PredictionServiceClient.java
/*
* Copyright 2022 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.google.cloud.aiplatform.v1;
import com.google.api.HttpBody;
import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutures;
import com.google.api.gax.core.BackgroundResource;
import com.google.api.gax.paging.AbstractFixedSizeCollection;
import com.google.api.gax.paging.AbstractPage;
import com.google.api.gax.paging.AbstractPagedListResponse;
import com.google.api.gax.rpc.PageContext;
import com.google.api.gax.rpc.UnaryCallable;
import com.google.cloud.aiplatform.v1.stub.PredictionServiceStub;
import com.google.cloud.aiplatform.v1.stub.PredictionServiceStubSettings;
import com.google.cloud.location.GetLocationRequest;
import com.google.cloud.location.ListLocationsRequest;
import com.google.cloud.location.ListLocationsResponse;
import com.google.cloud.location.Location;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.iam.v1.GetIamPolicyRequest;
import com.google.iam.v1.Policy;
import com.google.iam.v1.SetIamPolicyRequest;
import com.google.iam.v1.TestIamPermissionsRequest;
import com.google.iam.v1.TestIamPermissionsResponse;
import com.google.protobuf.Value;
import java.io.IOException;
import java.util.List;
import java.util.concurrent.TimeUnit;
import javax.annotation.Generated;
// AUTO-GENERATED DOCUMENTATION AND CLASS.
/**
* Service Description: A service for online predictions and explanations.
*
* <p>This class provides the ability to make remote calls to the backing service through method
* calls that map to API methods. Sample code to get started:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
* List<Value> instances = new ArrayList<>();
* Value parameters = Value.newBuilder().setBoolValue(true).build();
* PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
* }
* }</pre>
*
* <p>Note: close() needs to be called on the PredictionServiceClient object to clean up resources
* such as threads. In the example above, try-with-resources is used, which automatically calls
* close().
*
* <p>The surface of this class includes several types of Java methods for each of the API's
* methods:
*
* <ol>
* <li>A "flattened" method. With this type of method, the fields of the request type have been
* converted into function parameters. It may be the case that not all fields are available as
* parameters, and not every API method will have a flattened method entry point.
* <li>A "request object" method. This type of method only takes one parameter, a request object,
* which must be constructed before the call. Not every API method will have a request object
* method.
* <li>A "callable" method. This type of method takes no parameters and returns an immutable API
* callable object, which can be used to initiate calls to the service.
* </ol>
*
* <p>See the individual methods for example code.
*
* <p>Many parameters require resource names to be formatted in a particular way. To assist with
* these names, this class includes a format method for each type of name, and additionally a parse
* method to extract the individual identifiers contained within names that are returned.
*
* <p>This class can be customized by passing in a custom instance of PredictionServiceSettings to
* create(). For example:
*
* <p>To customize credentials:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder()
* .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
* .build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }</pre>
*
* <p>To customize the endpoint:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }</pre>
*
* <p>Please refer to the GitHub repository's samples for more quickstart code snippets.
*/
@Generated("by gapic-generator-java")
public class PredictionServiceClient implements BackgroundResource {
private final PredictionServiceSettings settings;
private final PredictionServiceStub stub;
/** Constructs an instance of PredictionServiceClient with default settings. */
public static final PredictionServiceClient create() throws IOException {
return create(PredictionServiceSettings.newBuilder().build());
}
/**
* Constructs an instance of PredictionServiceClient, using the given settings. The channels are
* created based on the settings passed in, or defaults for any settings that are not set.
*/
public static final PredictionServiceClient create(PredictionServiceSettings settings)
throws IOException {
return new PredictionServiceClient(settings);
}
/**
* Constructs an instance of PredictionServiceClient, using the given stub for making calls. This
* is for advanced usage - prefer using create(PredictionServiceSettings).
*/
public static final PredictionServiceClient create(PredictionServiceStub stub) {
return new PredictionServiceClient(stub);
}
/**
* Constructs an instance of PredictionServiceClient, using the given settings. This is protected
* so that it is easy to make a subclass, but otherwise, the static factory methods should be
* preferred.
