Class v1.MetadataServiceClient (1.16.0)

Service for reading and writing metadata entries. v1

Package

@google-cloud/aiplatform

Constructors

(constructor)(opts)

constructor(opts?: ClientOptions);

Construct an instance of MetadataServiceClient.

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;

descriptors

descriptors: Descriptors;

innerApiCalls

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

metadataServiceStub

metadataServiceStub?: Promise<{
        [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

addContextArtifactsAndExecutions(request, options)

addContextArtifactsAndExecutions(request?: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse,
        (protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | undefined),
        {} | undefined
    ]>;

Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, (protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddContextArtifactsAndExecutionsResponse]. 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 Context that the Artifacts and Executions
   *  belong to.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const context = 'abc123'
  /**
   *  The resource names of the Artifacts to attribute to the Context.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   */
  // const artifacts = 'abc123'
  /**
   *  The resource names of the Executions to associate with the
   *  Context.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const executions = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callAddContextArtifactsAndExecutions() {
    // Construct request
    const request = {
      context,
    };

    // Run request
    const response = await aiplatformClient.addContextArtifactsAndExecutions(request);
    console.log(response);
  }

  callAddContextArtifactsAndExecutions();

addContextArtifactsAndExecutions(request, options, callback)

addContextArtifactsAndExecutions(request: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

addContextArtifactsAndExecutions(request, callback)

addContextArtifactsAndExecutions(request: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest
callback Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

addContextChildren(request, options)

addContextChildren(request?: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse,
        protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | undefined,
        {} | undefined
    ]>;

Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddContextChildrenResponse]. 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 parent Context.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const context = 'abc123'
  /**
   *  The resource names of the child Contexts.
   */
  // const childContexts = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callAddContextChildren() {
    // Construct request
    const request = {
      context,
    };

    // Run request
    const response = await aiplatformClient.addContextChildren(request);
    console.log(response);
  }

  callAddContextChildren();

addContextChildren(request, options, callback)

addContextChildren(request: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

addContextChildren(request, callback)

addContextChildren(request: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest
callback Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

addExecutionEvents(request, options)

addExecutionEvents(request?: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse,
        protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | undefined,
        {} | undefined
    ]>;

Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddExecutionEventsResponse]. 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 Execution that the Events connect
   *  Artifacts with.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const execution = 'abc123'
  /**
   *  The Events to create and add.
   */
  // const events = 1234

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callAddExecutionEvents() {
    // Construct request
    const request = {
      execution,
    };

    // Run request
    const response = await aiplatformClient.addExecutionEvents(request);
    console.log(response);
  }

  callAddExecutionEvents();

addExecutionEvents(request, options, callback)

addExecutionEvents(request: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

addExecutionEvents(request, callback)

addExecutionEvents(request: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest
callback Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

annotationPath(project, location, dataset, dataItem, annotation)

annotationPath(project: string, location: string, dataset: string, dataItem: string, annotation: string): string;

Return a fully-qualified annotation resource name string.

Parameters
NameDescription
project string
location string
dataset string
dataItem string
annotation string
Returns
TypeDescription
string

{string} Resource name string.

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.

artifactPath(project, location, metadataStore, artifact)

artifactPath(project: string, location: string, metadataStore: string, artifact: string): string;

Return a fully-qualified artifact resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
artifact string
Returns
TypeDescription
string

{string} Resource name string.

batchPredictionJobPath(project, location, batchPredictionJob)

batchPredictionJobPath(project: string, location: string, batchPredictionJob: string): string;

Return a fully-qualified batchPredictionJob resource name string.

Parameters
NameDescription
project string
location string
batchPredictionJob string
Returns
TypeDescription
string

{string} Resource name string.

checkCreateMetadataStoreProgress(name)

checkCreateMetadataStoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.MetadataStore, protos.google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1.MetadataStore, protos.google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata>>

{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 Location where the MetadataStore should
   *  be created.
   *  Format: `projects/{project}/locations/{location}/`
   */
  // const parent = 'abc123'
  /**
   *  Required. The MetadataStore to create.
   */
  // const metadataStore = {}
  /**
   *  The {metadatastore} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   *  If not provided, the MetadataStore's ID will be a UUID generated by the
   *  service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all MetadataStores in the parent Location.
   *  (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
   *  if the caller can't view the preexisting MetadataStore.)
   */
  // const metadataStoreId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callCreateMetadataStore();

checkDeleteArtifactProgress(name)

checkDeleteArtifactProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>

{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 Artifact to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   */
  // const name = 'abc123'
  /**
   *  Optional. The etag of the Artifact to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteArtifact();

checkDeleteContextProgress(name)

checkDeleteContextProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>

{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 Context to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const name = 'abc123'
  /**
   *  The force deletion semantics is still undefined.
   *  Users should not use this field.
   */
  // const force = true
  /**
   *  Optional. The etag of the Context to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteContext();

checkDeleteExecutionProgress(name)

checkDeleteExecutionProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>

{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 Execution to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const name = 'abc123'
  /**
   *  Optional. The etag of the Execution to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteExecution();

checkDeleteMetadataStoreProgress(name)

checkDeleteMetadataStoreProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata>>

{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 MetadataStore to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteMetadataStore();

checkPurgeArtifactsProgress(name)

checkPurgeArtifactsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.PurgeArtifactsMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.PurgeArtifactsMetadata>>

{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 metadata store to purge Artifacts from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Artifacts to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" artifact="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeartifacts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeartifacts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeartifacts();="">

checkPurgeContextsProgress(name)

checkPurgeContextsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeContextsResponse, protos.google.cloud.aiplatform.v1.PurgeContextsMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeContextsResponse, protos.google.cloud.aiplatform.v1.PurgeContextsMetadata>>

{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 metadata store to purge Contexts from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Contexts to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" context="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgecontexts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgecontexts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgecontexts();="">

checkPurgeExecutionsProgress(name)

checkPurgeExecutionsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.PurgeExecutionsMetadata>>;

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

Parameter
NameDescription
name string

The operation name that will be passed.

