A service for managing Vertex AI's machine learning Models. v1beta1
Package
@google-cloud/aiplatformConstructors
(constructor)(opts, gaxInstance)
constructor(opts?: ClientOptions, gaxInstance?: typeof gax | typeof gax.fallback);
Construct an instance of ModelServiceClient.
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;
descriptors
descriptors: Descriptors;
iamClient
iamClient: IamClient;
innerApiCalls
innerApiCalls: {
[name: string]: Function;
};
locationsClient
locationsClient: LocationsClient;
modelServiceStub
modelServiceStub?: Promise<{
[name: string]: Function;
}>;
operationsClient
operationsClient: gax.OperationsClient;
pathTemplates
pathTemplates: {
[name: string]: gax.PathTemplate;
};
port
static get port(): number;
The port for this API service.
scopes
static get scopes(): string[];
The scopes needed to make gRPC calls for every method defined in this service.
servicePath
static get servicePath(): string;
The DNS address for this API service.
warn
warn: (code: string, message: string, warnType?: string) => void;
Methods
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. |
batchImportModelEvaluationSlices(request, options)
batchImportModelEvaluationSlices(request?: protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse,
(protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | undefined),
{} | undefined
]>;
Imports a list of externally generated ModelEvaluationSlice.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse,
(protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | undefined),
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 parent ModelEvaluation resource.
* Format:
* `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`
*/
// const parent = 'abc123'
/**
* Required. Model evaluation slice resource to be imported.
*/
// const modelEvaluationSlices = 1234
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callBatchImportModelEvaluationSlices() {
// Construct request
const request = {
parent,
modelEvaluationSlices,
};
// Run request
const response = await aiplatformClient.batchImportModelEvaluationSlices(request);
console.log(response);
}
callBatchImportModelEvaluationSlices();
batchImportModelEvaluationSlices(request, options, callback)
batchImportModelEvaluationSlices(request: protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
batchImportModelEvaluationSlices(request, callback)
batchImportModelEvaluationSlices(request: protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesResponse, protos.google.cloud.aiplatform.v1beta1.IBatchImportModelEvaluationSlicesRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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 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: ''});
checkCopyModelProgress(name)
checkCopyModelProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.CopyModelResponse, protos.google.cloud.aiplatform.v1beta1.CopyModelOperationMetadata>>;
Check the status of the long running operation returned by copyModel()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.CopyModelResponse, protos.google.cloud.aiplatform.v1beta1.CopyModelOperationMetadata>> | {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.
*/
/**
* Optional. Copy source_model into a new Model with this ID. The ID will
* become the final component of the model resource name.
* This value may be up to 63 characters, and valid characters are
* `[a-z0-9_-]`. The first character cannot be a number or hyphen.
*/
// const modelId = 'abc123'
/**
* Optional. Specify this field to copy source_model into this existing
* Model as a new version. Format:
* `projects/{project}/locations/{location}/models/{model}`
*/
// const parentModel = 'abc123'
/**
* Required. The resource name of the Location into which to copy the Model.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* Required. The resource name of the Model to copy. That Model must be in the
* same Project. Format:
* `projects/{project}/locations/{location}/models/{model}`
*/
// const sourceModel = 'abc123'
/**
* Customer-managed encryption key options. If this is set,
* then the Model copy will be encrypted with the provided encryption key.
*/
// const encryptionSpec = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callCopyModel() {
// Construct request
const request = {
parent,
sourceModel,
};
// Run request
const [operation] = await aiplatformClient.copyModel(request);
const [response] = await operation.promise();
console.log(response);
}
callCopyModel();
checkDeleteModelProgress(name)
checkDeleteModelProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteModel()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.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 name of the Model resource to be deleted.
* Format: `projects/{project}/locations/{location}/models/{model}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callDeleteModel() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteModel(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteModel();
checkDeleteModelVersionProgress(name)
checkDeleteModelVersionProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteModelVersion()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1beta1.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 name of the model version to be deleted, with a version ID
* explicitly included.
* Example: `projects/{project}/locations/{location}/models/{model}@1234`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callDeleteModelVersion() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteModelVersion(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteModelVersion();
checkExportModelProgress(name)
checkExportModelProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.ExportModelResponse, protos.google.cloud.aiplatform.v1beta1.ExportModelOperationMetadata>>;
Check the status of the long running operation returned by exportModel()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.ExportModelResponse, protos.google.cloud.aiplatform.v1beta1.ExportModelOperationMetadata>> | {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 Model to export.
