Service for reading and writing metadata entries. v1
Package
@google-cloud/aiplatformConstructors
(constructor)(opts)
constructor(opts?: ClientOptions);
Construct an instance of MetadataServiceClient.
Name | Description |
opts |
ClientOptions
|
Properties
apiEndpoint
static get apiEndpoint(): string;
The DNS address for this API service - same as servicePath(), exists for compatibility reasons.
auth
auth: gax.GoogleAuth;
descriptors
descriptors: Descriptors;
innerApiCalls
innerApiCalls: {
[name: string]: Function;
};
metadataServiceStub
metadataServiceStub?: Promise<{
[name: string]: Function;
}>;
operationsClient
operationsClient: gax.OperationsClient;
pathTemplates
pathTemplates: {
[name: string]: gax.PathTemplate;
};
port
static get port(): number;
The port for this API service.
scopes
static get scopes(): string[];
The scopes needed to make gRPC calls for every method defined in this service.
servicePath
static get servicePath(): string;
The DNS address for this API service.
warn
warn: (code: string, message: string, warnType?: string) => void;
Methods
addContextArtifactsAndExecutions(request, options)
addContextArtifactsAndExecutions(request?: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse,
(protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | undefined),
{} | undefined
]>;
Adds a set of Artifacts and Executions to a Context. If any of the Artifacts or Executions have already been added to a Context, they are simply skipped.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, (protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | undefined), {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddContextArtifactsAndExecutionsResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Context that the Artifacts and Executions
* belong to.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const context = 'abc123'
/**
* The resource names of the Artifacts to attribute to the Context.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
*/
// const artifacts = 'abc123'
/**
* The resource names of the Executions to associate with the
* Context.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const executions = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callAddContextArtifactsAndExecutions() {
// Construct request
const request = {
context,
};
// Run request
const response = await aiplatformClient.addContextArtifactsAndExecutions(request);
console.log(response);
}
callAddContextArtifactsAndExecutions();
addContextArtifactsAndExecutions(request, options, callback)
addContextArtifactsAndExecutions(request: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
addContextArtifactsAndExecutions(request, callback)
addContextArtifactsAndExecutions(request: protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsResponse, protos.google.cloud.aiplatform.v1.IAddContextArtifactsAndExecutionsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
addContextChildren(request, options)
addContextChildren(request?: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse,
protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | undefined,
{} | undefined
]>;
Adds a set of Contexts as children to a parent Context. If any of the child Contexts have already been added to the parent Context, they are simply skipped. If this call would create a cycle or cause any Context to have more than 10 parents, the request will fail with an INVALID_ARGUMENT error.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddContextChildrenResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the parent Context.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const context = 'abc123'
/**
* The resource names of the child Contexts.
*/
// const childContexts = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callAddContextChildren() {
// Construct request
const request = {
context,
};
// Run request
const response = await aiplatformClient.addContextChildren(request);
console.log(response);
}
callAddContextChildren();
addContextChildren(request, options, callback)
addContextChildren(request: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
addContextChildren(request, callback)
addContextChildren(request: protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddContextChildrenResponse, protos.google.cloud.aiplatform.v1.IAddContextChildrenRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
addExecutionEvents(request, options)
addExecutionEvents(request?: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse,
protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | undefined,
{} | undefined
]>;
Adds Events to the specified Execution. An Event indicates whether an Artifact was used as an input or output for an Execution. If an Event already exists between the Execution and the Artifact, the Event is skipped.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [AddExecutionEventsResponse]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Execution that the Events connect
* Artifacts with.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const execution = 'abc123'
/**
* The Events to create and add.
*/
// const events = 1234
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callAddExecutionEvents() {
// Construct request
const request = {
execution,
};
// Run request
const response = await aiplatformClient.addExecutionEvents(request);
console.log(response);
}
callAddExecutionEvents();
addExecutionEvents(request, options, callback)
addExecutionEvents(request: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
addExecutionEvents(request, callback)
addExecutionEvents(request: protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IAddExecutionEventsResponse, protos.google.cloud.aiplatform.v1.IAddExecutionEventsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
annotationPath(project, location, dataset, dataItem, annotation)
annotationPath(project: string, location: string, dataset: string, dataItem: string, annotation: string): string;
Return a fully-qualified annotation resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
dataItem |
string
|
annotation |
string
|
Type | Description |
string | {string} Resource name string. |
annotationSpecPath(project, location, dataset, annotationSpec)
annotationSpecPath(project: string, location: string, dataset: string, annotationSpec: string): string;
Return a fully-qualified annotationSpec resource name string.
Name | Description |
project |
string
|
location |
string
|
dataset |
string
|
annotationSpec |
string
|
Type | Description |
string | {string} Resource name string. |
artifactPath(project, location, metadataStore, artifact)
artifactPath(project: string, location: string, metadataStore: string, artifact: string): string;
Return a fully-qualified artifact resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
artifact |
string
|
Type | Description |
string | {string} Resource name string. |
batchPredictionJobPath(project, location, batchPredictionJob)
batchPredictionJobPath(project: string, location: string, batchPredictionJob: string): string;
Return a fully-qualified batchPredictionJob resource name string.
Name | Description |
project |
string
|
location |
string
|
batchPredictionJob |
string
|
Type | Description |
string | {string} Resource name string. |
checkCreateMetadataStoreProgress(name)
checkCreateMetadataStoreProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.MetadataStore, protos.google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata>>;
Check the status of the long running operation returned by createMetadataStore()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.MetadataStore, protos.google.cloud.aiplatform.v1.CreateMetadataStoreOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Location where the MetadataStore should
* be created.
* Format: `projects/{project}/locations/{location}/`
*/
// const parent = 'abc123'
/**
* Required. The MetadataStore to create.
*/
// const metadataStore = {}
/**
* The {metadatastore} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
* If not provided, the MetadataStore's ID will be a UUID generated by the
* service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all MetadataStores in the parent Location.
* (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
* if the caller can't view the preexisting MetadataStore.)
*/
// const metadataStoreId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateMetadataStore() {
// Construct request
const request = {
parent,
metadataStore,
};
// Run request
const [operation] = await aiplatformClient.createMetadataStore(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateMetadataStore();
checkDeleteArtifactProgress(name)
checkDeleteArtifactProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteArtifact()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Artifact to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
*/
// const name = 'abc123'
/**
* Optional. The etag of the Artifact to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteArtifact() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteArtifact(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteArtifact();
checkDeleteContextProgress(name)
checkDeleteContextProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteContext()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Context to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const name = 'abc123'
/**
* The force deletion semantics is still undefined.
* Users should not use this field.
*/
// const force = true
/**
* Optional. The etag of the Context to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteContext() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteContext(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteContext();
checkDeleteExecutionProgress(name)
checkDeleteExecutionProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>>;
Check the status of the long running operation returned by deleteExecution()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Execution to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const name = 'abc123'
/**
* Optional. The etag of the Execution to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteExecution() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteExecution(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteExecution();
checkDeleteMetadataStoreProgress(name)
checkDeleteMetadataStoreProgress(name: string): Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata>>;
Check the status of the long running operation returned by deleteMetadataStore()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.protobuf.Empty, protos.google.cloud.aiplatform.v1.DeleteMetadataStoreOperationMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteMetadataStore() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteMetadataStore(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteMetadataStore();
checkPurgeArtifactsProgress(name)
checkPurgeArtifactsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.PurgeArtifactsMetadata>>;
Check the status of the long running operation returned by purgeArtifacts()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.PurgeArtifactsMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Artifacts from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Artifacts to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" artifact="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeartifacts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeartifacts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeartifacts();="">
checkPurgeContextsProgress(name)
checkPurgeContextsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeContextsResponse, protos.google.cloud.aiplatform.v1.PurgeContextsMetadata>>;
Check the status of the long running operation returned by purgeContexts()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeContextsResponse, protos.google.cloud.aiplatform.v1.PurgeContextsMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Contexts from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Contexts to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" context="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgecontexts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgecontexts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgecontexts();="">
checkPurgeExecutionsProgress(name)
checkPurgeExecutionsProgress(name: string): Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.PurgeExecutionsMetadata>>;
Check the status of the long running operation returned by purgeExecutions()
.