Returns
TypeDescription
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.PurgeExecutionsMetadata>>

{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 metadata store to purge Executions from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Executions to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" execution="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeexecutions()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeexecutions(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeexecutions();="">

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.

contextPath(project, location, metadataStore, context)

contextPath(project: string, location: string, metadataStore: string, context: string): string;

Return a fully-qualified context resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
context string
Returns
TypeDescription
string

{string} Resource name string.

createArtifact(request, options)

createArtifact(request?: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IArtifact,
        protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | undefined,
        {} | undefined
    ]>;

Creates an Artifact associated with a MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateArtifactRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. 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 MetadataStore where the Artifact should
   *  be created.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Artifact to create.
   */
  // const artifact = {}
  /**
   *  The {artifact} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   *  If not provided, the Artifact's ID will be a UUID generated by the service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all Artifacts in the parent MetadataStore. (Otherwise
   *  the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the
   *  caller can't view the preexisting Artifact.)
   */
  // const artifactId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.createArtifact(request);
    console.log(response);
  }

  callCreateArtifact();

createArtifact(request, options, callback)

createArtifact(request: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateArtifactRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createArtifact(request, callback)

createArtifact(request: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateArtifactRequest
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createContext(request, options)

createContext(request?: protos.google.cloud.aiplatform.v1.ICreateContextRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IContext,
        protos.google.cloud.aiplatform.v1.ICreateContextRequest | undefined,
        {} | undefined
    ]>;

Creates a Context associated with a MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateContextRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. 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 MetadataStore where the Context should be
   *  created.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Context to create.
   */
  // const context = {}
  /**
   *  The {context} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`.
   *  If not provided, the Context's ID will be a UUID generated by the service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all Contexts in the parent MetadataStore. (Otherwise
   *  the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the
   *  caller can't view the preexisting Context.)
   */
  // const contextId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.createContext(request);
    console.log(response);
  }

  callCreateContext();

createContext(request, options, callback)

createContext(request: protos.google.cloud.aiplatform.v1.ICreateContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateContextRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createContext(request, callback)

createContext(request: protos.google.cloud.aiplatform.v1.ICreateContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateContextRequest
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createExecution(request, options)

createExecution(request?: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IExecution,
        protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | undefined,
        {} | undefined
    ]>;

Creates an Execution associated with a MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateExecutionRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. 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 MetadataStore where the Execution should
   *  be created.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The Execution to create.
   */
  // const execution = {}
  /**
   *  The {execution} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   *  If not provided, the Execution's ID will be a UUID generated by the
   *  service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all Executions in the parent MetadataStore.
   *  (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
   *  if the caller can't view the preexisting Execution.)
   */
  // const executionId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.createExecution(request);
    console.log(response);
  }

  callCreateExecution();

createExecution(request, options, callback)

createExecution(request: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateExecutionRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createExecution(request, callback)

createExecution(request: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateExecutionRequest
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createMetadataSchema(request, options)

createMetadataSchema(request?: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IMetadataSchema,
        (protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | undefined),
        {} | undefined
    ]>;

Creates a MetadataSchema.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema, (protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataSchema]. 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 MetadataStore where the MetadataSchema should
   *  be created.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. The MetadataSchema to create.
   */
  // const metadataSchema = {}
  /**
   *  The {metadata_schema} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`
   *  If not provided, the MetadataStore's ID will be a UUID generated by the
   *  service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all MetadataSchemas in the parent Location.
   *  (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
   *  if the caller can't view the preexisting MetadataSchema.)
   */
  // const metadataSchemaId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.createMetadataSchema(request);
    console.log(response);
  }

  callCreateMetadataSchema();

createMetadataSchema(request, options, callback)

createMetadataSchema(request: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createMetadataSchema(request, callback)

createMetadataSchema(request: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createMetadataStore(request, options)

createMetadataStore(request?: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Initializes a MetadataStore, including allocation of resources.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, 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 Location where the MetadataStore should
   *  be created.
   *  Format: `projects/{project}/locations/{location}/`
   */
  // const parent = 'abc123'
  /**
   *  Required. The MetadataStore to create.
   */
  // const metadataStore = {}
  /**
   *  The {metadatastore} portion of the resource name with the format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   *  If not provided, the MetadataStore's ID will be a UUID generated by the
   *  service.
   *  Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
   *  Must be unique across all MetadataStores in the parent Location.
   *  (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
   *  if the caller can't view the preexisting MetadataStore.)
   */
  // const metadataStoreId = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callCreateMetadataStore();

createMetadataStore(request, options, callback)

createMetadataStore(request: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

createMetadataStore(request, callback)

createMetadataStore(request: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

customJobPath(project, location, customJob)

customJobPath(project: string, location: string, customJob: string): string;

Return a fully-qualified customJob resource name string.

Parameters
NameDescription
project string
location string
customJob string
Returns
TypeDescription
string

{string} Resource name string.

dataItemPath(project, location, dataset, dataItem)

dataItemPath(project: string, location: string, dataset: string, dataItem: string): string;

Return a fully-qualified dataItem resource name string.

Parameters
NameDescription
project string
location string
dataset string
dataItem string
Returns
TypeDescription
string

{string} Resource name string.

dataLabelingJobPath(project, location, dataLabelingJob)

dataLabelingJobPath(project: string, location: string, dataLabelingJob: string): string;

Return a fully-qualified dataLabelingJob resource name string.

Parameters
NameDescription
project string
location string
dataLabelingJob string
Returns
TypeDescription
string

{string} Resource name string.

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.

deleteArtifact(request, options)

deleteArtifact(request?: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes an Artifact.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest

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.aiplatform.v1.IDeleteOperationMetadata>, 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 Artifact to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   */
  // const name = 'abc123'
  /**
   *  Optional. The etag of the Artifact to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteArtifact();

deleteArtifact(request, options, callback)

deleteArtifact(request: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteArtifact(request, callback)

deleteArtifact(request: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteContext(request, options)

deleteContext(request?: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a stored Context.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteContextRequest

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.aiplatform.v1.IDeleteOperationMetadata>, 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 Context to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const name = 'abc123'
  /**
   *  The force deletion semantics is still undefined.
   *  Users should not use this field.
   */
  // const force = true
  /**
   *  Optional. The etag of the Context to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteContext();

deleteContext(request, options, callback)

deleteContext(request: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteContextRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteContext(request, callback)

deleteContext(request: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteContextRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteExecution(request, options)

deleteExecution(request?: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes an Execution.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest

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.aiplatform.v1.IDeleteOperationMetadata>, 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 Execution to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const name = 'abc123'
  /**
   *  Optional. The etag of the Execution to delete.
   *  If this is provided, it must match the server's etag. Otherwise, the
   *  request will fail with a FAILED_PRECONDITION.
   */
  // const etag = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteExecution();

deleteExecution(request, options, callback)

deleteExecution(request: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteExecution(request, callback)

deleteExecution(request: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteMetadataStore(request, options)

deleteMetadataStore(request?: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest

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.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, 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 MetadataStore to delete.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callDeleteMetadataStore();

deleteMetadataStore(request, options, callback)

deleteMetadataStore(request: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest
options CallOptions
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

deleteMetadataStore(request, callback)

deleteMetadataStore(request: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest
callback Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

endpointPath(project, location, endpoint)

endpointPath(project: string, location: string, endpoint: string): string;

Return a fully-qualified endpoint resource name string.

Parameters
NameDescription
project string
location string
endpoint string
Returns
TypeDescription
string

{string} Resource name string.

entityTypePath(project, location, featurestore, entityType)

entityTypePath(project: string, location: string, featurestore: string, entityType: string): string;

Return a fully-qualified entityType resource name string.