*/
protected PredictionServiceClient(PredictionServiceSettings settings) throws IOException {
this.settings = settings;
this.stub = ((PredictionServiceStubSettings) settings.getStubSettings()).createStub();
}
protected PredictionServiceClient(PredictionServiceStub stub) {
this.settings = null;
this.stub = stub;
}
public final PredictionServiceSettings getSettings() {
return settings;
}
public PredictionServiceStub getStub() {
return stub;
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
* List<Value> instances = new ArrayList<>();
* Value parameters = Value.newBuilder().setBoolValue(true).build();
* PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the prediction. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param instances Required. The instances that are the input to the prediction call. A
* DeployedModel may have an upper limit on the number of instances it supports per request,
* and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of
* customer created Models, the behaviour is as documented by that Model. The schema of any
* single instance may be specified via Endpoint's DeployedModels'
* [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
* @param parameters The parameters that govern the prediction. The schema of the parameters may
* be specified via Endpoint's DeployedModels' [Model's
* ][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(
EndpointName endpoint, List<Value> instances, Value parameters) {
PredictRequest request =
PredictRequest.newBuilder()
.setEndpoint(endpoint == null ? null : endpoint.toString())
.addAllInstances(instances)
.setParameters(parameters)
.build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* String endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString();
* List<Value> instances = new ArrayList<>();
* Value parameters = Value.newBuilder().setBoolValue(true).build();
* PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the prediction. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param instances Required. The instances that are the input to the prediction call. A
* DeployedModel may have an upper limit on the number of instances it supports per request,
* and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of
* customer created Models, the behaviour is as documented by that Model. The schema of any
* single instance may be specified via Endpoint's DeployedModels'
* [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
* @param parameters The parameters that govern the prediction. The schema of the parameters may
* be specified via Endpoint's DeployedModels' [Model's
* ][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(String endpoint, List<Value> instances, Value parameters) {
PredictRequest request =
PredictRequest.newBuilder()
.setEndpoint(endpoint)
.addAllInstances(instances)
.setParameters(parameters)
.build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* PredictRequest request =
* PredictRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .addAllInstances(new ArrayList<Value>())
* .setParameters(Value.newBuilder().setBoolValue(true).build())
* .build();
* PredictResponse response = predictionServiceClient.predict(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictResponse predict(PredictRequest request) {
return predictCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* PredictRequest request =
* PredictRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .addAllInstances(new ArrayList<Value>())
* .setParameters(Value.newBuilder().setBoolValue(true).build())
* .build();
* ApiFuture<PredictResponse> future =
* predictionServiceClient.predictCallable().futureCall(request);
* // Do something.
* PredictResponse response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<PredictRequest, PredictResponse> predictCallable() {
return stub.predictCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction with an arbitrary HTTP payload.
*
* <p>The response includes the following HTTP headers:
*
* <ul>
* <li>`X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that
* served this prediction.
* </ul>
*
* <ul>
* <li>`X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
* [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
* HttpBody httpBody = HttpBody.newBuilder().build();
* HttpBody response = predictionServiceClient.rawPredict(endpoint, httpBody);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the prediction. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param httpBody The prediction input. Supports HTTP headers and arbitrary data payload.
* <p>A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on
* the number of instances it supports per request. When this limit it is exceeded for an
* AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict]
* method returns an error. When this limit is exceeded for a custom-trained model, the
* behavior varies depending on the model.
* <p>You can specify the schema for each instance in the
* [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
* field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when
* you deploy the `Model` as a `DeployedModel` to an
* [Endpoint][google.cloud.aiplatform.v1.Endpoint] and use the `RawPredict` method.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final HttpBody rawPredict(EndpointName endpoint, HttpBody httpBody) {
RawPredictRequest request =
RawPredictRequest.newBuilder()
.setEndpoint(endpoint == null ? null : endpoint.toString())
.setHttpBody(httpBody)
.build();
return rawPredict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction with an arbitrary HTTP payload.
