Class v1.AutoMlClient

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. v1

Package

@google-cloud/automl

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Construct an instance of AutoMlClient.

Parameter
NameDescription
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
NameDescription
project string
location string
dataset string
annotationSpec string
Returns
TypeDescription
string

{string} Resource name string.

checkCreateDatasetProgress(name)

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

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.automl.v1.Dataset, protos.google.cloud.automl.v1.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 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').v1;

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

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

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

  callCreateDataset();

checkCreateModelProgress(name)

checkCreateModelProgress(name: string): Promise<LROperation<protos.google.cloud.automl.v1.Model, protos.google.cloud.automl.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.automl.v1.Model, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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();

checkExportModelProgress(name)

checkExportModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.OperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.automl.v1.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').v1;

  // 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
TypeDescription
Promise<void>

{Promise} A promise that resolves when the client is closed.

createDataset(request, options)

createDataset(request?: protos.google.cloud.automl.v1.ICreateDatasetRequest, options?: CallOptions): Promise<[LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

Creates a dataset.

Parameters
NameDescription
request protos.google.cloud.automl.v1.ICreateDatasetRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.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 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').v1;

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

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

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

  callCreateDataset();

createDataset(request, options, callback)

createDataset(request: protos.google.cloud.automl.v1.ICreateDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.ICreateDatasetRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createDataset(request, callback)

createDataset(request: protos.google.cloud.automl.v1.ICreateDatasetRequest, callback: Callback<LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.ICreateDatasetRequest
callback Callback<LROperation<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createModel(request, options)

createModel(request?: protos.google.cloud.automl.v1.ICreateModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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
NameDescription
request protos.google.cloud.automl.v1.ICreateModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.ICreateModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.ICreateModelRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createModel(request, callback)

createModel(request: protos.google.cloud.automl.v1.ICreateModelRequest, callback: Callback<LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.ICreateModelRequest
callback Callback<LROperation<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

datasetPath(project, location, dataset)

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

Return a fully-qualified dataset resource name string.

Parameters
NameDescription
project string
location string
dataset string
Returns
TypeDescription
string

{string} Resource name string.

deleteDataset(request, options)

deleteDataset(request?: protos.google.cloud.automl.v1.IDeleteDatasetRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteDatasetRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IDeleteDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteDatasetRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteDataset(request, callback)

deleteDataset(request: protos.google.cloud.automl.v1.IDeleteDatasetRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteDatasetRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteModel(request, options)

deleteModel(request?: protos.google.cloud.automl.v1.IDeleteModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IDeleteModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteModelRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteModel(request, callback)

deleteModel(request: protos.google.cloud.automl.v1.IDeleteModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeleteModelRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deployModel(request, options)

deployModel(request?: protos.google.cloud.automl.v1.IDeployModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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
NameDescription
request protos.google.cloud.automl.v1.IDeployModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IDeployModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeployModelRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deployModel(request, callback)

deployModel(request: protos.google.cloud.automl.v1.IDeployModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IDeployModelRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

exportData(request, options)

exportData(request?: protos.google.cloud.automl.v1.IExportDataRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IExportDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IExportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IExportDataRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

exportData(request, callback)

exportData(request: protos.google.cloud.automl.v1.IExportDataRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IExportDataRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

exportModel(request, options)

exportModel(request?: protos.google.cloud.automl.v1.IExportModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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
NameDescription
request protos.google.cloud.automl.v1.IExportModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IExportModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IExportModelRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

exportModel(request, callback)

exportModel(request: protos.google.cloud.automl.v1.IExportModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IExportModelRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getAnnotationSpec(request, options)

getAnnotationSpec(request?: protos.google.cloud.automl.v1.IGetAnnotationSpecRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IAnnotationSpec, protos.google.cloud.automl.v1.IGetAnnotationSpecRequest | undefined, {} | undefined]>;