Parameters
NameDescription
project string
location string
featurestore string
entityType string
Returns
TypeDescription
string

{string} Resource name string.

executionPath(project, location, metadataStore, execution)

executionPath(project: string, location: string, metadataStore: string, execution: string): string;

Return a fully-qualified execution resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
execution string
Returns
TypeDescription
string

{string} Resource name string.

featurePath(project, location, featurestore, entityType, feature)

featurePath(project: string, location: string, featurestore: string, entityType: string, feature: string): string;

Return a fully-qualified feature resource name string.

Parameters
NameDescription
project string
location string
featurestore string
entityType string
feature string
Returns
TypeDescription
string

{string} Resource name string.

featurestorePath(project, location, featurestore)

featurestorePath(project: string, location: string, featurestore: string): string;

Return a fully-qualified featurestore resource name string.

Parameters
NameDescription
project string
location string
featurestore string
Returns
TypeDescription
string

{string} Resource name string.

getArtifact(request, options)

getArtifact(request?: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IArtifact,
        protos.google.cloud.aiplatform.v1.IGetArtifactRequest | undefined,
        {} | undefined
    ]>;

Retrieves a specific Artifact.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetArtifactRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. 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 Artifact to retrieve.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.getArtifact(request);
    console.log(response);
  }

  callGetArtifact();

getArtifact(request, options, callback)

getArtifact(request: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetArtifactRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getArtifact(request, callback)

getArtifact(request: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetArtifactRequest
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getContext(request, options)

getContext(request?: protos.google.cloud.aiplatform.v1.IGetContextRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IContext,
        protos.google.cloud.aiplatform.v1.IGetContextRequest | undefined,
        {} | undefined
    ]>;

Retrieves a specific Context.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetContextRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. 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 Context to retrieve.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.getContext(request);
    console.log(response);
  }

  callGetContext();

getContext(request, options, callback)

getContext(request: protos.google.cloud.aiplatform.v1.IGetContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetContextRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getContext(request, callback)

getContext(request: protos.google.cloud.aiplatform.v1.IGetContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetContextRequest
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getExecution(request, options)

getExecution(request?: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IExecution,
        protos.google.cloud.aiplatform.v1.IGetExecutionRequest | undefined,
        {} | undefined
    ]>;

Retrieves a specific Execution.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetExecutionRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. 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 Execution to retrieve.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.getExecution(request);
    console.log(response);
  }

  callGetExecution();

getExecution(request, options, callback)

getExecution(request: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetExecutionRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getExecution(request, callback)

getExecution(request: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetExecutionRequest
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getMetadataSchema(request, options)

getMetadataSchema(request?: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IMetadataSchema,
        protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | undefined,
        {} | undefined
    ]>;

Retrieves a specific MetadataSchema.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataSchema]. 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 MetadataSchema to retrieve.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.getMetadataSchema(request);
    console.log(response);
  }

  callGetMetadataSchema();

getMetadataSchema(request, options, callback)

getMetadataSchema(request: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getMetadataSchema(request, callback)

getMetadataSchema(request: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getMetadataStore(request, options)

getMetadataStore(request?: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IMetadataStore,
        protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | undefined,
        {} | undefined
    ]>;

Retrieves a specific MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataStore]. 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 MetadataStore to retrieve.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const name = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

    // Run request
    const response = await aiplatformClient.getMetadataStore(request);
    console.log(response);
  }

  callGetMetadataStore();

getMetadataStore(request, options, callback)

getMetadataStore(request: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

getMetadataStore(request, callback)

getMetadataStore(request: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest
callback Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | 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

hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)

hyperparameterTuningJobPath(project: string, location: string, hyperparameterTuningJob: string): string;

Return a fully-qualified hyperparameterTuningJob resource name string.

Parameters
NameDescription
project string
location string
hyperparameterTuningJob string
Returns
TypeDescription
string

{string} Resource name string.

indexEndpointPath(project, location, indexEndpoint)

indexEndpointPath(project: string, location: string, indexEndpoint: string): string;

Return a fully-qualified indexEndpoint resource name string.

Parameters
NameDescription
project string
location string
indexEndpoint string
Returns
TypeDescription
string

{string} Resource name string.

indexPath(project, location, index)

indexPath(project: string, location: string, index: string): string;

Return a fully-qualified index resource name string.

Parameters
NameDescription
project string
location string
index string
Returns
TypeDescription
string

{string} Resource name string.

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.

listArtifacts(request, options)

listArtifacts(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IArtifact[],
        protos.google.cloud.aiplatform.v1.IListArtifactsRequest | null,
        protos.google.cloud.aiplatform.v1.IListArtifactsResponse
    ]>;

Lists Artifacts in the MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListArtifactsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact[], protos.google.cloud.aiplatform.v1.IListArtifactsRequest | null, protos.google.cloud.aiplatform.v1.IListArtifactsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Artifact]. 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 listArtifactsAsync() 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.

listArtifacts(request, options, callback)

listArtifacts(request: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListArtifactsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>
Returns
TypeDescription
void

listArtifacts(request, callback)

listArtifacts(request: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListArtifactsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>
Returns
TypeDescription
void

listArtifactsAsync(request, options)

listArtifactsAsync(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IArtifact>;

Equivalent to listArtifacts, 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.aiplatform.v1.IListArtifactsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1.IArtifact>

{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 [Artifact]. 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 MetadataStore whose Artifacts should be listed.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  The maximum number of Artifacts to return. The service may return fewer.
   *  Must be in range 1-1000, inclusive. Defaults to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous MetadataService.ListArtifacts google.cloud.aiplatform.v1.MetadataService.ListArtifacts 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other provided parameters must match the call that
   *  provided the page token. (Otherwise the request will fail with
   *  INVALID_ARGUMENT error.)
   */
  // const pageToken = 'abc123'
  /**
   *  Filter specifying the boolean condition for the Artifacts to satisfy in
   *  order to be part of the result set.
   *  The syntax to define filter query is based on https://google.aip.dev/160.
   *  The supported set of filters include the following:
   *  *   **Attribute filtering**:
   *      For example: `display_name = "test"`.
   *      Supported fields include: `name`, `display_name`, `uri`, `state`,
   *      `schema_title`, `create_time`, and `update_time`.
   *      Time fields, such as `create_time` and `update_time`, require values
   *      specified in RFC-3339 format.
   *      For example: `create_time = "2020-11-19T11:30:00-04:00"`
   *  *   **Metadata field**:
   *      To filter on metadata fields use traversal operation as follows:
   *      `metadata.

listArtifactsStream(request, options)

listArtifactsStream(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListArtifactsRequest

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 [Artifact] 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 listArtifactsAsync() 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.

listContexts(request, options)

listContexts(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IContext[],
        protos.google.cloud.aiplatform.v1.IListContextsRequest | null,
        protos.google.cloud.aiplatform.v1.IListContextsResponse
    ]>;