Name | Description |
name |
string
The operation name that will be passed. |
Type | Description |
Promise<LROperation<protos.google.cloud.aiplatform.v1.PurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.PurgeExecutionsMetadata>> | {Promise} - The promise which resolves to an object. The decoded operation object has result and metadata field to get information from. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#long-running-operations) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Executions from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Executions to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" execution="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeexecutions()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeexecutions(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeexecutions();="">
close()
close(): Promise<void>;
Terminate the gRPC channel and close the client.
The client will no longer be usable and all future behavior is undefined.
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. |
createArtifact(request, options)
createArtifact(request?: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IArtifact,
protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | undefined,
{} | undefined
]>;
Creates an Artifact associated with a MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateArtifactRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore where the Artifact should
* be created.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. The Artifact to create.
*/
// const artifact = {}
/**
* The {artifact} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
* If not provided, the Artifact's ID will be a UUID generated by the service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all Artifacts in the parent MetadataStore. (Otherwise
* the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the
* caller can't view the preexisting Artifact.)
*/
// const artifactId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateArtifact() {
// Construct request
const request = {
parent,
artifact,
};
// Run request
const response = await aiplatformClient.createArtifact(request);
console.log(response);
}
callCreateArtifact();
createArtifact(request, options, callback)
createArtifact(request: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateArtifactRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createArtifact(request, callback)
createArtifact(request: protos.google.cloud.aiplatform.v1.ICreateArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateArtifactRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.ICreateArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createContext(request, options)
createContext(request?: protos.google.cloud.aiplatform.v1.ICreateContextRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IContext,
protos.google.cloud.aiplatform.v1.ICreateContextRequest | undefined,
{} | undefined
]>;
Creates a Context associated with a MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateContextRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore where the Context should be
* created.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. The Context to create.
*/
// const context = {}
/**
* The {context} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`.
* If not provided, the Context's ID will be a UUID generated by the service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all Contexts in the parent MetadataStore. (Otherwise
* the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED if the
* caller can't view the preexisting Context.)
*/
// const contextId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateContext() {
// Construct request
const request = {
parent,
context,
};
// Run request
const response = await aiplatformClient.createContext(request);
console.log(response);
}
callCreateContext();
createContext(request, options, callback)
createContext(request: protos.google.cloud.aiplatform.v1.ICreateContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateContextRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createContext(request, callback)
createContext(request: protos.google.cloud.aiplatform.v1.ICreateContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateContextRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.ICreateContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createExecution(request, options)
createExecution(request?: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IExecution,
protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | undefined,
{} | undefined
]>;
Creates an Execution associated with a MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateExecutionRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore where the Execution should
* be created.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. The Execution to create.
*/
// const execution = {}
/**
* The {execution} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
* If not provided, the Execution's ID will be a UUID generated by the
* service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all Executions in the parent MetadataStore.
* (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
* if the caller can't view the preexisting Execution.)
*/
// const executionId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateExecution() {
// Construct request
const request = {
parent,
execution,
};
// Run request
const response = await aiplatformClient.createExecution(request);
console.log(response);
}
callCreateExecution();
createExecution(request, options, callback)
createExecution(request: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateExecutionRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createExecution(request, callback)
createExecution(request: protos.google.cloud.aiplatform.v1.ICreateExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateExecutionRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.ICreateExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createMetadataSchema(request, options)
createMetadataSchema(request?: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IMetadataSchema,
(protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | undefined),
{} | undefined
]>;
Creates a MetadataSchema.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema, (protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | undefined), {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataSchema]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore where the MetadataSchema should
* be created.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. The MetadataSchema to create.
*/
// const metadataSchema = {}
/**
* The {metadata_schema} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`
* If not provided, the MetadataStore's ID will be a UUID generated by the
* service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all MetadataSchemas in the parent Location.
* (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
* if the caller can't view the preexisting MetadataSchema.)
*/
// const metadataSchemaId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateMetadataSchema() {
// Construct request
const request = {
parent,
metadataSchema,
};
// Run request
const response = await aiplatformClient.createMetadataSchema(request);
console.log(response);
}
callCreateMetadataSchema();
createMetadataSchema(request, options, callback)
createMetadataSchema(request: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createMetadataSchema(request, callback)
createMetadataSchema(request: protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.ICreateMetadataSchemaRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createMetadataStore(request, options)
createMetadataStore(request?: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Initializes a MetadataStore, including allocation of resources.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Location where the MetadataStore should
* be created.
* Format: `projects/{project}/locations/{location}/`
*/
// const parent = 'abc123'
/**
* Required. The MetadataStore to create.
*/
// const metadataStore = {}
/**
* The {metadatastore} portion of the resource name with the format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
* If not provided, the MetadataStore's ID will be a UUID generated by the
* service.
* Must be 4-128 characters in length. Valid characters are `/[a-z][0-9]-/`.
* Must be unique across all MetadataStores in the parent Location.
* (Otherwise the request will fail with ALREADY_EXISTS, or PERMISSION_DENIED
* if the caller can't view the preexisting MetadataStore.)
*/
// const metadataStoreId = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callCreateMetadataStore() {
// Construct request
const request = {
parent,
metadataStore,
};
// Run request
const [operation] = await aiplatformClient.createMetadataStore(request);
const [response] = await operation.promise();
console.log(response);
}
callCreateMetadataStore();
createMetadataStore(request, options, callback)
createMetadataStore(request: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
createMetadataStore(request, callback)
createMetadataStore(request: protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.ICreateMetadataStoreRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.ICreateMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
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. |
deleteArtifact(request, options)
deleteArtifact(request?: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes an Artifact.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Artifact to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
*/
// const name = 'abc123'
/**
* Optional. The etag of the Artifact to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteArtifact() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteArtifact(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteArtifact();
deleteArtifact(request, options, callback)
deleteArtifact(request: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteArtifact(request, callback)
deleteArtifact(request: protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteArtifactRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteContext(request, options)
deleteContext(request?: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a stored Context.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteContextRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Context to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const name = 'abc123'
/**
* The force deletion semantics is still undefined.
* Users should not use this field.
*/
// const force = true
/**
* Optional. The etag of the Context to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteContext() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteContext(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteContext();
deleteContext(request, options, callback)
deleteContext(request: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteContextRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteContext(request, callback)
deleteContext(request: protos.google.cloud.aiplatform.v1.IDeleteContextRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteContextRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteExecution(request, options)
deleteExecution(request?: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes an Execution.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Execution to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const name = 'abc123'
/**
* Optional. The etag of the Execution to delete.
* If this is provided, it must match the server's etag. Otherwise, the
* request will fail with a FAILED_PRECONDITION.
*/
// const etag = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteExecution() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteExecution(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteExecution();
deleteExecution(request, options, callback)
deleteExecution(request: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteExecution(request, callback)
deleteExecution(request: protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteExecutionRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteMetadataStore(request, options)
deleteMetadataStore(request?: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, options?: CallOptions): Promise<[
LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Deletes a single MetadataStore and all its child resources (Artifacts, Executions, and Contexts).