Gets an annotation spec.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetAnnotationSpecRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IAnnotationSpec, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IGetAnnotationSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IAnnotationSpec, protos.google.cloud.automl.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetAnnotationSpecRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IAnnotationSpec, protos.google.cloud.automl.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getAnnotationSpec(request, callback)

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

getDataset(request, options)

getDataset(request?: protos.google.cloud.automl.v1.IGetDatasetRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IGetDatasetRequest | undefined, {} | undefined]>;

Gets a dataset.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetDatasetRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IGetDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetDatasetRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getDataset(request, callback)

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

getModel(request, options)

getModel(request?: protos.google.cloud.automl.v1.IGetModelRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IGetModelRequest | undefined, {} | undefined]>;

Gets a model.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IGetModelRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IGetModelRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IGetModelRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getModel(request, callback)

getModel(request: protos.google.cloud.automl.v1.IGetModelRequest, callback: Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IGetModelRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelRequest
callback Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IGetModelRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getModelEvaluation(request, options)

getModelEvaluation(request?: protos.google.cloud.automl.v1.IGetModelEvaluationRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.IGetModelEvaluationRequest | undefined, {} | undefined]>;

Gets a model evaluation.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelEvaluationRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IGetModelEvaluationRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelEvaluationRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getModelEvaluation(request, callback)

getModelEvaluation(request: protos.google.cloud.automl.v1.IGetModelEvaluationRequest, callback: Callback<protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IGetModelEvaluationRequest
callback Callback<protos.google.cloud.automl.v1.IModelEvaluation, protos.google.cloud.automl.v1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getProjectId()

getProjectId(): Promise<string>;
Returns
TypeDescription
Promise<string>

getProjectId(callback)

getProjectId(callback: Callback<string, undefined, undefined>): void;
Parameter
NameDescription
callback Callback<string, undefined, undefined>
Returns
TypeDescription
void

importData(request, options)

importData(request?: protos.google.cloud.automl.v1.IImportDataRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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
NameDescription
request protos.google.cloud.automl.v1.IImportDataRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IImportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IImportDataRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

importData(request, callback)

importData(request: protos.google.cloud.automl.v1.IImportDataRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IImportDataRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
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
TypeDescription
Promise<{ [name: string]: Function; }>

{Promise} A promise that resolves to an authenticated service stub.

listDatasets(request, options)

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

Lists datasets in a project.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListDatasetsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IDataset[], protos.google.cloud.automl.v1.IListDatasetsRequest | null, protos.google.cloud.automl.v1.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.v1.IListDatasetsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1.IListDatasetsRequest, protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1.IDataset>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListDatasetsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.automl.v1.IListDatasetsRequest, protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1.IDataset>
Returns
TypeDescription
void

listDatasets(request, callback)

listDatasets(request: protos.google.cloud.automl.v1.IListDatasetsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1.IListDatasetsRequest, protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1.IDataset>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListDatasetsRequest
callback PaginationCallback<protos.google.cloud.automl.v1.IListDatasetsRequest, protos.google.cloud.automl.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.automl.v1.IDataset>
Returns
TypeDescription
void

listDatasetsAsync(request, options)

listDatasetsAsync(request?: protos.google.cloud.automl.v1.IListDatasetsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1.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
NameDescription
request protos.google.cloud.automl.v1.IListDatasetsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.automl.v1.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.v1.ListDatasetsResponse.next_page_token  of the previous
   *  AutoMl.ListDatasets google.cloud.automl.v1.AutoMl.ListDatasets  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1;

  // 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.v1.IListDatasetsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListDatasetsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.v1.IListModelEvaluationsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IModelEvaluation[], protos.google.cloud.automl.v1.IListModelEvaluationsRequest | null, protos.google.cloud.automl.v1.IListModelEvaluationsResponse]>;