Lists Contexts on the MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListContextsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IContext[], protos.google.cloud.aiplatform.v1.IListContextsRequest | null, protos.google.cloud.aiplatform.v1.IListContextsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Context]. 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 listContextsAsync() 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.

listContexts(request, options, callback)

listContexts(request: protos.google.cloud.aiplatform.v1.IListContextsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListContextsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>
Returns
TypeDescription
void

listContexts(request, callback)

listContexts(request: protos.google.cloud.aiplatform.v1.IListContextsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListContextsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>
Returns
TypeDescription
void

listContextsAsync(request, options)

listContextsAsync(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IContext>;

Equivalent to listContexts, 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.aiplatform.v1.IListContextsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1.IContext>

{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 [Context]. 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 MetadataStore whose Contexts should be listed.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  The maximum number of Contexts to return. The service may return fewer.
   *  Must be in range 1-1000, inclusive. Defaults to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous MetadataService.ListContexts google.cloud.aiplatform.v1.MetadataService.ListContexts 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other provided parameters must match the call that
   *  provided the page token. (Otherwise the request will fail with
   *  INVALID_ARGUMENT error.)
   */
  // const pageToken = 'abc123'
  /**
   *  Filter specifying the boolean condition for the Contexts to satisfy in
   *  order to be part of the result set.
   *  The syntax to define filter query is based on https://google.aip.dev/160.
   *  Following are the supported set of filters:
   *  *  **Attribute filtering**:
   *     For example: `display_name = "test"`.
   *     Supported fields include: `name`, `display_name`, `schema_title`,
   *     `create_time`, and `update_time`.
   *     Time fields, such as `create_time` and `update_time`, require values
   *     specified in RFC-3339 format.
   *     For example: `create_time = "2020-11-19T11:30:00-04:00"`.
   *  *  **Metadata field**:
   *     To filter on metadata fields use traversal operation as follows:
   *     `metadata.

listContextsStream(request, options)

listContextsStream(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListContextsRequest

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 [Context] 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 listContextsAsync() 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.

listExecutions(request, options)

listExecutions(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IExecution[],
        protos.google.cloud.aiplatform.v1.IListExecutionsRequest | null,
        protos.google.cloud.aiplatform.v1.IListExecutionsResponse
    ]>;

Lists Executions in the MetadataStore.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListExecutionsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IExecution[], protos.google.cloud.aiplatform.v1.IListExecutionsRequest | null, protos.google.cloud.aiplatform.v1.IListExecutionsResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [Execution]. 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 listExecutionsAsync() 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.

listExecutions(request, options, callback)

listExecutions(request: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListExecutionsRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>
Returns
TypeDescription
void

listExecutions(request, callback)

listExecutions(request: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListExecutionsRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>
Returns
TypeDescription
void

listExecutionsAsync(request, options)

listExecutionsAsync(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IExecution>;

Equivalent to listExecutions, 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.aiplatform.v1.IListExecutionsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1.IExecution>

{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 [Execution]. 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 MetadataStore whose Executions should be listed.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  The maximum number of Executions to return. The service may return fewer.
   *  Must be in range 1-1000, inclusive. Defaults to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous MetadataService.ListExecutions google.cloud.aiplatform.v1.MetadataService.ListExecutions 
   *  call. Provide this to retrieve the subsequent page.
   *  When paginating, all other provided parameters must match the call that
   *  provided the page token. (Otherwise the request will fail with an
   *  INVALID_ARGUMENT error.)
   */
  // const pageToken = 'abc123'
  /**
   *  Filter specifying the boolean condition for the Executions to satisfy in
   *  order to be part of the result set.
   *  The syntax to define filter query is based on https://google.aip.dev/160.
   *  Following are the supported set of filters:
   *  *  **Attribute filtering**:
   *     For example: `display_name = "test"`.
   *     Supported fields include: `name`, `display_name`, `state`,
   *     `schema_title`, `create_time`, and `update_time`.
   *     Time fields, such as `create_time` and `update_time`, require values
   *     specified in RFC-3339 format.
   *     For example: `create_time = "2020-11-19T11:30:00-04:00"`.
   *  *  **Metadata field**:
   *     To filter on metadata fields use traversal operation as follows:
   *     `metadata.

listExecutionsStream(request, options)

listExecutionsStream(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListExecutionsRequest

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 [Execution] 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 listExecutionsAsync() 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.

listMetadataSchemas(request, options)

listMetadataSchemas(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IMetadataSchema[],
        protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest | null,
        protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse
    ]>;

Lists MetadataSchemas.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema[], protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest | null, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [MetadataSchema]. 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 listMetadataSchemasAsync() 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.

listMetadataSchemas(request, options, callback)

listMetadataSchemas(request: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>
Returns
TypeDescription
void

listMetadataSchemas(request, callback)

listMetadataSchemas(request: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>
Returns
TypeDescription
void

listMetadataSchemasAsync(request, options)

listMetadataSchemasAsync(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataSchema>;

Equivalent to listMetadataSchemas, 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.aiplatform.v1.IListMetadataSchemasRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataSchema>

{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 [MetadataSchema]. 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 MetadataStore whose MetadataSchemas should be listed.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  The maximum number of MetadataSchemas to return. The service may return
   *  fewer.
   *  Must be in range 1-1000, inclusive. Defaults to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  MetadataService.ListMetadataSchemas google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas  call. Provide this to retrieve the
   *  next page.
   *  When paginating, all other provided parameters must match the call that
   *  provided the page token. (Otherwise the request will fail with
   *  INVALID_ARGUMENT error.)
   */
  // const pageToken = 'abc123'
  /**
   *  A query to filter available MetadataSchemas for matching results.
   */
  // const filter = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callListMetadataSchemas();

listMetadataSchemasStream(request, options)

listMetadataSchemasStream(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest

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 [MetadataSchema] 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 listMetadataSchemasAsync() 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.

listMetadataStores(request, options)

listMetadataStores(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IMetadataStore[],
        protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest | null,
        protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse
    ]>;

Lists MetadataStores for a Location.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataStore[], protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest | null, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse ]>

{Promise} - The promise which resolves to an array. The first element of the array is Array of [MetadataStore]. 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 listMetadataStoresAsync() 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.

listMetadataStores(request, options, callback)

listMetadataStores(request: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
options CallOptions
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>
Returns
TypeDescription
void

listMetadataStores(request, callback)

listMetadataStores(request: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
callback PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>
Returns
TypeDescription
void

listMetadataStoresAsync(request, options)

listMetadataStoresAsync(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataStore>;

Equivalent to listMetadataStores, 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.aiplatform.v1.IListMetadataStoresRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataStore>

{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 [MetadataStore]. 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 Location whose MetadataStores should be listed.
   *  Format:
   *  `projects/{project}/locations/{location}`
   */
  // const parent = 'abc123'
  /**
   *  The maximum number of Metadata Stores to return. The service may return
   *  fewer.
   *  Must be in range 1-1000, inclusive. Defaults to 100.
   */
  // const pageSize = 1234
  /**
   *  A page token, received from a previous
   *  MetadataService.ListMetadataStores google.cloud.aiplatform.v1.MetadataService.ListMetadataStores  call. Provide this to retrieve the
   *  subsequent page.
   *  When paginating, all other provided parameters must match the call that
   *  provided the page token. (Otherwise the request will fail with
   *  INVALID_ARGUMENT error.)
   */
  // const pageToken = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

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

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

  callListMetadataStores();

listMetadataStoresStream(request, options)

listMetadataStoresStream(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): Transform;

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

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest

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 [MetadataStore] 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 listMetadataStoresAsync() 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.

matchAnnotationFromAnnotationName(annotationName)

matchAnnotationFromAnnotationName(annotationName: string): string | number;

Parse the annotation from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the annotation.