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore to delete.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callDeleteMetadataStore() {
// Construct request
const request = {
name,
};
// Run request
const [operation] = await aiplatformClient.deleteMetadataStore(request);
const [response] = await operation.promise();
console.log(response);
}
callDeleteMetadataStore();
deleteMetadataStore(request, options, callback)
deleteMetadataStore(request: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, options: CallOptions, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
deleteMetadataStore(request, callback)
deleteMetadataStore(request: protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest, callback: Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreRequest
|
callback |
Callback<LROperation<protos.google.protobuf.IEmpty, protos.google.cloud.aiplatform.v1.IDeleteMetadataStoreOperationMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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. |
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. |
getArtifact(request, options)
getArtifact(request?: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IArtifact,
protos.google.cloud.aiplatform.v1.IGetArtifactRequest | undefined,
{} | undefined
]>;
Retrieves a specific Artifact.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetArtifactRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Artifact to retrieve.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callGetArtifact() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getArtifact(request);
console.log(response);
}
callGetArtifact();
getArtifact(request, options, callback)
getArtifact(request: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetArtifactRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getArtifact(request, callback)
getArtifact(request: protos.google.cloud.aiplatform.v1.IGetArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetArtifactRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IGetArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getContext(request, options)
getContext(request?: protos.google.cloud.aiplatform.v1.IGetContextRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IContext,
protos.google.cloud.aiplatform.v1.IGetContextRequest | undefined,
{} | undefined
]>;
Retrieves a specific Context.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetContextRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Context to retrieve.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callGetContext() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getContext(request);
console.log(response);
}
callGetContext();
getContext(request, options, callback)
getContext(request: protos.google.cloud.aiplatform.v1.IGetContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetContextRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getContext(request, callback)
getContext(request: protos.google.cloud.aiplatform.v1.IGetContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetContextRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IGetContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getExecution(request, options)
getExecution(request?: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IExecution,
protos.google.cloud.aiplatform.v1.IGetExecutionRequest | undefined,
{} | undefined
]>;
Retrieves a specific Execution.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetExecutionRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Execution to retrieve.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callGetExecution() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getExecution(request);
console.log(response);
}
callGetExecution();
getExecution(request, options, callback)
getExecution(request: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetExecutionRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getExecution(request, callback)
getExecution(request: protos.google.cloud.aiplatform.v1.IGetExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetExecutionRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IGetExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getMetadataSchema(request, options)
getMetadataSchema(request?: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IMetadataSchema,
protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | undefined,
{} | undefined
]>;
Retrieves a specific MetadataSchema.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataSchema]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataSchema to retrieve.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/metadataSchemas/{metadataschema}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callGetMetadataSchema() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getMetadataSchema(request);
console.log(response);
}
callGetMetadataSchema();
getMetadataSchema(request, options, callback)
getMetadataSchema(request: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getMetadataSchema(request, callback)
getMetadataSchema(request: protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataSchema, protos.google.cloud.aiplatform.v1.IGetMetadataSchemaRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getMetadataStore(request, options)
getMetadataStore(request?: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IMetadataStore,
protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | undefined,
{} | undefined
]>;
Retrieves a specific MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [MetadataStore]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the MetadataStore to retrieve.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const name = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callGetMetadataStore() {
// Construct request
const request = {
name,
};
// Run request
const response = await aiplatformClient.getMetadataStore(request);
console.log(response);
}
callGetMetadataStore();
getMetadataStore(request, options, callback)
getMetadataStore(request: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
getMetadataStore(request, callback)
getMetadataStore(request: protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IMetadataStore, protos.google.cloud.aiplatform.v1.IGetMetadataStoreRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
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. |
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. |
listArtifacts(request, options)
listArtifacts(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IArtifact[],
protos.google.cloud.aiplatform.v1.IListArtifactsRequest | null,
protos.google.cloud.aiplatform.v1.IListArtifactsResponse
]>;
Lists Artifacts in the MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListArtifactsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact[], protos.google.cloud.aiplatform.v1.IListArtifactsRequest | null, protos.google.cloud.aiplatform.v1.IListArtifactsResponse ]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Artifact]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listArtifacts(request, options, callback)
listArtifacts(request: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListArtifactsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>
|
Type | Description |
void |
listArtifacts(request, callback)
listArtifacts(request: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListArtifactsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListArtifactsRequest, protos.google.cloud.aiplatform.v1.IListArtifactsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IArtifact>
|
Type | Description |
void |
listArtifactsAsync(request, options)
listArtifactsAsync(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IArtifact>;
Equivalent to listArtifacts
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListArtifactsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IArtifact> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Artifact]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The MetadataStore whose Artifacts should be listed.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* The maximum number of Artifacts to return. The service may return fewer.
* Must be in range 1-1000, inclusive. Defaults to 100.
*/
// const pageSize = 1234
/**
* A page token, received from a previous MetadataService.ListArtifacts google.cloud.aiplatform.v1.MetadataService.ListArtifacts
* call. Provide this to retrieve the subsequent page.
* When paginating, all other provided parameters must match the call that
* provided the page token. (Otherwise the request will fail with
* INVALID_ARGUMENT error.)
*/
// const pageToken = 'abc123'
/**
* Filter specifying the boolean condition for the Artifacts to satisfy in
* order to be part of the result set.
* The syntax to define filter query is based on https://google.aip.dev/160.
* The supported set of filters include the following:
* * **Attribute filtering**:
* For example: `display_name = "test"`.
* Supported fields include: `name`, `display_name`, `uri`, `state`,
* `schema_title`, `create_time`, and `update_time`.
* Time fields, such as `create_time` and `update_time`, require values
* specified in RFC-3339 format.
* For example: `create_time = "2020-11-19T11:30:00-04:00"`
* * **Metadata field**:
* To filter on metadata fields use traversal operation as follows:
* `metadata.
listArtifactsStream(request, options)
listArtifactsStream(request?: protos.google.cloud.aiplatform.v1.IListArtifactsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListArtifactsRequest
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 [Artifact] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listContexts(request, options)
listContexts(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IContext[],
protos.google.cloud.aiplatform.v1.IListContextsRequest | null,
protos.google.cloud.aiplatform.v1.IListContextsResponse
]>;
Lists Contexts on the MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListContextsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IContext[], protos.google.cloud.aiplatform.v1.IListContextsRequest | null, protos.google.cloud.aiplatform.v1.IListContextsResponse ]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Context]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listContexts(request, options, callback)
listContexts(request: protos.google.cloud.aiplatform.v1.IListContextsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListContextsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>
|
Type | Description |
void |
listContexts(request, callback)
listContexts(request: protos.google.cloud.aiplatform.v1.IListContextsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListContextsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListContextsRequest, protos.google.cloud.aiplatform.v1.IListContextsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IContext>
|
Type | Description |
void |
listContextsAsync(request, options)
listContextsAsync(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IContext>;
Equivalent to listContexts
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListContextsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IContext> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Context]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The MetadataStore whose Contexts should be listed.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* The maximum number of Contexts to return. The service may return fewer.
* Must be in range 1-1000, inclusive. Defaults to 100.
*/
// const pageSize = 1234
/**
* A page token, received from a previous MetadataService.ListContexts google.cloud.aiplatform.v1.MetadataService.ListContexts
* call. Provide this to retrieve the subsequent page.
* When paginating, all other provided parameters must match the call that
* provided the page token. (Otherwise the request will fail with
* INVALID_ARGUMENT error.)
*/
// const pageToken = 'abc123'
/**
* Filter specifying the boolean condition for the Contexts to satisfy in
* order to be part of the result set.
* The syntax to define filter query is based on https://google.aip.dev/160.