* The resource name may contain version id or version alias to specify the
* version, if no version is specified, the default version will be exported.
*/
// const name = 'abc123'
/**
* Required. The desired output location and configuration.
*/
// const outputConfig = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callExportModel() {
// Construct request
const request = {
name,
outputConfig,
};
// Run request
const [operation] = await aiplatformClient.exportModel(request);
const [response] = await operation.promise();
console.log(response);
}
callExportModel();
checkUpdateExplanationDatasetProgress(name)
checkUpdateExplanationDatasetProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.UpdateExplanationDatasetResponse, protos.google.cloud.aiplatform.v1beta1.UpdateExplanationDatasetOperationMetadata>>;
Check the status of the long running operation returned by updateExplanationDataset()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.UpdateExplanationDatasetResponse, protos.google.cloud.aiplatform.v1beta1.UpdateExplanationDatasetOperationMetadata>> | {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 Model to update.
* Format: `projects/{project}/locations/{location}/models/{model}`
*/
// const model = 'abc123'
/**
* The example config containing the location of the dataset.
*/
// const examples = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callUpdateExplanationDataset() {
// Construct request
const request = {
model,
};
// Run request
const [operation] = await aiplatformClient.updateExplanationDataset(request);
const [response] = await operation.promise();
console.log(response);
}
callUpdateExplanationDataset();
checkUploadModelProgress(name)
checkUploadModelProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.UploadModelResponse, protos.google.cloud.aiplatform.v1beta1.UploadModelOperationMetadata>>;
Check the status of the long running operation returned by uploadModel()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1beta1.UploadModelResponse, protos.google.cloud.aiplatform.v1beta1.UploadModelOperationMetadata>> | {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 into which to upload the Model.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* Optional. The resource name of the model into which to upload the version.
* Only specify this field when uploading a new version.
*/
// const parentModel = 'abc123'
/**
* Optional. The ID to use for the uploaded Model, which will become the final
* component of the model resource name.
* This value may be up to 63 characters, and valid characters are
* `[a-z0-9_-]`. The first character cannot be a number or hyphen.
*/
// const modelId = 'abc123'
/**
* Required. The Model to create.
*/
// const model = {}
/**
* Optional. The user-provided custom service account to use to do the model
* upload. If empty, Vertex AI Service
* Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents)
* will be used. Users uploading the Model must have the
* `iam.serviceAccounts.actAs` permission on this service account. Also, this
* account must belong to the project specified in the `parent` field and have
* all necessary read permissions.
*/
// const serviceAccount = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callUploadModel() {
// Construct request
const request = {
parent,
model,
};
// Run request
const [operation] = await aiplatformClient.uploadModel(request);
const [response] = await operation.promise();
console.log(response);
}
callUploadModel();
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. |
copyModel(request, options)
copyModel(request?: protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Copies an already existing Vertex AI Model into the specified Location. The source Model must exist in the same Project. When copying custom Models, the users themselves are responsible for content to be region-agnostic, as well as making sure that any resources (e.g. files) it depends on remain accessible.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>,
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.
*/
/**
* Optional. Copy source_model into a new Model with this ID. The ID will
* become the final component of the model resource name.
* This value may be up to 63 characters, and valid characters are
* `[a-z0-9_-]`. The first character cannot be a number or hyphen.
*/
// const modelId = 'abc123'
/**
* Optional. Specify this field to copy source_model into this existing
* Model as a new version. Format:
* `projects/{project}/locations/{location}/models/{model}`
*/
// const parentModel = 'abc123'
/**
* Required. The resource name of the Location into which to copy the Model.
* Format: `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* Required. The resource name of the Model to copy. That Model must be in the
* same Project. Format:
* `projects/{project}/locations/{location}/models/{model}`
*/
// const sourceModel = 'abc123'
/**
* Customer-managed encryption key options. If this is set,
* then the Model copy will be encrypted with the provided encryption key.
*/
// const encryptionSpec = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callCopyModel() {
// Construct request
const request = {
parent,
sourceModel,
};
// Run request
const [operation] = await aiplatformClient.copyModel(request);
const [response] = await operation.promise();
console.log(response);
}
callCopyModel();
copyModel(request, options, callback)
copyModel(request: protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
copyModel(request, callback)
copyModel(request: protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.ICopyModelRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.ICopyModelResponse, protos.google.cloud.aiplatform.v1beta1.ICopyModelOperationMetadata>, 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. |
deleteModel(request, options)
deleteModel(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a Model.