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.

matchArtifactFromArtifactName(artifactName)

matchArtifactFromArtifactName(artifactName: string): string | number;

Parse the artifact from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the artifact.

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)

matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the batch_prediction_job from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the batch_prediction_job.

matchContextFromContextName(contextName)

matchContextFromContextName(contextName: string): string | number;

Parse the context from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the context.

matchCustomJobFromCustomJobName(customJobName)

matchCustomJobFromCustomJobName(customJobName: string): string | number;

Parse the custom_job from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the custom_job.

matchDataItemFromAnnotationName(annotationName)

matchDataItemFromAnnotationName(annotationName: string): string | number;

Parse the data_item from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the data_item.

matchDataItemFromDataItemName(dataItemName)

matchDataItemFromDataItemName(dataItemName: string): string | number;

Parse the data_item from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the data_item.

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)

matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the data_labeling_job from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob resource.

Returns
TypeDescription
string | number

{string} A string representing the data_labeling_job.

matchDatasetFromAnnotationName(annotationName)

matchDatasetFromAnnotationName(annotationName: string): string | number;

Parse the dataset from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the dataset.

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.

matchDatasetFromDataItemName(dataItemName)

matchDatasetFromDataItemName(dataItemName: string): string | number;

Parse the dataset from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem 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.

matchEndpointFromEndpointName(endpointName)

matchEndpointFromEndpointName(endpointName: string): string | number;

Parse the endpoint from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the endpoint.

matchEntityTypeFromEntityTypeName(entityTypeName)

matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;

Parse the entity_type from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEntityTypeFromFeatureName(featureName)

matchEntityTypeFromFeatureName(featureName: string): string | number;

Parse the entity_type from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the entity_type.

matchEvaluationFromModelEvaluationName(modelEvaluationName)

matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;

Parse the evaluation from ModelEvaluation resource.

Parameter
NameDescription
modelEvaluationName string

A fully-qualified path representing ModelEvaluation resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the evaluation from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the evaluation.

matchExecutionFromExecutionName(executionName)

matchExecutionFromExecutionName(executionName: string): string | number;

Parse the execution from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the execution.

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)

matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the experiment from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardRunName(tensorboardRunName)

matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the experiment from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the experiment from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the experiment.

matchFeatureFromFeatureName(featureName)

matchFeatureFromFeatureName(featureName: string): string | number;

Parse the feature from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the feature.

matchFeaturestoreFromEntityTypeName(entityTypeName)

matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;

Parse the featurestore from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeatureName(featureName)

matchFeaturestoreFromFeatureName(featureName: string): string | number;

Parse the featurestore from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchFeaturestoreFromFeaturestoreName(featurestoreName)

matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;

Parse the featurestore from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the featurestore.

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the hyperparameter_tuning_job.

matchIndexEndpointFromIndexEndpointName(indexEndpointName)

matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the index_endpoint from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the index_endpoint.

matchIndexFromIndexName(indexName)

matchIndexFromIndexName(indexName: string): string | number;

Parse the index from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index resource.

Returns
TypeDescription
string | number

{string} A string representing the index.

matchLocationFromAnnotationName(annotationName)

matchLocationFromAnnotationName(annotationName: string): string | number;

Parse the location from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

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.

matchLocationFromArtifactName(artifactName)

matchLocationFromArtifactName(artifactName: string): string | number;

Parse the location from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromBatchPredictionJobName(batchPredictionJobName)

matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the location from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromContextName(contextName)

matchLocationFromContextName(contextName: string): string | number;

Parse the location from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromCustomJobName(customJobName)

matchLocationFromCustomJobName(customJobName: string): string | number;

Parse the location from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataItemName(dataItemName)

matchLocationFromDataItemName(dataItemName: string): string | number;

Parse the location from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromDataLabelingJobName(dataLabelingJobName)

matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the location from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob 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.

matchLocationFromEndpointName(endpointName)

matchLocationFromEndpointName(endpointName: string): string | number;

Parse the location from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromEntityTypeName(entityTypeName)

matchLocationFromEntityTypeName(entityTypeName: string): string | number;

Parse the location from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromExecutionName(executionName)

matchLocationFromExecutionName(executionName: string): string | number;

Parse the location from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeatureName(featureName)

matchLocationFromFeatureName(featureName: string): string | number;

Parse the location from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromFeaturestoreName(featurestoreName)

matchLocationFromFeaturestoreName(featurestoreName: string): string | number;

Parse the location from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the location from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexEndpointName(indexEndpointName)

matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the location from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromIndexName(indexName)

matchLocationFromIndexName(indexName: string): string | number;

Parse the location from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index 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.

matchLocationFromMetadataSchemaName(metadataSchemaName)

matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the location from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromMetadataStoreName(metadataStoreName)

matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the location from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the location from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob 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.

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)

matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the location from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice 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.

matchLocationFromPipelineJobName(pipelineJobName)

matchLocationFromPipelineJobName(pipelineJobName: string): string | number;

Parse the location from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromSpecialistPoolName(specialistPoolName)

matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the location from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromStudyName(studyName)

matchLocationFromStudyName(studyName: string): string | number;

Parse the location from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardExperimentName(tensorboardExperimentName)

matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the location from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardName(tensorboardName)

matchLocationFromTensorboardName(tensorboardName: string): string | number;

Parse the location from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardRunName(tensorboardRunName)

matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the location from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the location from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrainingPipelineName(trainingPipelineName)

matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the location from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchLocationFromTrialName(trialName)

matchLocationFromTrialName(trialName: string): string | number;

Parse the location from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the location.

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)

matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_schema from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_schema.

matchMetadataStoreFromArtifactName(artifactName)

matchMetadataStoreFromArtifactName(artifactName: string): string | number;

Parse the metadata_store from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromContextName(contextName)

matchMetadataStoreFromContextName(contextName: string): string | number;

Parse the metadata_store from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromExecutionName(executionName)

matchMetadataStoreFromExecutionName(executionName: string): string | number;

Parse the metadata_store from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)

matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the metadata_store from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchMetadataStoreFromMetadataStoreName(metadataStoreName)

matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the metadata_store from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the metadata_store.