* Following are the supported set of filters:
* * **Attribute filtering**:
* For example: `display_name = "test"`.
* Supported fields include: `name`, `display_name`, `schema_title`,
* `create_time`, and `update_time`.
* Time fields, such as `create_time` and `update_time`, require values
* specified in RFC-3339 format.
* For example: `create_time = "2020-11-19T11:30:00-04:00"`.
* * **Metadata field**:
* To filter on metadata fields use traversal operation as follows:
* `metadata.
listContextsStream(request, options)
listContextsStream(request?: protos.google.cloud.aiplatform.v1.IListContextsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListContextsRequest
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 [Context] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listExecutions(request, options)
listExecutions(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IExecution[],
protos.google.cloud.aiplatform.v1.IListExecutionsRequest | null,
protos.google.cloud.aiplatform.v1.IListExecutionsResponse
]>;
Lists Executions in the MetadataStore.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListExecutionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IExecution[], protos.google.cloud.aiplatform.v1.IListExecutionsRequest | null, protos.google.cloud.aiplatform.v1.IListExecutionsResponse ]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [Execution]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listExecutions(request, options, callback)
listExecutions(request: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListExecutionsRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>
|
Type | Description |
void |
listExecutions(request, callback)
listExecutions(request: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListExecutionsRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListExecutionsRequest, protos.google.cloud.aiplatform.v1.IListExecutionsResponse | null | undefined, protos.google.cloud.aiplatform.v1.IExecution>
|
Type | Description |
void |
listExecutionsAsync(request, options)
listExecutionsAsync(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IExecution>;
Equivalent to listExecutions
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListExecutionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IExecution> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [Execution]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The MetadataStore whose Executions should be listed.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* The maximum number of Executions to return. The service may return fewer.
* Must be in range 1-1000, inclusive. Defaults to 100.
*/
// const pageSize = 1234
/**
* A page token, received from a previous MetadataService.ListExecutions google.cloud.aiplatform.v1.MetadataService.ListExecutions
* call. Provide this to retrieve the subsequent page.
* When paginating, all other provided parameters must match the call that
* provided the page token. (Otherwise the request will fail with an
* INVALID_ARGUMENT error.)
*/
// const pageToken = 'abc123'
/**
* Filter specifying the boolean condition for the Executions to satisfy in
* order to be part of the result set.
* The syntax to define filter query is based on https://google.aip.dev/160.
* Following are the supported set of filters:
* * **Attribute filtering**:
* For example: `display_name = "test"`.
* Supported fields include: `name`, `display_name`, `state`,
* `schema_title`, `create_time`, and `update_time`.
* Time fields, such as `create_time` and `update_time`, require values
* specified in RFC-3339 format.
* For example: `create_time = "2020-11-19T11:30:00-04:00"`.
* * **Metadata field**:
* To filter on metadata fields use traversal operation as follows:
* `metadata.
listExecutionsStream(request, options)
listExecutionsStream(request?: protos.google.cloud.aiplatform.v1.IListExecutionsRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListExecutionsRequest
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 [Execution] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listMetadataSchemas(request, options)
listMetadataSchemas(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IMetadataSchema[],
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest | null,
protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse
]>;
Lists MetadataSchemas.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataSchema[], protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest | null, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse ]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [MetadataSchema]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listMetadataSchemas(request, options, callback)
listMetadataSchemas(request: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>
|
Type | Description |
void |
listMetadataSchemas(request, callback)
listMetadataSchemas(request: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, protos.google.cloud.aiplatform.v1.IListMetadataSchemasResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataSchema>
|
Type | Description |
void |
listMetadataSchemasAsync(request, options)
listMetadataSchemasAsync(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataSchema>;
Equivalent to listMetadataSchemas
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataSchema> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [MetadataSchema]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The MetadataStore whose MetadataSchemas should be listed.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* The maximum number of MetadataSchemas to return. The service may return
* fewer.
* Must be in range 1-1000, inclusive. Defaults to 100.
*/
// const pageSize = 1234
/**
* A page token, received from a previous
* MetadataService.ListMetadataSchemas google.cloud.aiplatform.v1.MetadataService.ListMetadataSchemas call. Provide this to retrieve the
* next page.
* When paginating, all other provided parameters must match the call that
* provided the page token. (Otherwise the request will fail with
* INVALID_ARGUMENT error.)
*/
// const pageToken = 'abc123'
/**
* A query to filter available MetadataSchemas for matching results.
*/
// const filter = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callListMetadataSchemas() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listMetadataSchemasAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListMetadataSchemas();
listMetadataSchemasStream(request, options)
listMetadataSchemasStream(request?: protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataSchemasRequest
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 [MetadataSchema] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
listMetadataStores(request, options)
listMetadataStores(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IMetadataStore[],
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest | null,
protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse
]>;
Lists MetadataStores for a Location.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IMetadataStore[], protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest | null, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse ]> | {Promise} - The promise which resolves to an array. The first element of the array is Array of [MetadataStore]. The client library will perform auto-pagination by default: it will call the API as many times as needed and will merge results from all the pages into this array. Note that it can affect your quota. We recommend using |
listMetadataStores(request, options, callback)
listMetadataStores(request: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options: CallOptions, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
|
options |
CallOptions
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>
|
Type | Description |
void |
listMetadataStores(request, callback)
listMetadataStores(request: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, callback: PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
|
callback |
PaginationCallback<protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, protos.google.cloud.aiplatform.v1.IListMetadataStoresResponse | null | undefined, protos.google.cloud.aiplatform.v1.IMetadataStore>
|
Type | Description |
void |
listMetadataStoresAsync(request, options)
listMetadataStoresAsync(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataStore>;
Equivalent to listMetadataStores
, but returns an iterable object.
for
-await
-of
syntax is used with the iterable to get response elements on-demand.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
AsyncIterable<protos.google.cloud.aiplatform.v1.IMetadataStore> | {Object} An iterable Object that allows [async iteration](https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols). When you iterate the returned iterable, each element will be an object representing [MetadataStore]. The API will be called under the hood as needed, once per the page, so you can stop the iteration when you don't need more results. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#auto-pagination) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The Location whose MetadataStores should be listed.
* Format:
* `projects/{project}/locations/{location}`
*/
// const parent = 'abc123'
/**
* The maximum number of Metadata Stores to return. The service may return
* fewer.
* Must be in range 1-1000, inclusive. Defaults to 100.
*/
// const pageSize = 1234
/**
* A page token, received from a previous
* MetadataService.ListMetadataStores google.cloud.aiplatform.v1.MetadataService.ListMetadataStores call. Provide this to retrieve the
* subsequent page.
* When paginating, all other provided parameters must match the call that
* provided the page token. (Otherwise the request will fail with
* INVALID_ARGUMENT error.)