A model cannot be deleted if any resource has a based on the model in its field.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest
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.v1beta1.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 name of the Model resource to be deleted.
* Format: `projects/{project}/locations/{location}/models/{model}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callDeleteModel() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteModel(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteModel();
deleteModel(request, options, callback)
deleteModel(request: protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteModel(request, callback)
deleteModel(request: protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteModelVersion(request, options)
deleteModelVersion(request?: protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a Model version.
Model version can only be deleted if there are no created from it. Deleting the only version in the Model is not allowed. Use for deleting the Model instead.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest
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.v1beta1.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 name of the model version to be deleted, with a version ID
* explicitly included.
* Example: `projects/{project}/locations/{location}/models/{model}@1234`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callDeleteModelVersion() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteModelVersion(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteModelVersion();
deleteModelVersion(request, options, callback)
deleteModelVersion(request: protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteModelVersion(request, callback)
deleteModelVersion(request: protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IDeleteModelVersionRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1beta1.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 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: ''});
deploymentResourcePoolPath(project, location, deploymentResourcePool)
deploymentResourcePoolPath(project: string, location: string, deploymentResourcePool: string): string;
Return a fully-qualified deploymentResourcePool resource name string.
Name | Description |
project |
string
|
location |
string
|
deploymentResourcePool |
string
|
Type | Description |
string | {string} Resource name string. |
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. |
exportModel(request, options)
exportModel(request?: protos.google.cloud.aiplatform.v1beta1.IExportModelRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Exports a trained, exportable Model to a location specified by the user. A Model is considered to be exportable if it has at least one [supported export format][google.cloud.aiplatform.v1beta1.Model.supported_export_formats].
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IExportModelRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>,
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 Model to export.
* The resource name may contain version id or version alias to specify the
* version, if no version is specified, the default version will be exported.
*/
// const name = 'abc123'
/**
* Required. The desired output location and configuration.
*/
// const outputConfig = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callExportModel() {
// Construct request
const request = {
name,
outputConfig,
};
// Run request
const [operation] = await aiplatformClient.exportModel(request);
const [response] = await operation.promise();
console.log(response);
}
callExportModel();
exportModel(request, options, callback)
exportModel(request: protos.google.cloud.aiplatform.v1beta1.IExportModelRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IExportModelRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
exportModel(request, callback)
exportModel(request: protos.google.cloud.aiplatform.v1beta1.IExportModelRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IExportModelRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1beta1.IExportModelResponse, protos.google.cloud.aiplatform.v1beta1.IExportModelOperationMetadata>, 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. |
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 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 . |
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 . 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 . 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);
getModel(request, options)
getModel(request?: protos.google.cloud.aiplatform.v1beta1.IGetModelRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel,
protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | undefined,
{} | undefined
]>;
Gets a Model.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel,
protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | undefined,
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 Model resource.
* Format: `projects/{project}/locations/{location}/models/{model}`
* In order to retrieve a specific version of the model, also provide
* the version ID or version alias.
* Example: `projects/{project}/locations/{location}/models/{model}@2`
* or
* `projects/{project}/locations/{location}/models/{model}@golden`
* If no version ID or alias is specified, the "default" version will be
* returned. The "default" version alias is created for the first version of
* the model, and can be moved to other versions later on. There will be
* exactly one default version.
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callGetModel() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getModel(request);
console.log(response);
}
callGetModel();
getModel(request, options, callback)
getModel(request: protos.google.cloud.aiplatform.v1beta1.IGetModelRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getModel(request, callback)
getModel(request: protos.google.cloud.aiplatform.v1beta1.IGetModelRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IGetModelRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getModelEvaluation(request, options)
getModelEvaluation(request?: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation,
(protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | undefined),
{} | undefined
]>;
Gets a ModelEvaluation.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation,
(protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | undefined),
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 ModelEvaluation resource.
* Format:
* `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callGetModelEvaluation() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getModelEvaluation(request);
console.log(response);
}
callGetModelEvaluation();
getModelEvaluation(request, options, callback)
getModelEvaluation(request: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getModelEvaluation(request, callback)
getModelEvaluation(request: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getModelEvaluationSlice(request, options)
getModelEvaluationSlice(request?: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice,
(protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | undefined),
{} | undefined
]>;
Gets a ModelEvaluationSlice.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice,
(protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | undefined),
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 ModelEvaluationSlice resource.
