The service that handles the CRUD of Vertex AI Dataset and its child resources. v1
Package
@google-cloud/aiplatformConstructors
(constructor)(opts, gaxInstance)
constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);
Construct an instance of DatasetServiceClient.
Name | Description |
opts |
ClientOptions
|
gaxInstance |
typeof gax | typeof gax.fallback
: loaded instance of |
Properties
apiEndpoint
static get apiEndpoint(): string;
The DNS address for this API service - same as servicePath(), exists for compatibility reasons.
auth
auth: gax.GoogleAuth;
datasetServiceStub
datasetServiceStub?: Promise<{
[name: string]: Function;
}>;
descriptors
descriptors: Descriptors;
iamClient
iamClient: IamClient;
innerApiCalls
innerApiCalls: {
[name: string]: Function;
};
locationsClient
locationsClient: LocationsClient;
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
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.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
dataItem |
string
|
annotation |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
annotationSpec |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
artifact |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
batchPredictionJob |
string
|
Type | Description |
string | {string} Resource name string. |
cancelOperation(request, options, callback)
cancelOperation(request: protos.google.longrunning.CancelOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>, callback?: Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>): Promise<protos.google.protobuf.Empty>;
Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED
. Clients can use or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an value with a of 1, corresponding to Code.CANCELLED
.
Name | Description |
request |
protos.google.longrunning.CancelOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.CancelOperationRequest, {} | undefined | null>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.longrunning.CancelOperationRequest, protos.google.protobuf.Empty, {} | undefined | null>
The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
Promise<protos.google.protobuf.Empty> |
const client = longrunning.operationsClient();
await client.cancelOperation({name: ''});
checkCreateDatasetProgress(name)
checkCreateDatasetProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.Dataset, protos.google.cloud.aiplatform.v1.CreateDatasetOperationMetadata>>;
Check the status of the long running operation returned by createDataset()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.Dataset, protos.google.cloud.aiplatform.v1.CreateDatasetOperationMetadata>> | {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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Location to create the Dataset in.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* Required. The Dataset to create.
*/
// const dataset = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callCreateDataset() {
// Construct request
const request = {
parent,
dataset,
};
// Run request
const [operation] = await aiplatformClient.createDataset(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateDataset();
checkDeleteDatasetProgress(name)
checkDeleteDatasetProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteDataset()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Dataset to delete.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callDeleteDataset() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteDataset(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteDataset();
checkExportDataProgress(name)
checkExportDataProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportDataResponse, protos.google.cloud.aiplatform.v1.ExportDataOperationMetadata>>;
Check the status of the long running operation returned by exportData()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.ExportDataResponse, protos.google.cloud.aiplatform.v1.ExportDataOperationMetadata>> | {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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset resource.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
/**
* Required. The desired output location.
*/
// const exportConfig = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callExportData() {
// Construct request
const request = {
name,
exportConfig,
};
// Run request
const [operation] = await aiplatformClient.exportData(request);
const [response] = await operation.promise();
console.log(response);
}
callExportData();
checkImportDataProgress(name)
checkImportDataProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportDataResponse, protos.google.cloud.aiplatform.v1.ImportDataOperationMetadata>>;
Check the status of the long running operation returned by importData()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.ImportDataResponse, protos.google.cloud.aiplatform.v1.ImportDataOperationMetadata>> | {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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset resource.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
/**
* Required. The desired input locations. The contents of all input locations
* will be imported in one batch.
*/
// const importConfigs = 1234
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callImportData() {
// Construct request
const request = {
name,
importConfigs,
};
// Run request
const [operation] = await aiplatformClient.importData(request);
const [response] = await operation.promise();
console.log(response);
}
callImportData();
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.
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
context |
string
|
Type | Description |
string | {string} Resource name string. |
createDataset(request, options)
createDataset(request?: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Creates a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateDatasetRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>,
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 |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Location to create the Dataset in.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* Required. The Dataset to create.
*/
// const dataset = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callCreateDataset() {
// Construct request
const request = {
parent,
dataset,
};
// Run request
const [operation] = await aiplatformClient.createDataset(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateDataset();
createDataset(request, options, callback)
createDataset(request: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateDatasetRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createDataset(request, callback)
createDataset(request: protos.google.cloud.aiplatform.v1.ICreateDatasetRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateDatasetRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.ICreateDatasetOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
customJobPath(project, location, customJob)
customJobPath(project: string, location: string, customJob: string): string;
Return a fully-qualified customJob resource name string.
Name | Description |
project |
string
|
location |
string
|
customJob |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
dataItem |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
dataLabelingJob |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
Type | Description |
string | {string} Resource name string. |
deleteDataset(request, options)
deleteDataset(request?: protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
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 |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Dataset to delete.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callDeleteDataset() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteDataset(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteDataset();
deleteDataset(request, options, callback)
deleteDataset(request: protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteDataset(request, callback)
deleteDataset(request: protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteDatasetRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteOperation(request, options, callback)
deleteOperation(request: protos.google.longrunning.DeleteOperationRequest, options?: gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>): Promise<protos.google.protobuf.Empty>;
Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns google.rpc.Code.UNIMPLEMENTED
.