*/
// const pageToken = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callListMetadataStores() {
// Construct request
const request = {
parent,
};
// Run request
const iterable = await aiplatformClient.listMetadataStoresAsync(request);
for await (const response of iterable) {
console.log(response);
}
}
callListMetadataStores();
listMetadataStoresStream(request, options)
listMetadataStoresStream(request?: protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest, options?: CallOptions): Transform;
Equivalent to method.name.toCamelCase()
, but returns a NodeJS Stream object.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IListMetadataStoresRequest
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 [MetadataStore] on 'data' event. The client library will perform auto-pagination by default: it will call the API as many times as needed. Note that it can affect your quota. We recommend using |
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. |
matchEndpointFromEndpointName(endpointName)
matchEndpointFromEndpointName(endpointName: string): string | number;
Parse the endpoint from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the endpoint. |
matchEntityTypeFromEntityTypeName(entityTypeName)
matchEntityTypeFromEntityTypeName(entityTypeName: string): string | number;
Parse the entity_type from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEntityTypeFromFeatureName(featureName)
matchEntityTypeFromFeatureName(featureName: string): string | number;
Parse the entity_type from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the entity_type. |
matchEvaluationFromModelEvaluationName(modelEvaluationName)
matchEvaluationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the evaluation from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchEvaluationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the evaluation from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the evaluation. |
matchExecutionFromExecutionName(executionName)
matchExecutionFromExecutionName(executionName: string): string | number;
Parse the execution from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the execution. |
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName)
matchExperimentFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the experiment from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardRunName(tensorboardRunName)
matchExperimentFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the experiment from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchExperimentFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the experiment from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the experiment. |
matchFeatureFromFeatureName(featureName)
matchFeatureFromFeatureName(featureName: string): string | number;
Parse the feature from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the feature. |
matchFeaturestoreFromEntityTypeName(entityTypeName)
matchFeaturestoreFromEntityTypeName(entityTypeName: string): string | number;
Parse the featurestore from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeatureName(featureName)
matchFeaturestoreFromFeatureName(featureName: string): string | number;
Parse the featurestore from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchFeaturestoreFromFeaturestoreName(featurestoreName)
matchFeaturestoreFromFeaturestoreName(featurestoreName: string): string | number;
Parse the featurestore from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the featurestore. |
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchHyperparameterTuningJobFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the hyperparameter_tuning_job from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the hyperparameter_tuning_job. |
matchIndexEndpointFromIndexEndpointName(indexEndpointName)
matchIndexEndpointFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the index_endpoint from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the index_endpoint. |
matchIndexFromIndexName(indexName)
matchIndexFromIndexName(indexName: string): string | number;
Parse the index from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the index. |
matchLocationFromAnnotationName(annotationName)
matchLocationFromAnnotationName(annotationName: string): string | number;
Parse the location from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromAnnotationSpecName(annotationSpecName)
matchLocationFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the location from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromArtifactName(artifactName)
matchLocationFromArtifactName(artifactName: string): string | number;
Parse the location from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromBatchPredictionJobName(batchPredictionJobName)
matchLocationFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the location from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromContextName(contextName)
matchLocationFromContextName(contextName: string): string | number;
Parse the location from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromCustomJobName(customJobName)
matchLocationFromCustomJobName(customJobName: string): string | number;
Parse the location from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataItemName(dataItemName)
matchLocationFromDataItemName(dataItemName: string): string | number;
Parse the location from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDataLabelingJobName(dataLabelingJobName)
matchLocationFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the location from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromDatasetName(datasetName)
matchLocationFromDatasetName(datasetName: string): string | number;
Parse the location from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEndpointName(endpointName)
matchLocationFromEndpointName(endpointName: string): string | number;
Parse the location from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromEntityTypeName(entityTypeName)
matchLocationFromEntityTypeName(entityTypeName: string): string | number;
Parse the location from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromExecutionName(executionName)
matchLocationFromExecutionName(executionName: string): string | number;
Parse the location from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeatureName(featureName)
matchLocationFromFeatureName(featureName: string): string | number;
Parse the location from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromFeaturestoreName(featurestoreName)
matchLocationFromFeaturestoreName(featurestoreName: string): string | number;
Parse the location from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchLocationFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the location from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexEndpointName(indexEndpointName)
matchLocationFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the location from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromIndexName(indexName)
matchLocationFromIndexName(indexName: string): string | number;
Parse the location from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromLocationName(locationName)
matchLocationFromLocationName(locationName: string): string | number;
Parse the location from Location resource.
Name | Description |
locationName |
string
A fully-qualified path representing Location resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataSchemaName(metadataSchemaName)
matchLocationFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the location from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromMetadataStoreName(metadataStoreName)
matchLocationFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the location from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchLocationFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the location from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationName(modelEvaluationName)
matchLocationFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the location from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName)
matchLocationFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the location from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromModelName(modelName)
matchLocationFromModelName(modelName: string): string | number;
Parse the location from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromPipelineJobName(pipelineJobName)
matchLocationFromPipelineJobName(pipelineJobName: string): string | number;
Parse the location from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromSpecialistPoolName(specialistPoolName)
matchLocationFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the location from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromStudyName(studyName)
matchLocationFromStudyName(studyName: string): string | number;
Parse the location from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardExperimentName(tensorboardExperimentName)
matchLocationFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the location from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardName(tensorboardName)
matchLocationFromTensorboardName(tensorboardName: string): string | number;
Parse the location from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardRunName(tensorboardRunName)
matchLocationFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the location from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchLocationFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the location from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrainingPipelineName(trainingPipelineName)
matchLocationFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the location from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchLocationFromTrialName(trialName)
matchLocationFromTrialName(trialName: string): string | number;
Parse the location from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the location. |
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName)
matchMetadataSchemaFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_schema from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_schema. |
matchMetadataStoreFromArtifactName(artifactName)
matchMetadataStoreFromArtifactName(artifactName: string): string | number;
Parse the metadata_store from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromContextName(contextName)
matchMetadataStoreFromContextName(contextName: string): string | number;
Parse the metadata_store from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromExecutionName(executionName)
matchMetadataStoreFromExecutionName(executionName: string): string | number;
Parse the metadata_store from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName)
matchMetadataStoreFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the metadata_store from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchMetadataStoreFromMetadataStoreName(metadataStoreName)
matchMetadataStoreFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the metadata_store from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the metadata_store. |
matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchModelDeploymentMonitoringJobFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the model_deployment_monitoring_job from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the model_deployment_monitoring_job. |
matchModelFromModelEvaluationName(modelEvaluationName)
matchModelFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the model from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName)
matchModelFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the model from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchModelFromModelName(modelName)
matchModelFromModelName(modelName: string): string | number;
Parse the model from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the model. |
matchPipelineJobFromPipelineJobName(pipelineJobName)
matchPipelineJobFromPipelineJobName(pipelineJobName: string): string | number;
Parse the pipeline_job from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the pipeline_job. |
matchProjectFromAnnotationName(annotationName)
matchProjectFromAnnotationName(annotationName: string): string | number;
Parse the project from Annotation resource.
Name | Description |
annotationName |
string
A fully-qualified path representing Annotation resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromAnnotationSpecName(annotationSpecName)
matchProjectFromAnnotationSpecName(annotationSpecName: string): string | number;
Parse the project from AnnotationSpec resource.
Name | Description |
annotationSpecName |
string
A fully-qualified path representing AnnotationSpec resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromArtifactName(artifactName)
matchProjectFromArtifactName(artifactName: string): string | number;
Parse the project from Artifact resource.
Name | Description |
artifactName |
string
A fully-qualified path representing Artifact resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromBatchPredictionJobName(batchPredictionJobName)
matchProjectFromBatchPredictionJobName(batchPredictionJobName: string): string | number;
Parse the project from BatchPredictionJob resource.
Name | Description |
batchPredictionJobName |
string
A fully-qualified path representing BatchPredictionJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromContextName(contextName)
matchProjectFromContextName(contextName: string): string | number;
Parse the project from Context resource.
Name | Description |
contextName |
string
A fully-qualified path representing Context resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromCustomJobName(customJobName)
matchProjectFromCustomJobName(customJobName: string): string | number;
Parse the project from CustomJob resource.
Name | Description |
customJobName |
string
A fully-qualified path representing CustomJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataItemName(dataItemName)
matchProjectFromDataItemName(dataItemName: string): string | number;
Parse the project from DataItem resource.