*
* <p>The response includes the following HTTP headers:
*
* <ul>
* <li>`X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that
* served this prediction.
* </ul>
*
* <ul>
* <li>`X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
* [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* String endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString();
* HttpBody httpBody = HttpBody.newBuilder().build();
* HttpBody response = predictionServiceClient.rawPredict(endpoint, httpBody);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the prediction. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param httpBody The prediction input. Supports HTTP headers and arbitrary data payload.
* <p>A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on
* the number of instances it supports per request. When this limit it is exceeded for an
* AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict]
* method returns an error. When this limit is exceeded for a custom-trained model, the
* behavior varies depending on the model.
* <p>You can specify the schema for each instance in the
* [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri]
* field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when
* you deploy the `Model` as a `DeployedModel` to an
* [Endpoint][google.cloud.aiplatform.v1.Endpoint] and use the `RawPredict` method.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final HttpBody rawPredict(String endpoint, HttpBody httpBody) {
RawPredictRequest request =
RawPredictRequest.newBuilder().setEndpoint(endpoint).setHttpBody(httpBody).build();
return rawPredict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction with an arbitrary HTTP payload.
*
* <p>The response includes the following HTTP headers:
*
* <ul>
* <li>`X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that
* served this prediction.
* </ul>
*
* <ul>
* <li>`X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
* [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* RawPredictRequest request =
* RawPredictRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .setHttpBody(HttpBody.newBuilder().build())
* .build();
* HttpBody response = predictionServiceClient.rawPredict(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final HttpBody rawPredict(RawPredictRequest request) {
return rawPredictCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online prediction with an arbitrary HTTP payload.
*
* <p>The response includes the following HTTP headers:
*
* <ul>
* <li>`X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that
* served this prediction.
* </ul>
*
* <ul>
* <li>`X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's
* [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.
* </ul>
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* RawPredictRequest request =
* RawPredictRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .setHttpBody(HttpBody.newBuilder().build())
* .build();
* ApiFuture<HttpBody> future = predictionServiceClient.rawPredictCallable().futureCall(request);
* // Do something.
* HttpBody response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<RawPredictRequest, HttpBody> rawPredictCallable() {
return stub.rawPredictCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online explanation.
*
* <p>If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is
* specified, the corresponding DeployModel must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If
* [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not
* specified, all DeployedModels must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only
* deployed AutoML tabular Models have explanation_spec.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* EndpointName endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
* List<Value> instances = new ArrayList<>();
* Value parameters = Value.newBuilder().setBoolValue(true).build();
* String deployedModelId = "deployedModelId-1817547906";
* ExplainResponse response =
* predictionServiceClient.explain(endpoint, instances, parameters, deployedModelId);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the explanation. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param instances Required. The instances that are the input to the explanation call. A
* DeployedModel may have an upper limit on the number of instances it supports per request,
* and when it is exceeded the explanation call errors in case of AutoML Models, or, in case
* of customer created Models, the behaviour is as documented by that Model. The schema of any
* single instance may be specified via Endpoint's DeployedModels'
* [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
* @param parameters The parameters that govern the prediction. The schema of the parameters may
* be specified via Endpoint's DeployedModels' [Model's
* ][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
* @param deployedModelId If specified, this ExplainRequest will be served by the chosen
* DeployedModel, overriding
* [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final ExplainResponse explain(
EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId) {
ExplainRequest request =
ExplainRequest.newBuilder()
.setEndpoint(endpoint == null ? null : endpoint.toString())
.addAllInstances(instances)
.setParameters(parameters)
.setDeployedModelId(deployedModelId)
.build();
return explain(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online explanation.