Lists model evaluations.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelEvaluationsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IModelEvaluation[], protos.google.cloud.automl.v1.IListModelEvaluationsRequest | null, protos.google.cloud.automl.v1.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.v1.IListModelEvaluationsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1.IModelEvaluation>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelEvaluationsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.automl.v1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1.IModelEvaluation>
Returns
TypeDescription
void

listModelEvaluations(request, callback)

listModelEvaluations(request: protos.google.cloud.automl.v1.IListModelEvaluationsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1.IModelEvaluation>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelEvaluationsRequest
callback PaginationCallback<protos.google.cloud.automl.v1.IListModelEvaluationsRequest, protos.google.cloud.automl.v1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.automl.v1.IModelEvaluation>
Returns
TypeDescription
void

listModelEvaluationsAsync(request, options)

listModelEvaluationsAsync(request?: protos.google.cloud.automl.v1.IListModelEvaluationsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1.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
NameDescription
request protos.google.cloud.automl.v1.IListModelEvaluationsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.automl.v1.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'
  /**
   *  Required. An expression for filtering the results of the request.
   *    * `annotation_spec_id` - for =, !=  or existence. See example below for
   *                           the last.
   *  Some examples of using the filter are:
   *    * `annotation_spec_id!=4` --> The model evaluation was done for
   *                              annotation spec with ID different than 4.
   *    * `NOT annotation_spec_id:*` --> The model evaluation was done for
   *                                 aggregate of all annotation specs.
   */
  // 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.v1.ListModelEvaluationsResponse.next_page_token  of the previous
   *  AutoMl.ListModelEvaluations google.cloud.automl.v1.AutoMl.ListModelEvaluations  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1;

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

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

    // 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.v1.IListModelEvaluationsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelEvaluationsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.v1.IListModelsRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IModel[], protos.google.cloud.automl.v1.IListModelsRequest | null, protos.google.cloud.automl.v1.IListModelsResponse]>;

Lists models.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IModel[], protos.google.cloud.automl.v1.IListModelsRequest | null, protos.google.cloud.automl.v1.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.v1.IListModelsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.automl.v1.IListModelsRequest, protos.google.cloud.automl.v1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1.IModel>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.automl.v1.IListModelsRequest, protos.google.cloud.automl.v1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1.IModel>
Returns
TypeDescription
void

listModels(request, callback)

listModels(request: protos.google.cloud.automl.v1.IListModelsRequest, callback: PaginationCallback<protos.google.cloud.automl.v1.IListModelsRequest, protos.google.cloud.automl.v1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1.IModel>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelsRequest
callback PaginationCallback<protos.google.cloud.automl.v1.IListModelsRequest, protos.google.cloud.automl.v1.IListModelsResponse | null | undefined, protos.google.cloud.automl.v1.IModel>
Returns
TypeDescription
void

listModelsAsync(request, options)

listModelsAsync(request?: protos.google.cloud.automl.v1.IListModelsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.automl.v1.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
NameDescription
request protos.google.cloud.automl.v1.IListModelsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.automl.v1.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.v1.ListModelsResponse.next_page_token  of the previous
   *  AutoMl.ListModels google.cloud.automl.v1.AutoMl.ListModels  call.
   */
  // const pageToken = 'abc123'

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1;

  // 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.v1.IListModelsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.automl.v1.IListModelsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
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.

locationPath(project, location)

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

Return a fully-qualified location resource name string.

Parameters
NameDescription
project string
location string
Returns
TypeDescription
string

{string} Resource name string.

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)

matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the annotation_spec from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation_spec.

matchDatasetFromAnnotationSpecName(annotationSpecName)

matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the dataset from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchDatasetFromDatasetName(datasetName)

matchDatasetFromDatasetName(datasetName: string): string | number;

Parse the dataset from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

matchLocationFromAnnotationSpecName(annotationSpecName)

matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the location from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDatasetName(datasetName)

matchLocationFromDatasetName(datasetName: string): string | number;

Parse the location from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromLocationName(locationName)

matchLocationFromLocationName(locationName: string): string | number;

Parse the location from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelEvaluationName(modelEvaluationName)

matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the location from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelName(modelName)

matchLocationFromModelName(modelName: string): string | number;

Parse the location from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchModelEvaluationFromModelEvaluationName(modelEvaluationName)

matchModelEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model_evaluation from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the model_evaluation.

matchModelFromModelEvaluationName(modelEvaluationName)

matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the model from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchModelFromModelName(modelName)

matchModelFromModelName(modelName: string): string | number;

Parse the model from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the model.

matchProjectFromAnnotationSpecName(annotationSpecName)

matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;

Parse the project from AnnotationSpec resource.