Name | Description |
dataItemName |
string
A fully-qualified path representing DataItem resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDataLabelingJobName(dataLabelingJobName)
matchProjectFromDataLabelingJobName(dataLabelingJobName: string): string | number;
Parse the project from DataLabelingJob resource.
Name | Description |
dataLabelingJobName |
string
A fully-qualified path representing DataLabelingJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromDatasetName(datasetName)
matchProjectFromDatasetName(datasetName: string): string | number;
Parse the project from Dataset resource.
Name | Description |
datasetName |
string
A fully-qualified path representing Dataset resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEndpointName(endpointName)
matchProjectFromEndpointName(endpointName: string): string | number;
Parse the project from Endpoint resource.
Name | Description |
endpointName |
string
A fully-qualified path representing Endpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromEntityTypeName(entityTypeName)
matchProjectFromEntityTypeName(entityTypeName: string): string | number;
Parse the project from EntityType resource.
Name | Description |
entityTypeName |
string
A fully-qualified path representing EntityType resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromExecutionName(executionName)
matchProjectFromExecutionName(executionName: string): string | number;
Parse the project from Execution resource.
Name | Description |
executionName |
string
A fully-qualified path representing Execution resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeatureName(featureName)
matchProjectFromFeatureName(featureName: string): string | number;
Parse the project from Feature resource.
Name | Description |
featureName |
string
A fully-qualified path representing Feature resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromFeaturestoreName(featurestoreName)
matchProjectFromFeaturestoreName(featurestoreName: string): string | number;
Parse the project from Featurestore resource.
Name | Description |
featurestoreName |
string
A fully-qualified path representing Featurestore resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName)
matchProjectFromHyperparameterTuningJobName(hyperparameterTuningJobName: string): string | number;
Parse the project from HyperparameterTuningJob resource.
Name | Description |
hyperparameterTuningJobName |
string
A fully-qualified path representing HyperparameterTuningJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexEndpointName(indexEndpointName)
matchProjectFromIndexEndpointName(indexEndpointName: string): string | number;
Parse the project from IndexEndpoint resource.
Name | Description |
indexEndpointName |
string
A fully-qualified path representing IndexEndpoint resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromIndexName(indexName)
matchProjectFromIndexName(indexName: string): string | number;
Parse the project from Index resource.
Name | Description |
indexName |
string
A fully-qualified path representing Index resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromLocationName(locationName)
matchProjectFromLocationName(locationName: string): string | number;
Parse the project from Location resource.
Name | Description |
locationName |
string
A fully-qualified path representing Location resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromMetadataSchemaName(metadataSchemaName)
matchProjectFromMetadataSchemaName(metadataSchemaName: string): string | number;
Parse the project from MetadataSchema resource.
Name | Description |
metadataSchemaName |
string
A fully-qualified path representing MetadataSchema resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromMetadataStoreName(metadataStoreName)
matchProjectFromMetadataStoreName(metadataStoreName: string): string | number;
Parse the project from MetadataStore resource.
Name | Description |
metadataStoreName |
string
A fully-qualified path representing MetadataStore resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName)
matchProjectFromModelDeploymentMonitoringJobName(modelDeploymentMonitoringJobName: string): string | number;
Parse the project from ModelDeploymentMonitoringJob resource.
Name | Description |
modelDeploymentMonitoringJobName |
string
A fully-qualified path representing ModelDeploymentMonitoringJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelEvaluationName(modelEvaluationName)
matchProjectFromModelEvaluationName(modelEvaluationName: string): string | number;
Parse the project from ModelEvaluation resource.
Name | Description |
modelEvaluationName |
string
A fully-qualified path representing ModelEvaluation resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName)
matchProjectFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the project from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromModelName(modelName)
matchProjectFromModelName(modelName: string): string | number;
Parse the project from Model resource.
Name | Description |
modelName |
string
A fully-qualified path representing Model resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromPipelineJobName(pipelineJobName)
matchProjectFromPipelineJobName(pipelineJobName: string): string | number;
Parse the project from PipelineJob resource.
Name | Description |
pipelineJobName |
string
A fully-qualified path representing PipelineJob resource. |
Type | Description |
string | number | {string} A string representing the project. |
matchProjectFromProjectName(projectName)
matchProjectFromProjectName(projectName: string): string | number;
Parse the project from Project resource.
Name | Description |
projectName |
string
A fully-qualified path representing Project 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. |
matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName)
matchSliceFromModelEvaluationSliceName(modelEvaluationSliceName: string): string | number;
Parse the slice from ModelEvaluationSlice resource.
Name | Description |
modelEvaluationSliceName |
string
A fully-qualified path representing ModelEvaluationSlice resource. |
Type | Description |
string | number | {string} A string representing the slice. |
matchSpecialistPoolFromSpecialistPoolName(specialistPoolName)
matchSpecialistPoolFromSpecialistPoolName(specialistPoolName: string): string | number;
Parse the specialist_pool from SpecialistPool resource.
Name | Description |
specialistPoolName |
string
A fully-qualified path representing SpecialistPool resource. |
Type | Description |
string | number | {string} A string representing the specialist_pool. |
matchStudyFromStudyName(studyName)
matchStudyFromStudyName(studyName: string): string | number;
Parse the study from Study resource.
Name | Description |
studyName |
string
A fully-qualified path representing Study resource. |
Type | Description |
string | number | {string} A string representing the study. |
matchStudyFromTrialName(trialName)
matchStudyFromTrialName(trialName: string): string | number;
Parse the study from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the study. |
matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName)
matchTensorboardFromTensorboardExperimentName(tensorboardExperimentName: string): string | number;
Parse the tensorboard from TensorboardExperiment resource.
Name | Description |
tensorboardExperimentName |
string
A fully-qualified path representing TensorboardExperiment resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardName(tensorboardName)
matchTensorboardFromTensorboardName(tensorboardName: string): string | number;
Parse the tensorboard from Tensorboard resource.
Name | Description |
tensorboardName |
string
A fully-qualified path representing Tensorboard resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardRunName(tensorboardRunName)
matchTensorboardFromTensorboardRunName(tensorboardRunName: string): string | number;
Parse the tensorboard from TensorboardRun resource.
Name | Description |
tensorboardRunName |
string
A fully-qualified path representing TensorboardRun resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchTensorboardFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the tensorboard from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the tensorboard. |
matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName)
matchTimeSeriesFromTensorboardTimeSeriesName(tensorboardTimeSeriesName: string): string | number;
Parse the time_series from TensorboardTimeSeries resource.
Name | Description |
tensorboardTimeSeriesName |
string
A fully-qualified path representing TensorboardTimeSeries resource. |
Type | Description |
string | number | {string} A string representing the time_series. |
matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName)
matchTrainingPipelineFromTrainingPipelineName(trainingPipelineName: string): string | number;
Parse the training_pipeline from TrainingPipeline resource.
Name | Description |
trainingPipelineName |
string
A fully-qualified path representing TrainingPipeline resource. |
Type | Description |
string | number | {string} A string representing the training_pipeline. |
matchTrialFromTrialName(trialName)
matchTrialFromTrialName(trialName: string): string | number;
Parse the trial from Trial resource.
Name | Description |
trialName |
string
A fully-qualified path representing Trial resource. |
Type | Description |
string | number | {string} A string representing the trial. |
metadataSchemaPath(project, location, metadataStore, metadataSchema)
metadataSchemaPath(project: string, location: string, metadataStore: string, metadataSchema: string): string;
Return a fully-qualified metadataSchema resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
metadataSchema |
string
|
Type | Description |
string | {string} Resource name string. |
metadataStorePath(project, location, metadataStore)
metadataStorePath(project: string, location: string, metadataStore: string): string;
Return a fully-qualified metadataStore resource name string.
