IListTableSpecsResponse | null | undefined, protos.google.cloud.automl.v1beta1.ITableSpec>

Returns

Type	Description
void

listTableSpecsAsync(request, options)

listTableSpecsAsync(request?: protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1beta1.ITableSpec>;

Equivalent to listTableSpecs, but returns an iterable object.

for-await-of syntax is used with the iterable to get response elements on-demand.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListTableSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

AsyncIterable<protos.google.cloud.automl.v1beta1.ITableSpec>

{Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [TableSpec]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The resource name of the dataset to list table specs from.
   */
  // const parent = 'abc123'
  /**
   *  Mask specifying which fields to read.
   */
  // const fieldMask = {}
  /**
   *  Filter expression, see go/filtering.
   */
  // const filter = 'abc123'
  /**
   *  Requested page size. The server can return fewer results than requested.
   *  If unspecified, the server will pick a default size.
   */
  // const pageSize = 1234
  /**
   *  A token identifying a page of results for the server to return.
   *  Typically obtained from the
   *  ListTableSpecsResponse.next_page_token google.cloud.automl.v1beta1.ListTableSpecsResponse.next_page_token  field of the previous
   *  AutoMl.ListTableSpecs google.cloud.automl.v1beta1.AutoMl.ListTableSpecs  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callListTableSpecs();

listTableSpecsStream(request, options)

listTableSpecsStream(request?: protos.google.cloud.automl.v1beta1.IListTableSpecsRequest, options?: CallOptions): Transform;

Equivalent to method.name.toCamelCase(), but returns a NodeJS Stream object.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IListTableSpecsRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type

Description

Transform

{Stream} An object stream which emits an object representing [TableSpec] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using listTableSpecsAsync() method described below for async iteration which you can stop as needed. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples.

locationPath(project, location)

locationPath(project: string, location: string): string;

Return a fully-qualified location resource name string.

Parameters

Name	Description
project	string
location	string

Returns

Type	Description
string	{string} Resource name string.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the annotation_spec.

matchColumnSpecFromColumnSpecName(columnSpecName)

matchColumnSpecFromColumnSpecName(columnSpecName: string): string | number;

Parse the column_spec from ColumnSpec resource.

Parameter

Name	Description
columnSpecName	string A fully-qualified path representing ColumnSpec resource.

Returns

Type	Description
string | number	{string} A string representing the column_spec.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromColumnSpecName(columnSpecName)

matchDatasetFromColumnSpecName(columnSpecName: string): string | number;

Parse the dataset from ColumnSpec resource.

Parameter

Name	Description
columnSpecName	string A fully-qualified path representing ColumnSpec resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchDatasetFromTableSpecName(tableSpecName)

matchDatasetFromTableSpecName(tableSpecName: string): string | number;

Parse the dataset from TableSpec resource.

Parameter

Name	Description
tableSpecName	string A fully-qualified path representing TableSpec resource.

Returns

Type	Description
string | number	{string} A string representing the dataset.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromColumnSpecName(columnSpecName)

matchLocationFromColumnSpecName(columnSpecName: string): string | number;

Parse the location from ColumnSpec resource.

Parameter

Name	Description
columnSpecName	string A fully-qualified path representing ColumnSpec resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter

Name	Description
locationName	string A fully-qualified path representing Location resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchLocationFromTableSpecName(tableSpecName)

matchLocationFromTableSpecName(tableSpecName: string): string | number;

Parse the location from TableSpec resource.

Parameter

Name	Description
tableSpecName	string A fully-qualified path representing TableSpec resource.

Returns

Type	Description
string | number	{string} A string representing the location.

matchModelEvaluationFromModelEvaluationName(modelEvaluationName)

matchModelEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model_evaluation from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the model_evaluation.

matchModelFromModelEvaluationName(modelEvaluationName)

matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the model.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter

Name	Description
annotationSpecName	string A fully-qualified path representing AnnotationSpec resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromColumnSpecName(columnSpecName)

matchProjectFromColumnSpecName(columnSpecName: string): string | number;

Parse the project from ColumnSpec resource.

Parameter

Name	Description
columnSpecName	string A fully-qualified path representing ColumnSpec resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter

Name	Description
datasetName	string A fully-qualified path representing Dataset resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter

Name	Description
locationName	string A fully-qualified path representing Location resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter

Name	Description
modelEvaluationName	string A fully-qualified path representing ModelEvaluation resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter

Name	Description
modelName	string A fully-qualified path representing Model resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchProjectFromTableSpecName(tableSpecName)

matchProjectFromTableSpecName(tableSpecName: string): string | number;

Parse the project from TableSpec resource.

Parameter

Name	Description
tableSpecName	string A fully-qualified path representing TableSpec resource.

Returns

Type	Description
string | number	{string} A string representing the project.

matchTableSpecFromColumnSpecName(columnSpecName)

matchTableSpecFromColumnSpecName(columnSpecName: string): string | number;

Parse the table_spec from ColumnSpec resource.