* Format:
* `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}/slices/{slice}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callGetModelEvaluationSlice() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getModelEvaluationSlice(request);
console.log(response);
}
callGetModelEvaluationSlice();
getModelEvaluationSlice(request, options, callback)
getModelEvaluationSlice(request: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getModelEvaluationSlice(request, callback)
getModelEvaluationSlice(request: protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice, protos.google.cloud.aiplatform.v1beta1.IGetModelEvaluationSliceRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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 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 . {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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. |
importModelEvaluation(request, options)
importModelEvaluation(request?: protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation,
(protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | undefined),
{} | undefined
]>;
Imports an externally generated ModelEvaluation.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation,
(protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | undefined),
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 parent model resource.
* Format: `projects/{project}/locations/{location}/models/{model}`
*/
// const parent = 'abc123'
/**
* Required. Model evaluation resource to be imported.
*/
// const modelEvaluation = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callImportModelEvaluation() {
// Construct request
const request = {
parent,
modelEvaluation,
};
// Run request
const response = await aiplatformClient.importModelEvaluation(request);
console.log(response);
}
callImportModelEvaluation();
importModelEvaluation(request, options, callback)
importModelEvaluation(request: protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
importModelEvaluation(request, callback)
importModelEvaluation(request: protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation, protos.google.cloud.aiplatform.v1beta1.IImportModelEvaluationRequest | 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. |
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 . 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
}
listModelEvaluations(request, options)
listModelEvaluations(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation[],
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse
]>;
Lists ModelEvaluations in a Model.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluation[],
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of . 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 |
listModelEvaluations(request, options, callback)
listModelEvaluations(request: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluation>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluation>
|
Type | Description |
void |
listModelEvaluations(request, callback)
listModelEvaluations(request: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluation>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluation>
|
Type | Description |
void |
listModelEvaluationsAsync(request, options)
listModelEvaluationsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation>;
Equivalent to listModelEvaluations
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModelEvaluation> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing . 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 Model to list the ModelEvaluations from.
* Format: `projects/{project}/locations/{location}/models/{model}`
*/
// const parent = 'abc123'
/**
* The standard list filter.
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
* Typically obtained via
* ListModelEvaluationsResponse.next_page_token google.cloud.aiplatform.v1beta1.ListModelEvaluationsResponse.next_page_token
* of the previous
* ModelService.ListModelEvaluations google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluations
* call.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callListModelEvaluations() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listModelEvaluationsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListModelEvaluations();
listModelEvaluationSlices(request, options)
listModelEvaluationSlices(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice[],
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse
]>;
Lists ModelEvaluationSlices in a ModelEvaluation.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice[],
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of . 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 |
listModelEvaluationSlices(request, options, callback)
listModelEvaluationSlices(request: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice>
|
Type | Description |
void |
listModelEvaluationSlices(request, callback)
listModelEvaluationSlices(request: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice>
|
Type | Description |
void |
listModelEvaluationSlicesAsync(request, options)
listModelEvaluationSlicesAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice>;
Equivalent to listModelEvaluationSlices
, 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.v1beta1.IListModelEvaluationSlicesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModelEvaluationSlice> | {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 . 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 ModelEvaluation to list the
* ModelEvaluationSlices from. Format:
* `projects/{project}/locations/{location}/models/{model}/evaluations/{evaluation}`
*/
// const parent = 'abc123'
/**
* The standard list filter.
* * `slice.dimension` - for =.
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
* Typically obtained via
* ListModelEvaluationSlicesResponse.next_page_token google.cloud.aiplatform.v1beta1.ListModelEvaluationSlicesResponse.next_page_token
* of the previous
* ModelService.ListModelEvaluationSlices google.cloud.aiplatform.v1beta1.ModelService.ListModelEvaluationSlices
* call.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callListModelEvaluationSlices() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listModelEvaluationSlicesAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListModelEvaluationSlices();
listModelEvaluationSlicesStream(request, options)
listModelEvaluationSlicesStream(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationSlicesRequest
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 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 |
listModelEvaluationsStream(request, options)
listModelEvaluationsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelEvaluationsRequest
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 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 |
listModels(request, options)
listModels(request?: protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel[],
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelsResponse
]>;
Lists Models in a Location.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel[],
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of . 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 |
listModels(request, options, callback)
listModels(request: protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>
|
Type | Description |
void |
listModels(request, callback)
listModels(request: protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>
|
Type | Description |
void |
listModelsAsync(request, options)
listModelsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModel>;
Equivalent to listModels
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModel> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing . 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 Location to list the Models from.