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the model_deployment_monitoring_job from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob resource.

Returns
TypeDescription
string | number

{string} A string representing the model_deployment_monitoring_job.

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.

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)

matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the model from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice 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.

matchPipelineJobFromPipelineJobName(pipelineJobName)

matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;

Parse the pipeline_job from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the pipeline_job.

matchProjectFromAnnotationName(annotationName)

matchProjectFromAnnotationName(annotationName: string): string | number;

Parse the project from Annotation resource.

Parameter
NameDescription
annotationName string

A fully-qualified path representing Annotation resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

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.

matchProjectFromArtifactName(artifactName)

matchProjectFromArtifactName(artifactName: string): string | number;

Parse the project from Artifact resource.

Parameter
NameDescription
artifactName string

A fully-qualified path representing Artifact resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromBatchPredictionJobName(batchPredictionJobName)

matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;

Parse the project from BatchPredictionJob resource.

Parameter
NameDescription
batchPredictionJobName string

A fully-qualified path representing BatchPredictionJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromContextName(contextName)

matchProjectFromContextName(contextName: string): string | number;

Parse the project from Context resource.

Parameter
NameDescription
contextName string

A fully-qualified path representing Context resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromCustomJobName(customJobName)

matchProjectFromCustomJobName(customJobName: string): string | number;

Parse the project from CustomJob resource.

Parameter
NameDescription
customJobName string

A fully-qualified path representing CustomJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataItemName(dataItemName)

matchProjectFromDataItemName(dataItemName: string): string | number;

Parse the project from DataItem resource.

Parameter
NameDescription
dataItemName string

A fully-qualified path representing DataItem resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromDataLabelingJobName(dataLabelingJobName)

matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;

Parse the project from DataLabelingJob resource.

Parameter
NameDescription
dataLabelingJobName string

A fully-qualified path representing DataLabelingJob 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.

matchProjectFromEndpointName(endpointName)

matchProjectFromEndpointName(endpointName: string): string | number;

Parse the project from Endpoint resource.

Parameter
NameDescription
endpointName string

A fully-qualified path representing Endpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromEntityTypeName(entityTypeName)

matchProjectFromEntityTypeName(entityTypeName: string): string | number;

Parse the project from EntityType resource.

Parameter
NameDescription
entityTypeName string

A fully-qualified path representing EntityType resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromExecutionName(executionName)

matchProjectFromExecutionName(executionName: string): string | number;

Parse the project from Execution resource.

Parameter
NameDescription
executionName string

A fully-qualified path representing Execution resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeatureName(featureName)

matchProjectFromFeatureName(featureName: string): string | number;

Parse the project from Feature resource.

Parameter
NameDescription
featureName string

A fully-qualified path representing Feature resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromFeaturestoreName(featurestoreName)

matchProjectFromFeaturestoreName(featurestoreName: string): string | number;

Parse the project from Featurestore resource.

Parameter
NameDescription
featurestoreName string

A fully-qualified path representing Featurestore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)

matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;

Parse the project from HyperparameterTuningJob resource.

Parameter
NameDescription
hyperparameterTuningJobName string

A fully-qualified path representing HyperparameterTuningJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexEndpointName(indexEndpointName)

matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;

Parse the project from IndexEndpoint resource.

Parameter
NameDescription
indexEndpointName string

A fully-qualified path representing IndexEndpoint resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromIndexName(indexName)

matchProjectFromIndexName(indexName: string): string | number;

Parse the project from Index resource.

Parameter
NameDescription
indexName string

A fully-qualified path representing Index 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.

matchProjectFromMetadataSchemaName(metadataSchemaName)

matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;

Parse the project from MetadataSchema resource.

Parameter
NameDescription
metadataSchemaName string

A fully-qualified path representing MetadataSchema resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromMetadataStoreName(metadataStoreName)

matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;

Parse the project from MetadataStore resource.

Parameter
NameDescription
metadataStoreName string

A fully-qualified path representing MetadataStore resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)

matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;

Parse the project from ModelDeploymentMonitoringJob resource.

Parameter
NameDescription
modelDeploymentMonitoringJobName string

A fully-qualified path representing ModelDeploymentMonitoringJob 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.

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)

matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the project from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice 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.

matchProjectFromPipelineJobName(pipelineJobName)

matchProjectFromPipelineJobName(pipelineJobName: string): string | number;

Parse the project from PipelineJob resource.

Parameter
NameDescription
pipelineJobName string

A fully-qualified path representing PipelineJob resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromProjectName(projectName)

matchProjectFromProjectName(projectName: string): string | number;

Parse the project from Project resource.

Parameter
NameDescription
projectName string

A fully-qualified path representing Project resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromSpecialistPoolName(specialistPoolName)

matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the project from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromStudyName(studyName)

matchProjectFromStudyName(studyName: string): string | number;

Parse the project from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardExperimentName(tensorboardExperimentName)

matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the project from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardName(tensorboardName)

matchProjectFromTensorboardName(tensorboardName: string): string | number;

Parse the project from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardRunName(tensorboardRunName)

matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the project from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the project from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrainingPipelineName(trainingPipelineName)

matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the project from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchProjectFromTrialName(trialName)

matchProjectFromTrialName(trialName: string): string | number;

Parse the project from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the project.

matchRunFromTensorboardRunName(tensorboardRunName)

matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the run from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the run from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the run.

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)

matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;

Parse the slice from ModelEvaluationSlice resource.

Parameter
NameDescription
modelEvaluationSliceName string

A fully-qualified path representing ModelEvaluationSlice resource.

Returns
TypeDescription
string | number

{string} A string representing the slice.

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)

matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;

Parse the specialist_pool from SpecialistPool resource.

Parameter
NameDescription
specialistPoolName string

A fully-qualified path representing SpecialistPool resource.

Returns
TypeDescription
string | number

{string} A string representing the specialist_pool.

matchStudyFromStudyName(studyName)

matchStudyFromStudyName(studyName: string): string | number;

Parse the study from Study resource.

Parameter
NameDescription
studyName string

A fully-qualified path representing Study resource.

Returns
TypeDescription
string | number

{string} A string representing the study.

matchStudyFromTrialName(trialName)

matchStudyFromTrialName(trialName: string): string | number;

Parse the study from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the study.

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)

matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;

Parse the tensorboard from TensorboardExperiment resource.

Parameter
NameDescription
tensorboardExperimentName string

A fully-qualified path representing TensorboardExperiment resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardName(tensorboardName)

matchTensorboardFromTensorboardName(tensorboardName: string): string | number;

Parse the tensorboard from Tensorboard resource.