*
* <p>If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is
* specified, the corresponding DeployModel must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If
* [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not
* specified, all DeployedModels must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only
* deployed AutoML tabular Models have explanation_spec.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* String endpoint = EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString();
* List<Value> instances = new ArrayList<>();
* Value parameters = Value.newBuilder().setBoolValue(true).build();
* String deployedModelId = "deployedModelId-1817547906";
* ExplainResponse response =
* predictionServiceClient.explain(endpoint, instances, parameters, deployedModelId);
* }
* }</pre>
*
* @param endpoint Required. The name of the Endpoint requested to serve the explanation. Format:
* `projects/{project}/locations/{location}/endpoints/{endpoint}`
* @param instances Required. The instances that are the input to the explanation call. A
* DeployedModel may have an upper limit on the number of instances it supports per request,
* and when it is exceeded the explanation call errors in case of AutoML Models, or, in case
* of customer created Models, the behaviour is as documented by that Model. The schema of any
* single instance may be specified via Endpoint's DeployedModels'
* [Model's][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
* @param parameters The parameters that govern the prediction. The schema of the parameters may
* be specified via Endpoint's DeployedModels' [Model's
* ][google.cloud.aiplatform.v1.DeployedModel.model]
* [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata]
* [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
* @param deployedModelId If specified, this ExplainRequest will be served by the chosen
* DeployedModel, overriding
* [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final ExplainResponse explain(
String endpoint, List<Value> instances, Value parameters, String deployedModelId) {
ExplainRequest request =
ExplainRequest.newBuilder()
.setEndpoint(endpoint)
.addAllInstances(instances)
.setParameters(parameters)
.setDeployedModelId(deployedModelId)
.build();
return explain(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online explanation.
*
* <p>If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is
* specified, the corresponding DeployModel must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If
* [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not
* specified, all DeployedModels must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only
* deployed AutoML tabular Models have explanation_spec.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ExplainRequest request =
* ExplainRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .addAllInstances(new ArrayList<Value>())
* .setParameters(Value.newBuilder().setBoolValue(true).build())
* .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
* .setDeployedModelId("deployedModelId-1817547906")
* .build();
* ExplainResponse response = predictionServiceClient.explain(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final ExplainResponse explain(ExplainRequest request) {
return explainCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Perform an online explanation.
*
* <p>If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is
* specified, the corresponding DeployModel must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If
* [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not
* specified, all DeployedModels must have
* [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. Only
* deployed AutoML tabular Models have explanation_spec.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ExplainRequest request =
* ExplainRequest.newBuilder()
* .setEndpoint(EndpointName.of("[PROJECT]", "[LOCATION]", "[ENDPOINT]").toString())
* .addAllInstances(new ArrayList<Value>())
* .setParameters(Value.newBuilder().setBoolValue(true).build())
* .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
* .setDeployedModelId("deployedModelId-1817547906")
* .build();
* ApiFuture<ExplainResponse> future =
* predictionServiceClient.explainCallable().futureCall(request);
* // Do something.
* ExplainResponse response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<ExplainRequest, ExplainResponse> explainCallable() {
return stub.explainCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Lists information about the supported locations for this service.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ListLocationsRequest request =
* ListLocationsRequest.newBuilder()
* .setName("name3373707")
* .setFilter("filter-1274492040")
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .build();
* for (Location element : predictionServiceClient.listLocations(request).iterateAll()) {
* // doThingsWith(element);
* }
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final ListLocationsPagedResponse listLocations(ListLocationsRequest request) {
return listLocationsPagedCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Lists information about the supported locations for this service.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ListLocationsRequest request =
* ListLocationsRequest.newBuilder()
* .setName("name3373707")
* .setFilter("filter-1274492040")
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .build();
* ApiFuture<Location> future =
* predictionServiceClient.listLocationsPagedCallable().futureCall(request);
* // Do something.