* 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.
* * `model` supports = and !=. `model` represents the Model ID,
* i.e. the last segment of the Model's resource
* name google.cloud.aiplatform.v1beta1.Model.name.
* * `display_name` 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:
* * `model=1234`
* * `displayName="myDisplayName"`
* * `labels.myKey="myValue"`
*/
// const filter = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
* Typically obtained via
* ListModelsResponse.next_page_token google.cloud.aiplatform.v1beta1.ListModelsResponse.next_page_token
* of the previous
* ModelService.ListModels google.cloud.aiplatform.v1beta1.ModelService.ListModels
* call.
*/
// const pageToken = 'abc123'
/**
* Mask specifying which fields to read.
*/
// const readMask = {}
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callListModels() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listModelsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListModels();
listModelsStream(request, options)
listModelsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListModelsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelsRequest
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 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 |
listModelVersions(request, options)
listModelVersions(request?: protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel[],
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse
]>;
Lists versions of the specified model.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel[],
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest | null,
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse
]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of . 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 |
listModelVersions(request, options, callback)
listModelVersions(request: protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>
|
Type | Description |
void |
listModelVersions(request, callback)
listModelVersions(request: protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, protos.google.cloud.aiplatform.v1beta1.IListModelVersionsResponse | null | undefined, protos.google.cloud.aiplatform.v1beta1.IModel>
|
Type | Description |
void |
listModelVersionsAsync(request, options)
listModelVersionsAsync(request?: protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModel>;
Equivalent to listModelVersions
, 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.v1beta1.IListModelVersionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1beta1.IModel> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing . 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 model to list versions for.
*/
// const name = 'abc123'
/**
* The standard list page size.
*/
// const pageSize = 1234
/**
* The standard list page token.
* Typically obtained via
* ListModelVersionsResponse.next_page_token google.cloud.aiplatform.v1beta1.ListModelVersionsResponse.next_page_token
* of the previous ModelService.ListModelversions call.
*/
// const pageToken = 'abc123'
/**
* An expression for filtering the results of the request. For field names
* both snake_case and camelCase are supported.
* * `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:
* * `labels.myKey="myValue"`
*/
// const filter = '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:
* * `create_time`
* * `update_time`
* Example: `update_time asc, create_time desc`.
*/
// const orderBy = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callListModelVersions() {
// Construct request
const request = {
name,
};
// Run request
const iterable = await aiplatformClient.listModelVersionsAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListModelVersions();
listModelVersionsStream(request, options)
listModelVersionsStream(request?: protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IListModelVersionsRequest
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 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 |
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 for the details. |
Type | Description |
AsyncIterable<protos.google.longrunning.ListOperationsResponse> | {Object} An iterable Object that conforms to iteration protocols. |
const client = longrunning.operationsClient();
for await (const response of client.listOperationsAsync(request));
// doThingsWith(response)
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. |
matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName)
matchDeploymentResourcePoolFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;
Parse the deployment_resource_pool from DeploymentResourcePool resource.
Name | Description |
deploymentResourcePoolName |
string
A fully-qualified path representing DeploymentResourcePool resource. |
Type | Description |
string | number | {string} A string representing the deployment_resource_pool. |
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. |
matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName)
matchLocationFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;
Parse the location from DeploymentResourcePool resource.
Name | Description |
deploymentResourcePoolName |
string
A fully-qualified path representing DeploymentResourcePool 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. |
matchLocationFromNasJobName(nasJobName)
matchLocationFromNasJobName(nasJobName: string): string | number;
Parse the location from NasJob resource.
Name | Description |
nasJobName |
string
A fully-qualified path representing NasJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromNasTrialDetailName(nasTrialDetailName)
matchLocationFromNasTrialDetailName(nasTrialDetailName: string): string | number;
Parse the location from NasTrialDetail resource.