Parameter
NameDescription
tensorboardName string

A fully-qualified path representing Tensorboard resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardRunName(tensorboardRunName)

matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;

Parse the tensorboard from TensorboardRun resource.

Parameter
NameDescription
tensorboardRunName string

A fully-qualified path representing TensorboardRun resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the tensorboard from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the tensorboard.

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)

matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;

Parse the time_series from TensorboardTimeSeries resource.

Parameter
NameDescription
tensorboardTimeSeriesName string

A fully-qualified path representing TensorboardTimeSeries resource.

Returns
TypeDescription
string | number

{string} A string representing the time_series.

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)

matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;

Parse the training_pipeline from TrainingPipeline resource.

Parameter
NameDescription
trainingPipelineName string

A fully-qualified path representing TrainingPipeline resource.

Returns
TypeDescription
string | number

{string} A string representing the training_pipeline.

matchTrialFromTrialName(trialName)

matchTrialFromTrialName(trialName: string): string | number;

Parse the trial from Trial resource.

Parameter
NameDescription
trialName string

A fully-qualified path representing Trial resource.

Returns
TypeDescription
string | number

{string} A string representing the trial.

metadataSchemaPath(project, location, metadataStore, metadataSchema)

metadataSchemaPath(project: string, location: string, metadataStore: string, metadataSchema: string): string;

Return a fully-qualified metadataSchema resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
metadataSchema string
Returns
TypeDescription
string

{string} Resource name string.

metadataStorePath(project, location, metadataStore)

metadataStorePath(project: string, location: string, metadataStore: string): string;

Return a fully-qualified metadataStore resource name string.

Parameters
NameDescription
project string
location string
metadataStore string
Returns
TypeDescription
string

{string} Resource name string.

modelDeploymentMonitoringJobPath(project, location, modelDeploymentMonitoringJob)

modelDeploymentMonitoringJobPath(project: string, location: string, modelDeploymentMonitoringJob: string): string;

Return a fully-qualified modelDeploymentMonitoringJob resource name string.

Parameters
NameDescription
project string
location string
modelDeploymentMonitoringJob string
Returns
TypeDescription
string

{string} Resource name string.

modelEvaluationPath(project, location, model, evaluation)

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

Return a fully-qualified modelEvaluation resource name string.

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

{string} Resource name string.

modelEvaluationSlicePath(project, location, model, evaluation, slice)

modelEvaluationSlicePath(project: string, location: string, model: string, evaluation: string, slice: string): string;

Return a fully-qualified modelEvaluationSlice resource name string.

Parameters
NameDescription
project string
location string
model string
evaluation string
slice 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.

pipelineJobPath(project, location, pipelineJob)

pipelineJobPath(project: string, location: string, pipelineJob: string): string;

Return a fully-qualified pipelineJob resource name string.

Parameters
NameDescription
project string
location string
pipelineJob string
Returns
TypeDescription
string

{string} Resource name string.

projectPath(project)

projectPath(project: string): string;

Return a fully-qualified project resource name string.

Parameter
NameDescription
project string
Returns
TypeDescription
string

{string} Resource name string.

purgeArtifacts(request, options)

purgeArtifacts(request?: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Purges Artifacts.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, 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 metadata store to purge Artifacts from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Artifacts to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" artifact="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeartifacts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeartifacts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeartifacts();="">

purgeArtifacts(request, options, callback)

purgeArtifacts(request: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

purgeArtifacts(request, callback)

purgeArtifacts(request: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

purgeContexts(request, options)

purgeContexts(request?: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Purges Contexts.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeContextsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, 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 metadata store to purge Contexts from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Contexts to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" context="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgecontexts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgecontexts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgecontexts();="">

purgeContexts(request, options, callback)

purgeContexts(request: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeContextsRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

purgeContexts(request, callback)

purgeContexts(request: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeContextsRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

purgeExecutions(request, options)

purgeExecutions(request?: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, options?: CallOptions): Promise<[
        LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>,
        protos.google.longrunning.IOperation | undefined,
        {} | undefined
    ]>;

Purges Executions.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, 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 metadata store to purge Executions from.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
   */
  // const parent = 'abc123'
  /**
   *  Required. A required filter matching the Executions to be purged.
   *  E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" execution="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeexecutions()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeexecutions(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeexecutions();="">

purgeExecutions(request, options, callback)

purgeExecutions(request: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest
options CallOptions
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

purgeExecutions(request, callback)

purgeExecutions(request: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest
callback Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryArtifactLineageSubgraph(request, options)

queryArtifactLineageSubgraph(request?: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ILineageSubgraph,
        (protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | undefined),
        {} | undefined
    ]>;

Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. 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 Artifact whose Lineage needs to be retrieved as a
   *  LineageSubgraph.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   *  The request may error with FAILED_PRECONDITION if the number of Artifacts,
   *  the number of Executions, or the number of Events that would be returned
   *  for the Context exceeds 1000.
   */
  // const artifact = 'abc123'
  /**
   *  Specifies the size of the lineage graph in terms of number of hops from the
   *  specified artifact.
   *  Negative Value: INVALID_ARGUMENT error is returned
   *  0: Only input artifact is returned.
   *  No value: Transitive closure is performed to return the complete graph.
   */
  // const maxHops = 1234
  /**
   *  Filter specifying the boolean condition for the Artifacts to satisfy in
   *  order to be part of the Lineage Subgraph.
   *  The syntax to define filter query is based on https://google.aip.dev/160.
   *  The supported set of filters include the following:
   *  *  **Attribute filtering**:
   *     For example: `display_name = "test"`
   *     Supported fields include: `name`, `display_name`, `uri`, `state`,
   *     `schema_title`, `create_time`, and `update_time`.
   *     Time fields, such as `create_time` and `update_time`, require values
   *     specified in RFC-3339 format.
   *     For example: `create_time = "2020-11-19T11:30:00-04:00"`
   *  *  **Metadata field**:
   *     To filter on metadata fields use traversal operation as follows:
   *     `metadata.

queryArtifactLineageSubgraph(request, options, callback)

queryArtifactLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryArtifactLineageSubgraph(request, callback)

queryArtifactLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryContextLineageSubgraph(request, options)

queryContextLineageSubgraph(request?: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ILineageSubgraph,
        (protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | undefined),
        {} | undefined
    ]>;

Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. 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 Context whose Artifacts and Executions
   *  should be retrieved as a LineageSubgraph.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   *  The request may error with FAILED_PRECONDITION if the number of Artifacts,
   *  the number of Executions, or the number of Events that would be returned
   *  for the Context exceeds 1000.
   */
  // const context = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callQueryContextLineageSubgraph() {
    // Construct request
    const request = {
      context,
    };