* for (Location element : future.get().iterateAll()) {
* // doThingsWith(element);
* }
* }
* }</pre>
*/
public final UnaryCallable<ListLocationsRequest, ListLocationsPagedResponse>
listLocationsPagedCallable() {
return stub.listLocationsPagedCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Lists information about the supported locations for this service.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* ListLocationsRequest request =
* ListLocationsRequest.newBuilder()
* .setName("name3373707")
* .setFilter("filter-1274492040")
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .build();
* while (true) {
* ListLocationsResponse response =
* predictionServiceClient.listLocationsCallable().call(request);
* for (Location element : response.getLocationsList()) {
* // doThingsWith(element);
* }
* String nextPageToken = response.getNextPageToken();
* if (!Strings.isNullOrEmpty(nextPageToken)) {
* request = request.toBuilder().setPageToken(nextPageToken).build();
* } else {
* break;
* }
* }
* }
* }</pre>
*/
public final UnaryCallable<ListLocationsRequest, ListLocationsResponse> listLocationsCallable() {
return stub.listLocationsCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Gets information about a location.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();
* Location response = predictionServiceClient.getLocation(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final Location getLocation(GetLocationRequest request) {
return getLocationCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Gets information about a location.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();
* ApiFuture<Location> future =
* predictionServiceClient.getLocationCallable().futureCall(request);
* // Do something.
* Location response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<GetLocationRequest, Location> getLocationCallable() {
return stub.getLocationCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Sets the access control policy on the specified resource. Replacesany existing policy.
*
* <p>Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED`errors.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* SetIamPolicyRequest request =
* SetIamPolicyRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .setPolicy(Policy.newBuilder().build())
* .setUpdateMask(FieldMask.newBuilder().build())
* .build();
* Policy response = predictionServiceClient.setIamPolicy(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final Policy setIamPolicy(SetIamPolicyRequest request) {
return setIamPolicyCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Sets the access control policy on the specified resource. Replacesany existing policy.
*
* <p>Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED`errors.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* SetIamPolicyRequest request =
* SetIamPolicyRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .setPolicy(Policy.newBuilder().build())
* .setUpdateMask(FieldMask.newBuilder().build())
* .build();
* ApiFuture<Policy> future = predictionServiceClient.setIamPolicyCallable().futureCall(request);
* // Do something.
* Policy response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<SetIamPolicyRequest, Policy> setIamPolicyCallable() {
return stub.setIamPolicyCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Gets the access control policy for a resource. Returns an empty policyif the resource exists
* and does not have a policy set.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* GetIamPolicyRequest request =
* GetIamPolicyRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .setOptions(GetPolicyOptions.newBuilder().build())
* .build();
* Policy response = predictionServiceClient.getIamPolicy(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final Policy getIamPolicy(GetIamPolicyRequest request) {
return getIamPolicyCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Gets the access control policy for a resource. Returns an empty policyif the resource exists
* and does not have a policy set.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* GetIamPolicyRequest request =
* GetIamPolicyRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .setOptions(GetPolicyOptions.newBuilder().build())
* .build();
* ApiFuture<Policy> future = predictionServiceClient.getIamPolicyCallable().futureCall(request);
* // Do something.
* Policy response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<GetIamPolicyRequest, Policy> getIamPolicyCallable() {
return stub.getIamPolicyCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Returns permissions that a caller has on the specified resource. If theresource does not exist,
* this will return an empty set ofpermissions, not a `NOT_FOUND` error.
*
* <p>Note: This operation is designed to be used for buildingpermission-aware UIs and
* command-line tools, not for authorizationchecking. This operation may "fail open" without
* warning.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* TestIamPermissionsRequest request =
* TestIamPermissionsRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .addAllPermissions(new ArrayList<String>())
* .build();
* TestIamPermissionsResponse response = predictionServiceClient.testIamPermissions(request);
* }
* }</pre>
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final TestIamPermissionsResponse testIamPermissions(TestIamPermissionsRequest request) {
return testIamPermissionsCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Returns permissions that a caller has on the specified resource. If theresource does not exist,
* this will return an empty set ofpermissions, not a `NOT_FOUND` error.
*
* <p>Note: This operation is designed to be used for buildingpermission-aware UIs and
* command-line tools, not for authorizationchecking. This operation may "fail open" without
* warning.