Name | Description |
nasTrialDetailName |
string
A fully-qualified path representing NasTrialDetail 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. |
matchNasJobFromNasJobName(nasJobName)
matchNasJobFromNasJobName(nasJobName: string): string | number;
Parse the nas_job from NasJob resource.
Name | Description |
nasJobName |
string
A fully-qualified path representing NasJob resource. |
Type | Description |
string | number | {string} A string representing the nas_job. |
matchNasJobFromNasTrialDetailName(nasTrialDetailName)
matchNasJobFromNasTrialDetailName(nasTrialDetailName: string): string | number;
Parse the nas_job from NasTrialDetail resource.
Name | Description |
nasTrialDetailName |
string
A fully-qualified path representing NasTrialDetail resource. |
Type | Description |
string | number | {string} A string representing the nas_job. |
matchNasTrialDetailFromNasTrialDetailName(nasTrialDetailName)
matchNasTrialDetailFromNasTrialDetailName(nasTrialDetailName: string): string | number;
Parse the nas_trial_detail from NasTrialDetail resource.
Name | Description |
nasTrialDetailName |
string
A fully-qualified path representing NasTrialDetail resource. |
Type | Description |
string | number | {string} A string representing the nas_trial_detail. |
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. |
matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName)
matchProjectFromDeploymentResourcePoolName(deploymentResourcePoolName: string): string | number;
Parse the project from DeploymentResourcePool resource.
Name | Description |
deploymentResourcePoolName |
string
A fully-qualified path representing DeploymentResourcePool 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. |
matchProjectFromNasJobName(nasJobName)
matchProjectFromNasJobName(nasJobName: string): string | number;
Parse the project from NasJob resource.
Name | Description |
nasJobName |
string
A fully-qualified path representing NasJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromNasTrialDetailName(nasTrialDetailName)
matchProjectFromNasTrialDetailName(nasTrialDetailName: string): string | number;
Parse the project from NasTrialDetail resource.
Name | Description |
nasTrialDetailName |
string
A fully-qualified path representing NasTrialDetail 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. |
mergeVersionAliases(request, options)
mergeVersionAliases(request?: protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel,
(protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | undefined),
{} | undefined
]>;
Merges a set of aliases for a Model version.
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[
protos.google.cloud.aiplatform.v1beta1.IModel,
(protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | undefined),
{} | undefined
]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing . 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 model version to merge aliases, with a version ID
* explicitly included.
* Example: `projects/{project}/locations/{location}/models/{model}@1234`
*/
// const name = 'abc123'
/**
* Required. The set of version aliases to merge.
* The alias should be at most 128 characters, and match
* `[a-z][a-zA-Z0-9-]{0,126}[a-z-0-9]`.
* Add the `-` prefix to an alias means removing that alias from the version.
* `-` is NOT counted in the 128 characters. Example: `-golden` means removing
* the `golden` alias from the version.
* There is NO ordering in aliases, which means
* 1) The aliases returned from GetModel API might not have the exactly same
* order from this MergeVersionAliases API. 2) Adding and deleting the same
* alias in the request is not recommended, and the 2 operations will be
* cancelled out.
*/
// const versionAliases = 'abc123'
// Imports the Aiplatform library
const {ModelServiceClient} = require('@google-cloud/aiplatform').v1beta1;
// Instantiates a client
const aiplatformClient = new ModelServiceClient();
async function callMergeVersionAliases() {
// Construct request
const request = {
name,
versionAliases,
};
// Run request
const response = await aiplatformClient.mergeVersionAliases(request);
console.log(response);
}
callMergeVersionAliases();
mergeVersionAliases(request, options, callback)
mergeVersionAliases(request: protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
mergeVersionAliases(request, callback)
mergeVersionAliases(request: protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest, callback: Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1beta1.IModel, protos.google.cloud.aiplatform.v1beta1.IMergeVersionAliasesRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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. |
nasJobPath(project, location, nasJob)
nasJobPath(project: string, location: string, nasJob: string): string;
Return a fully-qualified nasJob resource name string.
Name | Description |
project |
string
|
location |
string
|
nasJob |
string
|
Type | Description |
string | {string} Resource name string. |
nasTrialDetailPath(project, location, nasJob, nasTrialDetail)
nasTrialDetailPath(project: string, location: string, nasJob: string, nasTrialDetail: string): string;
Return a fully-qualified nasTrialDetail resource name string.
Name | Description |
project |
string
|
location |
string
|
nasJob |
string
|
nasTrialDetail |
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. |