Name | Description |
request |
protos.google.longrunning.DeleteOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.protobuf.Empty, protos.google.longrunning.DeleteOperationRequest, {} | null | undefined>
The function which will be called with the result of the API call. {Promise} - The promise which resolves when API call finishes. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
Promise<protos.google.protobuf.Empty> |
const client = longrunning.operationsClient();
await client.deleteOperation({name: ''});
endpointPath(project, location, endpoint)
endpointPath(project: string, location: string, endpoint: string): string;
Return a fully-qualified endpoint resource name string.
Name | Description |
project |
string
|
location |
string
|
endpoint |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
entityType |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
execution |
string
|
Type | Description |
string | {string} Resource name string. |
exportData(request, options)
exportData(request?: protos.google.cloud.aiplatform.v1.IExportDataRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Exports data from a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportDataRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>,
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 |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset resource.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
/**
* Required. The desired output location.
*/
// const exportConfig = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callExportData() {
// Construct request
const request = {
name,
exportConfig,
};
// Run request
const [operation] = await aiplatformClient.exportData(request);
const [response] = await operation.promise();
console.log(response);
}
callExportData();
exportData(request, options, callback)
exportData(request: protos.google.cloud.aiplatform.v1.IExportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportDataRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
exportData(request, callback)
exportData(request: protos.google.cloud.aiplatform.v1.IExportDataRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IExportDataRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IExportDataResponse, protos.google.cloud.aiplatform.v1.IExportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
entityType |
string
|
feature |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
featurestore |
string
|
Type | Description |
string | {string} Resource name string. |
getAnnotationSpec(request, options)
getAnnotationSpec(request?: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IAnnotationSpec,
protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | undefined,
{} | undefined
]>;
Gets an AnnotationSpec.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IAnnotationSpec,
protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [AnnotationSpec]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the AnnotationSpec resource.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}/annotationSpecs/{annotation_spec}`
*/
// const name = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callGetAnnotationSpec() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getAnnotationSpec(request);
console.log(response);
}
callGetAnnotationSpec();
getAnnotationSpec(request, options, callback)
getAnnotationSpec(request: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getAnnotationSpec(request, callback)
getAnnotationSpec(request: protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAnnotationSpec, protos.google.cloud.aiplatform.v1.IGetAnnotationSpecRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getDataset(request, options)
getDataset(request?: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IDataset,
protos.google.cloud.aiplatform.v1.IGetDatasetRequest | undefined,
{} | undefined
]>;
Gets a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetDatasetRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IDataset,
protos.google.cloud.aiplatform.v1.IGetDatasetRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Dataset]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset resource.
*/
// const name = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callGetDataset() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getDataset(request);
console.log(response);
}
callGetDataset();
getDataset(request, options, callback)
getDataset(request: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetDatasetRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getDataset(request, callback)
getDataset(request: protos.google.cloud.aiplatform.v1.IGetDatasetRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetDatasetRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IGetDatasetRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getIamPolicy(request, options, callback)
getIamPolicy(request: IamProtos.google.iam.v1.GetIamPolicyRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.Policy>;
Gets the access control policy for a resource. Returns an empty policy if the resource exists and does not have a policy set.
Name | Description |
request |
IamProtos.google.iam.v1.GetIamPolicyRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details. |
callback |
Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.GetIamPolicyRequest | null | undefined, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [Policy]. |
Type | Description |
Promise<IamProtos.google.iam.v1.Policy> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Policy]. The promise has a method named "cancel" which cancels the ongoing API call. |
getLocation(request, options, callback)
getLocation(request: LocationProtos.google.cloud.location.IGetLocationRequest, options?: gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>, callback?: Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>): Promise<LocationProtos.google.cloud.location.ILocation>;
Gets information about a location.
Name | Description |
request |
LocationProtos.google.cloud.location.IGetLocationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>
Call options. See CallOptions for more details. |
callback |
Callback<LocationProtos.google.cloud.location.ILocation, LocationProtos.google.cloud.location.IGetLocationRequest | null | undefined, {} | null | undefined>
|
Type | Description |
Promise<LocationProtos.google.cloud.location.ILocation> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Location]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
const [response] = await client.getLocation(request);
getOperation(request, options, callback)
getOperation(request: protos.google.longrunning.GetOperationRequest, options?: gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>, callback?: Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>): Promise<[protos.google.longrunning.Operation]>;
Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
Name | Description |
request |
protos.google.longrunning.GetOperationRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
callback |
Callback<protos.google.longrunning.Operation, protos.google.longrunning.GetOperationRequest, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [google.longrunning.Operation]. {Promise} - The promise which resolves to an array. The first element of the array is an object representing [google.longrunning.Operation]. The promise has a method named "cancel" which cancels the ongoing API call. |
Type | Description |
Promise<[protos.google.longrunning.Operation]> |
const client = longrunning.operationsClient();
const name = '';
const [response] = await client.getOperation({name});
// doThingsWith(response)
getProjectId()
getProjectId(): Promise<string>;
Type | Description |
Promise<string> |
getProjectId(callback)
getProjectId(callback: Callback<string, undefined, undefined>): void;
Name | Description |
callback |
Callback<string, undefined, undefined>
|
Type | Description |
void |
hyperparameterTuningJobPath(project, location, hyperparameterTuningJob)
hyperparameterTuningJobPath(project: string, location: string, hyperparameterTuningJob: string): string;
Return a fully-qualified hyperparameterTuningJob resource name string.