Name | Description |
project |
string
|
location |
string
|
metadataStore |
string
|
Type | Description |
string | {string} Resource name string. |
modelDeploymentMonitoringJobPath(project, location, modelDeploymentMonitoringJob)
modelDeploymentMonitoringJobPath(project: string, location: string, modelDeploymentMonitoringJob: string): string;
Return a fully-qualified modelDeploymentMonitoringJob resource name string.
Name | Description |
project |
string
|
location |
string
|
modelDeploymentMonitoringJob |
string
|
Type | Description |
string | {string} Resource name string. |
modelEvaluationPath(project, location, model, evaluation)
modelEvaluationPath(project: string, location: string, model: string, evaluation: string): string;
Return a fully-qualified modelEvaluation resource name string.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
evaluation |
string
|
Type | Description |
string | {string} Resource name string. |
modelEvaluationSlicePath(project, location, model, evaluation, slice)
modelEvaluationSlicePath(project: string, location: string, model: string, evaluation: string, slice: string): string;
Return a fully-qualified modelEvaluationSlice resource name string.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
evaluation |
string
|
slice |
string
|
Type | Description |
string | {string} Resource name string. |
modelPath(project, location, model)
modelPath(project: string, location: string, model: string): string;
Return a fully-qualified model resource name string.
Name | Description |
project |
string
|
location |
string
|
model |
string
|
Type | Description |
string | {string} Resource name string. |
pipelineJobPath(project, location, pipelineJob)
pipelineJobPath(project: string, location: string, pipelineJob: string): string;
Return a fully-qualified pipelineJob resource name string.
Name | Description |
project |
string
|
location |
string
|
pipelineJob |
string
|
Type | Description |
string | {string} Resource name string. |
projectPath(project)
projectPath(project: string): string;
Return a fully-qualified project resource name string.
Name | Description |
project |
string
|
Type | Description |
string | {string} Resource name string. |
purgeArtifacts(request, options)
purgeArtifacts(request?: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Purges Artifacts.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Artifacts from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Artifacts to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" artifact="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeartifacts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeartifacts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeartifacts();="">
purgeArtifacts(request, options, callback)
purgeArtifacts(request: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
purgeArtifacts(request, callback)
purgeArtifacts(request: protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeArtifactsRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeArtifactsResponse, protos.google.cloud.aiplatform.v1.IPurgeArtifactsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
purgeContexts(request, options)
purgeContexts(request?: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Purges Contexts.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeContextsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Contexts from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Contexts to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" context="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgecontexts()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgecontexts(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgecontexts();="">
purgeContexts(request, options, callback)
purgeContexts(request: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeContextsRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
purgeContexts(request, callback)
purgeContexts(request: protos.google.cloud.aiplatform.v1.IPurgeContextsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeContextsRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeContextsResponse, protos.google.cloud.aiplatform.v1.IPurgeContextsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
purgeExecutions(request, options)
purgeExecutions(request?: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, options?: CallOptions): Promise<[
LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>,
protos.google.longrunning.IOperation | undefined,
{} | undefined
]>;
Purges Executions.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing a long running operation. Its |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The metadata store to purge Executions from.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}`
*/
// const parent = 'abc123'
/**
* Required. A required filter matching the Executions to be purged.
* E.g., `update_time <= 2020-11-19t11:30:00-04:00`.="" */="" const="" filter='abc123' *="" *="" optional.="" flag="" to="" indicate="" to="" actually="" perform="" the="" purge.="" *="" if="" `force`="" is="" set="" to="" false,="" the="" method="" will="" return="" a="" sample="" of="" *="" execution="" names="" that="" would="" be="" deleted.="" */="" const="" force="true" imports="" the="" aiplatform="" library="" const="" {metadataserviceclient}="require('@google-cloud/aiplatform').v1;" instantiates="" a="" client="" const="" aiplatformclient="new" metadataserviceclient();="" async="" function="" callpurgeexecutions()="" {="" construct="" request="" const="" request="{" parent,="" filter,="" };="" run="" request="" const="" [operation]="await" aiplatformclient.purgeexecutions(request);="" const="" [response]="await" operation.promise();="" console.log(response);="" }="" callpurgeexecutions();="">
purgeExecutions(request, options, callback)
purgeExecutions(request: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, options: CallOptions, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest
|
options |
CallOptions
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
purgeExecutions(request, callback)
purgeExecutions(request: protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest, callback: Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IPurgeExecutionsRequest
|
callback |
Callback<LROperation<protos.google.cloud.aiplatform.v1.IPurgeExecutionsResponse, protos.google.cloud.aiplatform.v1.IPurgeExecutionsMetadata>, protos.google.longrunning.IOperation | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryArtifactLineageSubgraph(request, options)
queryArtifactLineageSubgraph(request?: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.ILineageSubgraph,
(protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | undefined),
{} | undefined
]>;
Retrieves lineage of an Artifact represented through Artifacts and Executions connected by Event edges and returned as a LineageSubgraph.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | undefined), {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Artifact whose Lineage needs to be retrieved as a
* LineageSubgraph.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
* The request may error with FAILED_PRECONDITION if the number of Artifacts,
* the number of Executions, or the number of Events that would be returned
* for the Context exceeds 1000.
*/
// const artifact = 'abc123'
/**
* Specifies the size of the lineage graph in terms of number of hops from the
* specified artifact.
* Negative Value: INVALID_ARGUMENT error is returned
* 0: Only input artifact is returned.
* No value: Transitive closure is performed to return the complete graph.
*/
// const maxHops = 1234
/**
* Filter specifying the boolean condition for the Artifacts to satisfy in
* order to be part of the Lineage Subgraph.
* The syntax to define filter query is based on https://google.aip.dev/160.
* The supported set of filters include the following:
* * **Attribute filtering**:
* For example: `display_name = "test"`
* Supported fields include: `name`, `display_name`, `uri`, `state`,
* `schema_title`, `create_time`, and `update_time`.
* Time fields, such as `create_time` and `update_time`, require values
* specified in RFC-3339 format.
* For example: `create_time = "2020-11-19T11:30:00-04:00"`
* * **Metadata field**:
* To filter on metadata fields use traversal operation as follows:
* `metadata.
queryArtifactLineageSubgraph(request, options, callback)
queryArtifactLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryArtifactLineageSubgraph(request, callback)
queryArtifactLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryArtifactLineageSubgraphRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryContextLineageSubgraph(request, options)
queryContextLineageSubgraph(request?: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.ILineageSubgraph,
(protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | undefined),
{} | undefined
]>;
Retrieves Artifacts and Executions within the specified Context, connected by Event edges and returned as a LineageSubgraph.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | undefined), {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Context whose Artifacts and Executions
* should be retrieved as a LineageSubgraph.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
* The request may error with FAILED_PRECONDITION if the number of Artifacts,
* the number of Executions, or the number of Events that would be returned
* for the Context exceeds 1000.