Parameter
NameDescription
annotationSpecName string

A fully-qualified path representing AnnotationSpec resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDatasetName(datasetName)

matchProjectFromDatasetName(datasetName: string): string | number;

Parse the project from Dataset resource.

Parameter
NameDescription
datasetName string

A fully-qualified path representing Dataset resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromLocationName(locationName)

matchProjectFromLocationName(locationName: string): string | number;

Parse the project from Location resource.

Parameter
NameDescription
locationName string

A fully-qualified path representing Location resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelEvaluationName(modelEvaluationName)

matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the project from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelName(modelName)

matchProjectFromModelName(modelName: string): string | number;

Parse the project from Model resource.

Parameter
NameDescription
modelName string

A fully-qualified path representing Model resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

modelEvaluationPath(project, location, model, modelEvaluation)

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

Return a fully-qualified modelEvaluation resource name string.

Parameters
NameDescription
project string
location string
model string
modelEvaluation string
Returns
TypeDescription
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
NameDescription
project string
location string
model string
Returns
TypeDescription
string

{string} Resource name string.

undeployModel(request, options)

undeployModel(request?: protos.google.cloud.automl.v1.IUndeployModelRequest, options?: CallOptions): Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined]>;

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
NameDescription
request protos.google.cloud.automl.v1.IUndeployModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.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').v1;

  // 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.v1.IUndeployModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUndeployModelRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

undeployModel(request, callback)

undeployModel(request: protos.google.cloud.automl.v1.IUndeployModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUndeployModelRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.automl.v1.IOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateDataset(request, options)

updateDataset(request?: protos.google.cloud.automl.v1.IUpdateDatasetRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IUpdateDatasetRequest | undefined, {} | undefined]>;

Updates a dataset.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateDatasetRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.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 = {}
  /**
   *  Required. The update mask applies to the resource.
   */
  // const updateMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1;

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

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

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

  callUpdateDataset();

updateDataset(request, options, callback)

updateDataset(request: protos.google.cloud.automl.v1.IUpdateDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateDatasetRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateDataset(request, callback)

updateDataset(request: protos.google.cloud.automl.v1.IUpdateDatasetRequest, callback: Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateDatasetRequest
callback Callback<protos.google.cloud.automl.v1.IDataset, protos.google.cloud.automl.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateModel(request, options)

updateModel(request?: protos.google.cloud.automl.v1.IUpdateModelRequest, options?: CallOptions): Promise<[protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | undefined, {} | undefined]>;

Updates a model.

Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateModelRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | 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. The model which replaces the resource on the server.
   */
  // const model = {}
  /**
   *  Required. The update mask applies to the resource.
   */
  // const updateMask = {}

  // Imports the Automl library
  const {AutoMlClient} = require('@google-cloud/automl').v1;

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

  async function callUpdateModel() {
    // Construct request
    const request = {
      model,
      updateMask,
    };

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

  callUpdateModel();

updateModel(request, options, callback)

updateModel(request: protos.google.cloud.automl.v1.IUpdateModelRequest, options: CallOptions, callback: Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateModelRequest
options CallOptions
callback Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateModel(request, callback)

updateModel(request: protos.google.cloud.automl.v1.IUpdateModelRequest, callback: Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.automl.v1.IUpdateModelRequest
callback Callback<protos.google.cloud.automl.v1.IModel, protos.google.cloud.automl.v1.IUpdateModelRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void