Name | Description |
project |
string
|
location |
string
|
hyperparameterTuningJob |
string
|
Type | Description |
string | {string} Resource name string. |
importData(request, options)
importData(request?: protos.google.cloud.aiplatform.v1.IImportDataRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Imports data into a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportDataRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>,
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 |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset resource.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const name = 'abc123'
/**
* Required. The desired input locations. The contents of all input locations
* will be imported in one batch.
*/
// const importConfigs = 1234
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callImportData() {
// Construct request
const request = {
name,
importConfigs,
};
// Run request
const [operation] = await aiplatformClient.importData(request);
const [response] = await operation.promise();
console.log(response);
}
callImportData();
importData(request, options, callback)
importData(request: protos.google.cloud.aiplatform.v1.IImportDataRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportDataRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
importData(request, callback)
importData(request: protos.google.cloud.aiplatform.v1.IImportDataRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IImportDataRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IImportDataResponse, protos.google.cloud.aiplatform.v1.IImportDataOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
indexEndpointPath(project, location, indexEndpoint)
indexEndpointPath(project: string, location: string, indexEndpoint: string): string;
Return a fully-qualified indexEndpoint resource name string.
Name | Description |
project |
string
|
location |
string
|
indexEndpoint |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
index |
string
|
Type | Description |
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.
Type | Description |
Promise<{
[name: string]: Function;
}> | {Promise} A promise that resolves to an authenticated service stub. |
listAnnotations(request, options)
listAnnotations(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IAnnotation[],
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest | null,
protos.google.cloud.aiplatform.v1.IListAnnotationsResponse
]>;
Lists Annotations belongs to a dataitem
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IAnnotation[],
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest | null,
protos.google.cloud.aiplatform.v1.IListAnnotationsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Annotation]. 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 |
listAnnotations(request, options, callback)
listAnnotations(request: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>
|
Type | Description |
void |
listAnnotations(request, callback)
listAnnotations(request: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, protos.google.cloud.aiplatform.v1.IListAnnotationsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IAnnotation>
|
Type | Description |
void |
listAnnotationsAsync(request, options)
listAnnotationsAsync(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IAnnotation>;
Equivalent to listAnnotations
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IAnnotation> | {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 [Annotation]. 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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the DataItem to list Annotations from.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}/dataItems/{data_item}`
*/
// const parent = 'abc123'
/**
* The standard list filter.
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
*/
// const orderBy = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callListAnnotations() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listAnnotationsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListAnnotations();
listAnnotationsStream(request, options)
listAnnotationsStream(request?: protos.google.cloud.aiplatform.v1.IListAnnotationsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListAnnotationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [Annotation] 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 |
listDataItems(request, options)
listDataItems(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IDataItem[],
protos.google.cloud.aiplatform.v1.IListDataItemsRequest | null,
protos.google.cloud.aiplatform.v1.IListDataItemsResponse
]>;
Lists DataItems in a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IDataItem[],
protos.google.cloud.aiplatform.v1.IListDataItemsRequest | null,
protos.google.cloud.aiplatform.v1.IListDataItemsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [DataItem]. 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 |
listDataItems(request, options, callback)
listDataItems(request: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDataItemsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>
|
Type | Description |
void |
listDataItems(request, callback)
listDataItems(request: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDataItemsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListDataItemsRequest, protos.google.cloud.aiplatform.v1.IListDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItem>
|
Type | Description |
void |
listDataItemsAsync(request, options)
listDataItemsAsync(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDataItem>;
Equivalent to listDataItems
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IDataItem> | {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 [DataItem]. 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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Dataset to list DataItems from.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const parent = 'abc123'
/**
* The standard list filter.