*/
// const context = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callQueryContextLineageSubgraph() {
// Construct request
const request = {
context,
};
// Run request
const response = await aiplatformClient.queryContextLineageSubgraph(request);
console.log(response);
}
callQueryContextLineageSubgraph();
queryContextLineageSubgraph(request, options, callback)
queryContextLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryContextLineageSubgraph(request, callback)
queryContextLineageSubgraph(request: protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryContextLineageSubgraphRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryExecutionInputsAndOutputs(request, options)
queryExecutionInputsAndOutputs(request?: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.ILineageSubgraph,
(protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | undefined),
{} | undefined
]>;
Obtains the set of input and output Artifacts for this Execution, in the form of LineageSubgraph that also contains the Execution and connecting Events.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.ILineageSubgraph, (protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | undefined), {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [LineageSubgraph]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The resource name of the Execution whose input and output Artifacts should
* be retrieved as a LineageSubgraph.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const execution = 'abc123'
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callQueryExecutionInputsAndOutputs() {
// Construct request
const request = {
execution,
};
// Run request
const response = await aiplatformClient.queryExecutionInputsAndOutputs(request);
console.log(response);
}
callQueryExecutionInputsAndOutputs();
queryExecutionInputsAndOutputs(request, options, callback)
queryExecutionInputsAndOutputs(request: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
queryExecutionInputsAndOutputs(request, callback)
queryExecutionInputsAndOutputs(request: protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest, callback: Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.ILineageSubgraph, protos.google.cloud.aiplatform.v1.IQueryExecutionInputsAndOutputsRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
specialistPoolPath(project, location, specialistPool)
specialistPoolPath(project: string, location: string, specialistPool: string): string;
Return a fully-qualified specialistPool resource name string.
Name | Description |
project |
string
|
location |
string
|
specialistPool |
string
|
Type | Description |
string | {string} Resource name string. |
studyPath(project, location, study)
studyPath(project: string, location: string, study: string): string;
Return a fully-qualified study resource name string.
Name | Description |
project |
string
|
location |
string
|
study |
string
|
Type | Description |
string | {string} Resource name string. |
tensorboardExperimentPath(project, location, tensorboard, experiment)
tensorboardExperimentPath(project: string, location: string, tensorboard: string, experiment: string): string;
Return a fully-qualified tensorboardExperiment resource name string.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
Type | Description |
string | {string} Resource name string. |
tensorboardPath(project, location, tensorboard)
tensorboardPath(project: string, location: string, tensorboard: string): string;
Return a fully-qualified tensorboard resource name string.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
Type | Description |
string | {string} Resource name string. |
tensorboardRunPath(project, location, tensorboard, experiment, run)
tensorboardRunPath(project: string, location: string, tensorboard: string, experiment: string, run: string): string;
Return a fully-qualified tensorboardRun resource name string.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
run |
string
|
Type | Description |
string | {string} Resource name string. |
tensorboardTimeSeriesPath(project, location, tensorboard, experiment, run, timeSeries)
tensorboardTimeSeriesPath(project: string, location: string, tensorboard: string, experiment: string, run: string, timeSeries: string): string;
Return a fully-qualified tensorboardTimeSeries resource name string.
Name | Description |
project |
string
|
location |
string
|
tensorboard |
string
|
experiment |
string
|
run |
string
|
timeSeries |
string
|
Type | Description |
string | {string} Resource name string. |
trainingPipelinePath(project, location, trainingPipeline)
trainingPipelinePath(project: string, location: string, trainingPipeline: string): string;
Return a fully-qualified trainingPipeline resource name string.
Name | Description |
project |
string
|
location |
string
|
trainingPipeline |
string
|
Type | Description |
string | {string} Resource name string. |
trialPath(project, location, study, trial)
trialPath(project: string, location: string, study: string, trial: string): string;
Return a fully-qualified trial resource name string.
Name | Description |
project |
string
|
location |
string
|
study |
string
|
trial |
string
|
Type | Description |
string | {string} Resource name string. |
updateArtifact(request, options)
updateArtifact(request?: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IArtifact,
protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | undefined,
{} | undefined
]>;
Updates a stored Artifact.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Artifact]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The Artifact containing updates.
* The Artifact's Artifact.name google.cloud.aiplatform.v1.Artifact.name field is used to identify the Artifact to
* be updated.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/artifacts/{artifact}`
*/
// const artifact = {}
/**
* Required. A FieldMask indicating which fields should be updated.
* Functionality of this field is not yet supported.
*/
// const updateMask = {}
/**
* If set to true, and the Artifact google.cloud.aiplatform.v1.Artifact is not found, a new Artifact google.cloud.aiplatform.v1.Artifact is
* created.
*/
// const allowMissing = true
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callUpdateArtifact() {
// Construct request
const request = {
artifact,
updateMask,
};
// Run request
const response = await aiplatformClient.updateArtifact(request);
console.log(response);
}
callUpdateArtifact();
updateArtifact(request, options, callback)
updateArtifact(request: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateArtifact(request, callback)
updateArtifact(request: protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IArtifact, protos.google.cloud.aiplatform.v1.IUpdateArtifactRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateContext(request, options)
updateContext(request?: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IContext,
protos.google.cloud.aiplatform.v1.IUpdateContextRequest | undefined,
{} | undefined
]>;
Updates a stored Context.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateContextRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Context]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The Context containing updates.
* The Context's Context.name google.cloud.aiplatform.v1.Context.name field is used to identify the Context to be
* updated.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/contexts/{context}`
*/
// const context = {}
/**
* Required. A FieldMask indicating which fields should be updated.
* Functionality of this field is not yet supported.
*/
// const updateMask = {}
/**
* If set to true, and the Context google.cloud.aiplatform.v1.Context is not found, a new Context google.cloud.aiplatform.v1.Context is
* created.
*/
// const allowMissing = true
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callUpdateContext() {
// Construct request
const request = {
context,
updateMask,
};
// Run request
const response = await aiplatformClient.updateContext(request);
console.log(response);
}
callUpdateContext();
updateContext(request, options, callback)
updateContext(request: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateContextRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateContext(request, callback)
updateContext(request: protos.google.cloud.aiplatform.v1.IUpdateContextRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateContextRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IContext, protos.google.cloud.aiplatform.v1.IUpdateContextRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateExecution(request, options)
updateExecution(request?: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, options?: CallOptions): Promise<[
protos.google.cloud.aiplatform.v1.IExecution,
protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | undefined,
{} | undefined
]>;
Updates a stored Execution.
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest
The request object that will be sent. |
options |
CallOptions
Call options. See CallOptions for more details. |
Type | Description |
Promise<[ protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | undefined, {} | undefined ]> | {Promise} - The promise which resolves to an array. The first element of the array is an object representing [Execution]. Please see the [documentation](https://github.com/googleapis/gax-nodejs/blob/master/client-libraries.md#regular-methods) for more details and examples. |
/**
* TODO(developer): Uncomment these variables before running the sample.
*/
/**
* Required. The Execution containing updates.
* The Execution's Execution.name google.cloud.aiplatform.v1.Execution.name field is used to identify the Execution
* to be updated.
* Format:
* `projects/{project}/locations/{location}/metadataStores/{metadatastore}/executions/{execution}`
*/
// const execution = {}
/**
* Required. A FieldMask indicating which fields should be updated.
* Functionality of this field is not yet supported.
*/
// const updateMask = {}
/**
* If set to true, and the Execution google.cloud.aiplatform.v1.Execution is not found, a new Execution google.cloud.aiplatform.v1.Execution
* is created.
*/
// const allowMissing = true
// Imports the Aiplatform library
const {MetadataServiceClient} = require('@google-cloud/aiplatform').v1;
// Instantiates a client
const aiplatformClient = new MetadataServiceClient();
async function callUpdateExecution() {
// Construct request
const request = {
execution,
updateMask,
};
// Run request
const response = await aiplatformClient.updateExecution(request);
console.log(response);
}
callUpdateExecution();
updateExecution(request, options, callback)
updateExecution(request: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, options: CallOptions, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest
|
options |
CallOptions
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |
updateExecution(request, callback)
updateExecution(request: protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest, callback: Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>): void;
Name | Description |
request |
protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest
|
callback |
Callback<protos.google.cloud.aiplatform.v1.IExecution, protos.google.cloud.aiplatform.v1.IUpdateExecutionRequest | null | undefined, {} | null | undefined>
|
Type | Description |
void |