*
* <p>Sample code:
*
* <pre>{@code
* // This snippet has been automatically generated and should be regarded as a code template only.
* // It will require modifications to work:
* // - It may require correct/in-range values for request initialization.
* // - It may require specifying regional endpoints when creating the service client as shown in
* // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
* try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
* TestIamPermissionsRequest request =
* TestIamPermissionsRequest.newBuilder()
* .setResource(
* EntityTypeName.of("[PROJECT]", "[LOCATION]", "[FEATURESTORE]", "[ENTITY_TYPE]")
* .toString())
* .addAllPermissions(new ArrayList<String>())
* .build();
* ApiFuture<TestIamPermissionsResponse> future =
* predictionServiceClient.testIamPermissionsCallable().futureCall(request);
* // Do something.
* TestIamPermissionsResponse response = future.get();
* }
* }</pre>
*/
public final UnaryCallable<TestIamPermissionsRequest, TestIamPermissionsResponse>
testIamPermissionsCallable() {
return stub.testIamPermissionsCallable();
}
@Override
public final void close() {
stub.close();
}
@Override
public void shutdown() {
stub.shutdown();
}
@Override
public boolean isShutdown() {
return stub.isShutdown();
}
@Override
public boolean isTerminated() {
return stub.isTerminated();
}
@Override
public void shutdownNow() {
stub.shutdownNow();
}
@Override
public boolean awaitTermination(long duration, TimeUnit unit) throws InterruptedException {
return stub.awaitTermination(duration, unit);
}
public static class ListLocationsPagedResponse
extends AbstractPagedListResponse<
ListLocationsRequest,
ListLocationsResponse,
Location,
ListLocationsPage,
ListLocationsFixedSizeCollection> {
public static ApiFuture<ListLocationsPagedResponse> createAsync(
PageContext<ListLocationsRequest, ListLocationsResponse, Location> context,
ApiFuture<ListLocationsResponse> futureResponse) {
ApiFuture<ListLocationsPage> futurePage =
ListLocationsPage.createEmptyPage().createPageAsync(context, futureResponse);
return ApiFutures.transform(
futurePage,
input -> new ListLocationsPagedResponse(input),
MoreExecutors.directExecutor());
}
private ListLocationsPagedResponse(ListLocationsPage page) {
super(page, ListLocationsFixedSizeCollection.createEmptyCollection());
}
}
public static class ListLocationsPage
extends AbstractPage<
ListLocationsRequest, ListLocationsResponse, Location, ListLocationsPage> {
private ListLocationsPage(
PageContext<ListLocationsRequest, ListLocationsResponse, Location> context,
ListLocationsResponse response) {
super(context, response);
}
private static ListLocationsPage createEmptyPage() {
return new ListLocationsPage(null, null);
}
@Override
protected ListLocationsPage createPage(
PageContext<ListLocationsRequest, ListLocationsResponse, Location> context,
ListLocationsResponse response) {
return new ListLocationsPage(context, response);
}
@Override
public ApiFuture<ListLocationsPage> createPageAsync(
PageContext<ListLocationsRequest, ListLocationsResponse, Location> context,
ApiFuture<ListLocationsResponse> futureResponse) {
return super.createPageAsync(context, futureResponse);
}
}
public static class ListLocationsFixedSizeCollection
extends AbstractFixedSizeCollection<
ListLocationsRequest,
ListLocationsResponse,
Location,
ListLocationsPage,
ListLocationsFixedSizeCollection> {
private ListLocationsFixedSizeCollection(List<ListLocationsPage> pages, int collectionSize) {
super(pages, collectionSize);
}
private static ListLocationsFixedSizeCollection createEmptyCollection() {
return new ListLocationsFixedSizeCollection(null, 0);
}
@Override
protected ListLocationsFixedSizeCollection createCollection(
List<ListLocationsPage> pages, int collectionSize) {
return new ListLocationsFixedSizeCollection(pages, collectionSize);
}
}
}