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
*/
// const orderBy = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callListDataItems() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listDataItemsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListDataItems();
listDataItemsStream(request, options)
listDataItemsStream(request?: protos.google.cloud.aiplatform.v1.IListDataItemsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [DataItem] 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 |
listDatasets(request, options)
listDatasets(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IDataset[],
protos.google.cloud.aiplatform.v1.IListDatasetsRequest | null,
protos.google.cloud.aiplatform.v1.IListDatasetsResponse
]>;
Lists Datasets in a Location.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDatasetsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IDataset[],
protos.google.cloud.aiplatform.v1.IListDatasetsRequest | null,
protos.google.cloud.aiplatform.v1.IListDatasetsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Dataset]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listDatasets(request, options, callback)
listDatasets(request: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDatasetsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>
|
Type | Description |
void |
listDatasets(request, callback)
listDatasets(request: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDatasetsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListDatasetsRequest, protos.google.cloud.aiplatform.v1.IListDatasetsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataset>
|
Type | Description |
void |
listDatasetsAsync(request, options)
listDatasetsAsync(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDataset>;
Equivalent to listDatasets
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDatasetsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IDataset> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Dataset]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The name of the Dataset's parent resource.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* An expression for filtering the results of the request. For field names
* both snake_case and camelCase are supported.
* * `display_name`: supports = and !=
* * `metadata_schema_uri`: supports = and !=
* * `labels` supports general map functions that is:
* * `labels.key=value` - key:value equality
* * `labels.key:* or labels:key - key existence
* * A key including a space must be quoted. `labels."a key"`.
* Some examples:
* * `displayName="myDisplayName"`
* * `labels.myKey="myValue"`
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
* Supported fields:
* * `display_name`
* * `create_time`
* * `update_time`
*/
// const orderBy = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callListDatasets() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listDatasetsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListDatasets();
listDatasetsStream(request, options)
listDatasetsStream(request?: protos.google.cloud.aiplatform.v1.IListDatasetsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListDatasetsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [Dataset] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listLocationsAsync(request, options)
listLocationsAsync(request: LocationProtos.google.cloud.location.IListLocationsRequest, options?: CallOptions): AsyncIterable<LocationProtos.google.cloud.location.ILocation>;
Lists information about the supported locations for this service. Returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
LocationProtos.google.cloud.location.IListLocationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<LocationProtos.google.cloud.location.ILocation> | {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 [Location]. 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. |
const iterable = client.listLocationsAsync(request);
for await (const response of iterable) {
// process response
}
listOperationsAsync(request, options)
listOperationsAsync(request: protos.google.longrunning.ListOperationsRequest, options?: gax.CallOptions): AsyncIterable<protos.google.longrunning.ListOperationsResponse>;
Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns UNIMPLEMENTED
. Returns an iterable object.
For-await-of syntax is used with the iterable to recursively get response element on-demand.
Name | Description |
request |
protos.google.longrunning.ListOperationsRequest
The request object that will be sent. |
options |
gax.CallOptions
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/global.html#CallOptions for the details. |
Type | Description |
AsyncIterable<protos.google.longrunning.ListOperationsResponse> | {Object} An iterable Object that conforms to https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols. |
const client = longrunning.operationsClient();
for await (const response of client.listOperationsAsync(request));
// doThingsWith(response)
listSavedQueries(request, options)
listSavedQueries(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.ISavedQuery[],
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest | null,
protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse
]>;
Lists SavedQueries in a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.ISavedQuery[],
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest | null,
protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [SavedQuery]. 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 |
listSavedQueries(request, options, callback)
listSavedQueries(request: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>
|
Type | Description |
void |
listSavedQueries(request, callback)
listSavedQueries(request: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, protos.google.cloud.aiplatform.v1.IListSavedQueriesResponse | null | undefined, protos.google.cloud.aiplatform.v1.ISavedQuery>
|
Type | Description |
void |
listSavedQueriesAsync(request, options)
listSavedQueriesAsync(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.ISavedQuery>;
Equivalent to listSavedQueries
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.ISavedQuery> | {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 [SavedQuery]. 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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Dataset to list SavedQueries from.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const parent = 'abc123'
/**
* The standard list filter.
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
*/
// const orderBy = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callListSavedQueries() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listSavedQueriesAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListSavedQueries();
listSavedQueriesStream(request, options)
listSavedQueriesStream(request?: protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListSavedQueriesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [SavedQuery] 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 |
locationPath(project, location)
locationPath(project: string, location: string): string;
Return a fully-qualified location resource name string.