    // Run request
    const response = await aiplatformClient.queryContextLineageSubgraph(request);
    console.log(response);
  }

  callQueryContextLineageSubgraph();

queryContextLineageSubgraph(request, options, callback)

queryContextLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryContextLineageSubgraph(request, callback)

queryContextLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryExecutionInputsAndOutputs(request, options)

queryExecutionInputsAndOutputs(request?: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.ILineageSubgraph,
        (protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | undefined),
        {} | undefined
    ]>;

Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | undefined), {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. 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 Execution whose input and output Artifacts should
   *  be retrieved as a LineageSubgraph.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const execution = 'abc123'

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callQueryExecutionInputsAndOutputs() {
    // Construct request
    const request = {
      execution,
    };

    // Run request
    const response = await aiplatformClient.queryExecutionInputsAndOutputs(request);
    console.log(response);
  }

  callQueryExecutionInputsAndOutputs();

queryExecutionInputsAndOutputs(request, options, callback)

queryExecutionInputsAndOutputs(request: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

queryExecutionInputsAndOutputs(request, callback)

queryExecutionInputsAndOutputs(request: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest
callback Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

specialistPoolPath(project, location, specialistPool)

specialistPoolPath(project: string, location: string, specialistPool: string): string;

Return a fully-qualified specialistPool resource name string.

Parameters
NameDescription
project string
location string
specialistPool string
Returns
TypeDescription
string

{string} Resource name string.

studyPath(project, location, study)

studyPath(project: string, location: string, study: string): string;

Return a fully-qualified study resource name string.

Parameters
NameDescription
project string
location string
study string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardExperimentPath(project, location, tensorboard, experiment)

tensorboardExperimentPath(project: string, location: string, tensorboard: string, experiment: string): string;

Return a fully-qualified tensorboardExperiment resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardPath(project, location, tensorboard)

tensorboardPath(project: string, location: string, tensorboard: string): string;

Return a fully-qualified tensorboard resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardRunPath(project, location, tensorboard, experiment, run)

tensorboardRunPath(project: string, location: string, tensorboard: string, experiment: string, run: string): string;

Return a fully-qualified tensorboardRun resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
run string
Returns
TypeDescription
string

{string} Resource name string.

tensorboardTimeSeriesPath(project, location, tensorboard, experiment, run, timeSeries)

tensorboardTimeSeriesPath(project: string, location: string, tensorboard: string, experiment: string, run: string, timeSeries: string): string;

Return a fully-qualified tensorboardTimeSeries resource name string.

Parameters
NameDescription
project string
location string
tensorboard string
experiment string
run string
timeSeries string
Returns
TypeDescription
string

{string} Resource name string.

trainingPipelinePath(project, location, trainingPipeline)

trainingPipelinePath(project: string, location: string, trainingPipeline: string): string;

Return a fully-qualified trainingPipeline resource name string.

Parameters
NameDescription
project string
location string
trainingPipeline string
Returns
TypeDescription
string

{string} Resource name string.

trialPath(project, location, study, trial)

trialPath(project: string, location: string, study: string, trial: string): string;

Return a fully-qualified trial resource name string.

Parameters
NameDescription
project string
location string
study string
trial string
Returns
TypeDescription
string

{string} Resource name string.

updateArtifact(request, options)

updateArtifact(request?: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IArtifact,
        protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | undefined,
        {} | undefined
    ]>;

Updates a stored Artifact.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. 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 Artifact containing updates.
   *  The Artifact's Artifact.name google.cloud.aiplatform.v1.Artifact.name  field is used to identify the Artifact to
   *  be updated.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
   */
  // const artifact = {}
  /**
   *  Required. A FieldMask indicating which fields should be updated.
   *  Functionality of this field is not yet supported.
   */
  // const updateMask = {}
  /**
   *  If set to true, and the Artifact google.cloud.aiplatform.v1.Artifact  is not found, a new Artifact google.cloud.aiplatform.v1.Artifact  is
   *  created.
   */
  // const allowMissing = true

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callUpdateArtifact() {
    // Construct request
    const request = {
      artifact,
      updateMask,
    };

    // Run request
    const response = await aiplatformClient.updateArtifact(request);
    console.log(response);
  }

  callUpdateArtifact();

updateArtifact(request, options, callback)

updateArtifact(request: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateArtifact(request, callback)

updateArtifact(request: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest
callback Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateContext(request, options)

updateContext(request?: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IContext,
        protos.google.cloud.aiplatform.v1.IUpdateContextRequest | undefined,
        {} | undefined
    ]>;

Updates a stored Context.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateContextRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. 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 Context containing updates.
   *  The Context's Context.name google.cloud.aiplatform.v1.Context.name  field is used to identify the Context to be
   *  updated.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
   */
  // const context = {}
  /**
   *  Required. A FieldMask indicating which fields should be updated.
   *  Functionality of this field is not yet supported.
   */
  // const updateMask = {}
  /**
   *  If set to true, and the Context google.cloud.aiplatform.v1.Context  is not found, a new Context google.cloud.aiplatform.v1.Context  is
   *  created.
   */
  // const allowMissing = true

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callUpdateContext() {
    // Construct request
    const request = {
      context,
      updateMask,
    };

    // Run request
    const response = await aiplatformClient.updateContext(request);
    console.log(response);
  }

  callUpdateContext();

updateContext(request, options, callback)

updateContext(request: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateContextRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateContext(request, callback)

updateContext(request: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateContextRequest
callback Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateExecution(request, options)

updateExecution(request?: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, options?: CallOptions): Promise<[
        protos.google.cloud.aiplatform.v1.IExecution,
        protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | undefined,
        {} | undefined
    ]>;

Updates a stored Execution.

Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest

The request object that will be sent.

options CallOptions

Call options. See CallOptions for more details.

Returns
TypeDescription
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | undefined, {} | undefined ]>

{Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. 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 Execution containing updates.
   *  The Execution's Execution.name google.cloud.aiplatform.v1.Execution.name  field is used to identify the Execution
   *  to be updated.
   *  Format:
   *  `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
   */
  // const execution = {}
  /**
   *  Required. A FieldMask indicating which fields should be updated.
   *  Functionality of this field is not yet supported.
   */
  // const updateMask = {}
  /**
   *  If set to true, and the Execution google.cloud.aiplatform.v1.Execution  is not found, a new Execution google.cloud.aiplatform.v1.Execution 
   *  is created.
   */
  // const allowMissing = true

  // Imports the Aiplatform library
  const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;

  // Instantiates a client
  const aiplatformClient = new MetadataServiceClient();

  async function callUpdateExecution() {
    // Construct request
    const request = {
      execution,
      updateMask,
    };

    // Run request
    const response = await aiplatformClient.updateExecution(request);
    console.log(response);
  }

  callUpdateExecution();

updateExecution(request, options, callback)

updateExecution(request: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest
options CallOptions
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void

updateExecution(request, callback)

updateExecution(request: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>): void;
Parameters
NameDescription
request protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest
callback Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>
Returns
TypeDescription
void