Parameter

Name	Description
columnSpecName	string A fully-qualified path representing ColumnSpec resource.

Returns

Type	Description
string | number	{string} A string representing the table_spec.

matchTableSpecFromTableSpecName(tableSpecName)

matchTableSpecFromTableSpecName(tableSpecName: string): string | number;

Parse the table_spec from TableSpec resource.

Parameter

Name	Description
tableSpecName	string A fully-qualified path representing TableSpec resource.

Returns

Type	Description
string | number	{string} A string representing the table_spec.

modelEvaluationPath(project, location, model, modelEvaluation)

modelEvaluationPath(project: string, location: string, model: string, modelEvaluation: string): string;

Return a fully-qualified modelEvaluation resource name string.

Parameters

Name	Description
project	string
location	string
model	string
modelEvaluation	string

Returns

Type	Description
string	{string} Resource name string.

modelPath(project, location, model)

modelPath(project: string, location: string, model: string): string;

Return a fully-qualified model resource name string.

Parameters

Name	Description
project	string
location	string
model	string

Returns

Type	Description
string	{string} Resource name string.

tableSpecPath(project, location, dataset, tableSpec)

tableSpecPath(project: string, location: string, dataset: string, tableSpec: string): string;

Return a fully-qualified tableSpec resource name string.

Parameters

Name	Description
project	string
location	string
dataset	string
tableSpec	string

Returns

Type	Description
string	{string} Resource name string.

undeployModel(request, options)

undeployModel(request?: protos.google.cloud.automl.v1beta1.IUndeployModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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 field when it completes.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUndeployModelRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its promise() method returns a promise you can await for. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. Resource name of the model to undeploy.
   */
  // const name = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

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

  callUndeployModel();

undeployModel(request, options, callback)

undeployModel(request: protos.google.cloud.automl.v1beta1.IUndeployModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUndeployModelRequest
options	CallOptions
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

undeployModel(request, callback)

undeployModel(request: protos.google.cloud.automl.v1beta1.IUndeployModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUndeployModelRequest
callback	Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1beta1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateColumnSpec(request, options)

updateColumnSpec(request?: protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | undefined, {} | undefined]>;

Updates a column spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [ColumnSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The column spec which replaces the resource on the server.
   */
  // const columnSpec = {}
  /**
   *  The update mask applies to the resource.
   */
  // const updateMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

  async function callUpdateColumnSpec() {
    // Construct request
    const request = {
      columnSpec,
    };

    // Run request
    const response = await automlClient.updateColumnSpec(request);
    console.log(response);
  }

  callUpdateColumnSpec();

updateColumnSpec(request, options, callback)

updateColumnSpec(request: protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateColumnSpec(request, callback)

updateColumnSpec(request: protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IColumnSpec, protos.google.cloud.automl.v1beta1.IUpdateColumnSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateDataset(request, options)

updateDataset(request?: protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | undefined, {} | undefined]>;

Updates a dataset.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Dataset]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The dataset which replaces the resource on the server.
   */
  // const dataset = {}
  /**
   *  The update mask applies to the resource.
   */
  // const updateMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

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

    // Run request
    const response = await automlClient.updateDataset(request);
    console.log(response);
  }

  callUpdateDataset();

updateDataset(request, options, callback)

updateDataset(request: protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateDataset(request, callback)

updateDataset(request: protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest, callback: Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest
callback	Callback<protos.google.cloud.automl.v1beta1.IDataset, protos.google.cloud.automl.v1beta1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateTableSpec(request, options)

updateTableSpec(request?: protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | undefined, {} | undefined]>;

Updates a table spec.

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest The request object that will be sent.
options	CallOptions Call options. See CallOptions for more details.

Returns

Type	Description
Promise<[protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | undefined, {} | undefined]>	{Promise} - The promise which resolves to an array. The first element of the array is an object representing [TableSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples.

Example

  /**
   * TODO(developer): Uncomment these variables before running the sample.
   */
  /**
   *  Required. The table spec which replaces the resource on the server.
   */
  // const tableSpec = {}
  /**
   *  The update mask applies to the resource.
   */
  // const updateMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1beta1;

  // Instantiates a client
  const automlClient = new AutoMlClient();

  async function callUpdateTableSpec() {
    // Construct request
    const request = {
      tableSpec,
    };

    // Run request
    const response = await automlClient.updateTableSpec(request);
    console.log(response);
  }

  callUpdateTableSpec();

updateTableSpec(request, options, callback)

updateTableSpec(request: protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest
options	CallOptions
callback	Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void

updateTableSpec(request, callback)

updateTableSpec(request: protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest, callback: Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | null | undefined, {} | null | undefined>): void;

Parameters

Name	Description
request	protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest
callback	Callback<protos.google.cloud.automl.v1beta1.ITableSpec, protos.google.cloud.automl.v1beta1.IUpdateTableSpecRequest | null | undefined, {} | null | undefined>

Returns

Type	Description
void