Name | Description |
project |
string
|
location |
string
|
Type | Description |
string | {string} Resource name string. |
matchAnnotationFromAnnotationName(annotationName)
matchAnnotationFromAnnotationName(annotationName: string): string | number;
Parse the annotation from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the annotation. |
matchAnnotationSpecFromAnnotationSpecName(annotationSpecName)
matchAnnotationSpecFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the annotation_spec from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the annotation_spec. |
matchArtifactFromArtifactName(artifactName)
matchArtifactFromArtifactName(artifactName: string): string | number;
Parse the artifact from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the artifact. |
matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName)
matchBatchPredictionJobFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the batch_prediction_job from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the batch_prediction_job. |
matchContextFromContextName(contextName)
matchContextFromContextName(contextName: string): string | number;
Parse the context from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the context. |
matchCustomJobFromCustomJobName(customJobName)
matchCustomJobFromCustomJobName(customJobName: string): string | number;
Parse the custom_job from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the custom_job. |
matchDataItemFromAnnotationName(annotationName)
matchDataItemFromAnnotationName(annotationName: string): string | number;
Parse the data_item from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the data_item. |
matchDataItemFromDataItemName(dataItemName)
matchDataItemFromDataItemName(dataItemName: string): string | number;
Parse the data_item from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the data_item. |
matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName)
matchDataLabelingJobFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the data_labeling_job from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the data_labeling_job. |
matchDatasetFromAnnotationName(annotationName)
matchDatasetFromAnnotationName(annotationName: string): string | number;
Parse the dataset from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromAnnotationSpecName(annotationSpecName)
matchDatasetFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the dataset from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromDataItemName(dataItemName)
matchDatasetFromDataItemName(dataItemName: string): string | number;
Parse the dataset from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromDatasetName(datasetName)
matchDatasetFromDatasetName(datasetName: string): string | number;
Parse the dataset from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchDatasetFromSavedQueryName(savedQueryName)
matchDatasetFromSavedQueryName(savedQueryName: string): string | number;
Parse the dataset from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the dataset. |
matchEndpointFromEndpointName(endpointName)
matchEndpointFromEndpointName(endpointName: string): string | number;
Parse the endpoint from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the endpoint. |
matchEntityTypeFromEntityTypeName(entityTypeName)
matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;
Parse the entity_type from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEntityTypeFromFeatureName(featureName)
matchEntityTypeFromFeatureName(featureName: string): string | number;
Parse the entity_type from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEvaluationFromModelEvaluationName(modelEvaluationName)
matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the evaluation from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the evaluation from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchExecutionFromExecutionName(executionName)
matchExecutionFromExecutionName(executionName: string): string | number;
Parse the execution from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the execution. |
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the experiment from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardRunName(tensorboardRunName)
matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the experiment from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the experiment from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchFeatureFromFeatureName(featureName)
matchFeatureFromFeatureName(featureName: string): string | number;
Parse the feature from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the feature. |
matchFeaturestoreFromEntityTypeName(entityTypeName)
matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;
Parse the featurestore from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeatureName(featureName)
matchFeaturestoreFromFeatureName(featureName: string): string | number;
Parse the featurestore from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeaturestoreName(featurestoreName)
matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;
Parse the featurestore from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the hyperparameter_tuning_job. |
matchIndexEndpointFromIndexEndpointName(indexEndpointName)
matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the index_endpoint from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the index_endpoint. |
matchIndexFromIndexName(indexName)
matchIndexFromIndexName(indexName: string): string | number;
Parse the index from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the index. |
matchLocationFromAnnotationName(annotationName)
matchLocationFromAnnotationName(annotationName: string): string | number;
Parse the location from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromAnnotationSpecName(annotationSpecName)
matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the location from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromArtifactName(artifactName)
matchLocationFromArtifactName(artifactName: string): string | number;
Parse the location from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromBatchPredictionJobName(batchPredictionJobName)
matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the location from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromContextName(contextName)
matchLocationFromContextName(contextName: string): string | number;
Parse the location from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromCustomJobName(customJobName)
matchLocationFromCustomJobName(customJobName: string): string | number;
Parse the location from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataItemName(dataItemName)
matchLocationFromDataItemName(dataItemName: string): string | number;
Parse the location from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataLabelingJobName(dataLabelingJobName)
matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the location from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDatasetName(datasetName)
matchLocationFromDatasetName(datasetName: string): string | number;
Parse the location from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEndpointName(endpointName)
matchLocationFromEndpointName(endpointName: string): string | number;
Parse the location from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEntityTypeName(entityTypeName)
matchLocationFromEntityTypeName(entityTypeName: string): string | number;
Parse the location from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromExecutionName(executionName)
matchLocationFromExecutionName(executionName: string): string | number;
Parse the location from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeatureName(featureName)
matchLocationFromFeatureName(featureName: string): string | number;
Parse the location from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeaturestoreName(featurestoreName)
matchLocationFromFeaturestoreName(featurestoreName: string): string | number;
Parse the location from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the location from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexEndpointName(indexEndpointName)
matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the location from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexName(indexName)
matchLocationFromIndexName(indexName: string): string | number;
Parse the location from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromLocationName(locationName)
matchLocationFromLocationName(locationName: string): string | number;
Parse the location from Location resource.
Name | Description |
locationName |
string
A fully-qualified path representing Location resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataSchemaName(metadataSchemaName)
matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the location from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataStoreName(metadataStoreName)
matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the location from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the location from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationName(modelEvaluationName)
matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the location from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the location from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelName(modelName)
matchLocationFromModelName(modelName: string): string | number;
Parse the location from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromPipelineJobName(pipelineJobName)
matchLocationFromPipelineJobName(pipelineJobName: string): string | number;
Parse the location from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromSavedQueryName(savedQueryName)
matchLocationFromSavedQueryName(savedQueryName: string): string | number;
Parse the location from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromSpecialistPoolName(specialistPoolName)
matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the location from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromStudyName(studyName)
matchLocationFromStudyName(studyName: string): string | number;
Parse the location from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardExperimentName(tensorboardExperimentName)
matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the location from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardName(tensorboardName)
matchLocationFromTensorboardName(tensorboardName: string): string | number;
Parse the location from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardRunName(tensorboardRunName)
matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the location from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the location from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrainingPipelineName(trainingPipelineName)
matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the location from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrialName(trialName)
matchLocationFromTrialName(trialName: string): string | number;
Parse the location from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_schema from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_schema. |
matchMetadataStoreFromArtifactName(artifactName)
matchMetadataStoreFromArtifactName(artifactName: string): string | number;
Parse the metadata_store from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromContextName(contextName)
matchMetadataStoreFromContextName(contextName: string): string | number;
Parse the metadata_store from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromExecutionName(executionName)
matchMetadataStoreFromExecutionName(executionName: string): string | number;
Parse the metadata_store from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_store from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataStoreName(metadataStoreName)
matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the metadata_store from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
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.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the model_deployment_monitoring_job. |
matchModelFromModelEvaluationName(modelEvaluationName)
matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the model from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the model from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelName(modelName)
matchModelFromModelName(modelName: string): string | number;
Parse the model from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchPipelineJobFromPipelineJobName(pipelineJobName)
matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;
Parse the pipeline_job from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the pipeline_job. |
matchProjectFromAnnotationName(annotationName)
matchProjectFromAnnotationName(annotationName: string): string | number;
Parse the project from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromAnnotationSpecName(annotationSpecName)
matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the project from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromArtifactName(artifactName)
matchProjectFromArtifactName(artifactName: string): string | number;
Parse the project from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromBatchPredictionJobName(batchPredictionJobName)
matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the project from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromContextName(contextName)
matchProjectFromContextName(contextName: string): string | number;
Parse the project from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromCustomJobName(customJobName)
matchProjectFromCustomJobName(customJobName: string): string | number;
Parse the project from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataItemName(dataItemName)
matchProjectFromDataItemName(dataItemName: string): string | number;
Parse the project from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataLabelingJobName(dataLabelingJobName)
matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the project from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDatasetName(datasetName)
matchProjectFromDatasetName(datasetName: string): string | number;
Parse the project from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEndpointName(endpointName)
matchProjectFromEndpointName(endpointName: string): string | number;
Parse the project from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEntityTypeName(entityTypeName)
matchProjectFromEntityTypeName(entityTypeName: string): string | number;
Parse the project from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromExecutionName(executionName)
matchProjectFromExecutionName(executionName: string): string | number;
Parse the project from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeatureName(featureName)
matchProjectFromFeatureName(featureName: string): string | number;
Parse the project from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeaturestoreName(featurestoreName)
matchProjectFromFeaturestoreName(featurestoreName: string): string | number;
Parse the project from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the project from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexEndpointName(indexEndpointName)
matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the project from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexName(indexName)
matchProjectFromIndexName(indexName: string): string | number;
Parse the project from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromLocationName(locationName)
matchProjectFromLocationName(locationName: string): string | number;
Parse the project from Location resource.
Name | Description |
locationName |
string
A fully-qualified path representing Location resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromMetadataSchemaName(metadataSchemaName)
matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the project from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromMetadataStoreName(metadataStoreName)
matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the project from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the project from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelEvaluationName(modelEvaluationName)
matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the project from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)
matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the project from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelName(modelName)
matchProjectFromModelName(modelName: string): string | number;
Parse the project from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromPipelineJobName(pipelineJobName)
matchProjectFromPipelineJobName(pipelineJobName: string): string | number;
Parse the project from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromSavedQueryName(savedQueryName)
matchProjectFromSavedQueryName(savedQueryName: string): string | number;
Parse the project from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromSpecialistPoolName(specialistPoolName)
matchProjectFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the project from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromStudyName(studyName)
matchProjectFromStudyName(studyName: string): string | number;
Parse the project from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTensorboardExperimentName(tensorboardExperimentName)
matchProjectFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the project from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTensorboardName(tensorboardName)
matchProjectFromTensorboardName(tensorboardName: string): string | number;
Parse the project from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTensorboardRunName(tensorboardRunName)
matchProjectFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the project from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchProjectFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the project from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTrainingPipelineName(trainingPipelineName)
matchProjectFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the project from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromTrialName(trialName)
matchProjectFromTrialName(trialName: string): string | number;
Parse the project from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchRunFromTensorboardRunName(tensorboardRunName)
matchRunFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the run from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the run. |
matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchRunFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the run from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the run. |
matchSavedQueryFromSavedQueryName(savedQueryName)
matchSavedQueryFromSavedQueryName(savedQueryName: string): string | number;
Parse the saved_query from SavedQuery resource.
Name | Description |
savedQueryName |
string
A fully-qualified path representing SavedQuery resource. |
Type | Description |
string | number | {string} A string representing the saved_query. |
matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)
matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the slice from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the slice. |
matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)
matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the specialist_pool from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the specialist_pool. |
matchStudyFromStudyName(studyName)
matchStudyFromStudyName(studyName: string): string | number;
Parse the study from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the study. |
matchStudyFromTrialName(trialName)
matchStudyFromTrialName(trialName: string): string | number;
Parse the study from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the study. |
matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)
matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the tensorboard from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardName(tensorboardName)
matchTensorboardFromTensorboardName(tensorboardName: string): string | number;
Parse the tensorboard from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardRunName(tensorboardRunName)
matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the tensorboard from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the tensorboard from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the time_series from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the time_series. |
matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)
matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the training_pipeline from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the training_pipeline. |
matchTrialFromTrialName(trialName)
matchTrialFromTrialName(trialName: string): string | number;
Parse the trial from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
metadataSchema |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
modelDeploymentMonitoringJob |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
evaluation |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
evaluation |
string
|
slice |
string
|
Type | Description |
string | {string} Resource name string. |
modelPath(project, location, model)
modelPath(project: string, location: string, model: string): string;
Return a fully-qualified model resource name string.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
pipelineJob |
string
|
Type | Description |
string | {string} Resource name string. |
savedQueryPath(project, location, dataset, savedQuery)
savedQueryPath(project: string, location: string, dataset: string, savedQuery: string): string;
Return a fully-qualified savedQuery resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
savedQuery |
string
|
Type | Description |
string | {string} Resource name string. |
searchDataItems(request, options)
searchDataItems(request?: protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IDataItemView[],
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest | null,
protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse
]>;
Searches DataItems in a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IDataItemView[],
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest | null,
protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [DataItemView]. 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 |
searchDataItems(request, options, callback)
searchDataItems(request: protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItemView>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItemView>
|
Type | Description |
void |
searchDataItems(request, callback)
searchDataItems(request: protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItemView>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, protos.google.cloud.aiplatform.v1.ISearchDataItemsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IDataItemView>
|
Type | Description |
void |
searchDataItemsAsync(request, options)
searchDataItemsAsync(request?: protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IDataItemView>;
Equivalent to searchDataItems
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IDataItemView> | {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 [DataItemView]. 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. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* A comma-separated list of data item fields to order by, sorted in
* ascending order. Use "desc" after a field name for descending.
*/
// const orderByDataItem = 'abc123'
/**
* Expression that allows ranking results based on annotation's property.
*/
// const orderByAnnotation = {}
/**
* Required. The resource name of the Dataset from which to search DataItems.
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}`
*/
// const dataset = 'abc123'
/**
* The resource name of a SavedQuery(annotation set in UI).
* Format:
* `projects/{project}/locations/{location}/datasets/{dataset}/savedQueries/{saved_query}`
* All of the search will be done in the context of this SavedQuery.
*/
// const savedQuery = 'abc123'
/**
* The resource name of a DataLabelingJob.
* Format:
* `projects/{project}/locations/{location}/dataLabelingJobs/{data_labeling_job}`
* If this field is set, all of the search will be done in the context of
* this DataLabelingJob.
*/
// const dataLabelingJob = 'abc123'
/**
* An expression for filtering the DataItem that will be returned.
* * `data_item_id` - for = or !=.
* * `labeled` - for = or !=.
* * `has_annotation(ANNOTATION_SPEC_ID)` - true only for DataItem that
* have at least one annotation with annotation_spec_id =
* `ANNOTATION_SPEC_ID` in the context of SavedQuery or DataLabelingJob.
* For example:
* * `data_item=1`
* * `has_annotation(5)`
*/
// const dataItemFilter = 'abc123'
/**
* An expression for filtering the Annotations that will be returned per
* DataItem.
* * `annotation_spec_id` - for = or !=.
*/
// const annotationsFilter = 'abc123'
/**
* An expression that specifies what Annotations will be returned per
* DataItem. Annotations satisfied either of the conditions will be returned.
* * `annotation_spec_id` - for = or !=.
* Must specify `saved_query_id=` - saved query id that annotations should
* belong to.
*/
// const annotationFilters = 'abc123'
/**
* Mask specifying which fields of
* DataItemView google.cloud.aiplatform.v1.DataItemView to read.
*/
// const fieldMask = {}
/**
* If set, only up to this many of Annotations will be returned per
* DataItemView. The maximum value is 1000. If not set, the maximum value will
* be used.
*/
// const annotationsLimit = 1234
/**
* Requested page size. Server may return fewer results than requested.
* Default and maximum page size is 100.
*/
// const pageSize = 1234
/**
* A comma-separated list of fields to order by, sorted in ascending order.
* Use "desc" after a field name for descending.
*/
// const orderBy = 'abc123'
/**
* A token identifying a page of results for the server to return
* Typically obtained via
* SearchDataItemsResponse.next_page_token google.cloud.aiplatform.v1.SearchDataItemsResponse.next_page_token
* of the previous
* DatasetService.SearchDataItems google.cloud.aiplatform.v1.DatasetService.SearchDataItems
* call.
*/
// const pageToken = 'abc123'
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callSearchDataItems() {
// Construct request
const request = {
dataset,
};
// Run request
const iterable = await aiplatformClient.searchDataItemsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callSearchDataItems();
searchDataItemsStream(request, options)
searchDataItemsStream(request?: protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ISearchDataItemsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Transform | {Stream} An object stream which emits an object representing [DataItemView] 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 |
setIamPolicy(request, options, callback)
setIamPolicy(request: IamProtos.google.iam.v1.SetIamPolicyRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.Policy>;
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.
Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Name | Description |
request |
IamProtos.google.iam.v1.SetIamPolicyRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details. |
callback |
Callback<IamProtos.google.iam.v1.Policy, IamProtos.google.iam.v1.SetIamPolicyRequest | null | undefined, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [TestIamPermissionsResponse]. |
Type | Description |
Promise<IamProtos.google.iam.v1.Policy> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [TestIamPermissionsResponse]. The promise has a method named "cancel" which cancels the ongoing API call. |
specialistPoolPath(project, location, specialistPool)
specialistPoolPath(project: string, location: string, specialistPool: string): string;
Return a fully-qualified specialistPool resource name string.
Name | Description |
project |
string
|
location |
string
|
specialistPool |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
study |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
run |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
run |
string
|
timeSeries |
string
|
Type | Description |
string | {string} Resource name string. |
testIamPermissions(request, options, callback)
testIamPermissions(request: IamProtos.google.iam.v1.TestIamPermissionsRequest, options?: gax.CallOptions | Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>, callback?: Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>): Promise<IamProtos.google.iam.v1.TestIamPermissionsResponse>;
Returns permissions that a caller has on the specified resource. If the resource does not exist, this will return an empty set of permissions, not a NOT_FOUND error.
Note: This operation is designed to be used for building permission-aware UIs and command-line tools, not for authorization checking. This operation may "fail open" without warning.
Name | Description |
request |
IamProtos.google.iam.v1.TestIamPermissionsRequest
The request object that will be sent. |
options |
gax.CallOptions | Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>
Optional parameters. You can override the default settings for this call, e.g, timeout, retries, paginations, etc. See [gax.CallOptions]https://googleapis.github.io/gax-nodejs/interfaces/CallOptions.html for the details. |
callback |
Callback<IamProtos.google.iam.v1.TestIamPermissionsResponse, IamProtos.google.iam.v1.TestIamPermissionsRequest | null | undefined, {} | null | undefined>
The function which will be called with the result of the API call. The second parameter to the callback is an object representing [TestIamPermissionsResponse]. |
Type | Description |
Promise<IamProtos.google.iam.v1.TestIamPermissionsResponse> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [TestIamPermissionsResponse]. The promise has a method named "cancel" which cancels the ongoing API call. |
trainingPipelinePath(project, location, trainingPipeline)
trainingPipelinePath(project: string, location: string, trainingPipeline: string): string;
Return a fully-qualified trainingPipeline resource name string.
Name | Description |
project |
string
|
location |
string
|
trainingPipeline |
string
|
Type | Description |
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.
Name | Description |
project |
string
|
location |
string
|
study |
string
|
trial |
string
|
Type | Description |
string | {string} Resource name string. |
updateDataset(request, options)
updateDataset(request?: protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IDataset,
protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | undefined,
{} | undefined
]>;
Updates a Dataset.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1.IDataset,
protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Dataset]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* This snippet has been automatically generated and should be regarded as a code template only.
* It will require modifications to work.
* It may require correct/in-range values for request initialization.
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The Dataset which replaces the resource on the server.
*/
// const dataset = {}
/**
* Required. The update mask applies to the resource.
* For the `FieldMask` definition, see
* google.protobuf.FieldMask google.protobuf.FieldMask. Updatable fields:
* * `display_name`
* * `description`
* * `labels`
*/
// const updateMask = {}
// Imports the Aiplatform library
const {DatasetServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new DatasetServiceClient();
async function callUpdateDataset() {
// Construct request
const request = {
dataset,
updateMask,
};
// Run request
const response = await aiplatformClient.updateDataset(request);
console.log(response);
}
callUpdateDataset();
updateDataset(request, options, callback)
updateDataset(request: protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateDataset(request, callback)
updateDataset(request: protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IDataset, protos.google.cloud.aiplatform.v1.IUpdateDatasetRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |