Class PredictionServiceClient (3.32.0)

GitHub RepositoryProduct ReferenceREST DocumentationRPC Documentation

Service Description: A service for online predictions and explanations.

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:


 // 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.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
 }

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().

The surface of this class includes several types of Java methods for each of the API's methods:

  1. 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.
  2. 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.
  3. 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.

See the individual methods for example code.

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.

This class can be customized by passing in a custom instance of PredictionServiceSettings to create(). For example:

To customize credentials:


 // 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);

To customize the endpoint:


 // 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);

Please refer to the GitHub repository's samples for more quickstart code snippets.

Inheritance

java.lang.Object > PredictionServiceClient

Static Methods

create()

public static final PredictionServiceClient create()

Constructs an instance of PredictionServiceClient with default settings.

Returns
TypeDescription
PredictionServiceClient
Exceptions
TypeDescription
IOException

create(PredictionServiceSettings settings)

public static final PredictionServiceClient create(PredictionServiceSettings settings)

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.

Parameter
NameDescription
settingsPredictionServiceSettings
Returns
TypeDescription
PredictionServiceClient
Exceptions
TypeDescription
IOException

create(PredictionServiceStub stub)

public static final PredictionServiceClient create(PredictionServiceStub stub)

Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings).

Parameter
NameDescription
stubPredictionServiceStub
Returns
TypeDescription
PredictionServiceClient

Constructors

PredictionServiceClient(PredictionServiceSettings settings)

protected PredictionServiceClient(PredictionServiceSettings settings)

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.

Parameter
NameDescription
settingsPredictionServiceSettings

PredictionServiceClient(PredictionServiceStub stub)

protected PredictionServiceClient(PredictionServiceStub stub)
Parameter
NameDescription
stubPredictionServiceStub

Methods

awaitTermination(long duration, TimeUnit unit)

public boolean awaitTermination(long duration, TimeUnit unit)
Parameters
NameDescription
durationlong
unitTimeUnit
Returns
TypeDescription
boolean
Exceptions
TypeDescription
InterruptedException

close()

public final void close()

countTokens(CountTokensRequest request)

public final CountTokensResponse countTokens(CountTokensRequest request)

Perform a token counting.

Sample 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()) {
   CountTokensRequest request =
       CountTokensRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .build();
   CountTokensResponse response = predictionServiceClient.countTokens(request);
 }
Parameter
NameDescription
requestCountTokensRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
CountTokensResponse

countTokens(EndpointName endpoint, List<Value> instances)

public final CountTokensResponse countTokens(EndpointName endpoint, List<Value> instances)

Perform a token counting.

Sample 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.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   CountTokensResponse response = predictionServiceClient.countTokens(endpoint, instances);
 }
Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesList<Value>

Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.

Returns
TypeDescription
CountTokensResponse

countTokens(String endpoint, List<Value> instances)

public final CountTokensResponse countTokens(String endpoint, List<Value> instances)

Perform a token counting.

Sample 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.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]")
           .toString();
   List<Value> instances = new ArrayList<>();
   CountTokensResponse response = predictionServiceClient.countTokens(endpoint, instances);
 }
Parameters
NameDescription
endpointString

Required. The name of the Endpoint requested to perform token counting. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesList<Value>

Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model.

Returns
TypeDescription
CountTokensResponse

countTokensCallable()

public final UnaryCallable<CountTokensRequest,CountTokensResponse> countTokensCallable()

Perform a token counting.

Sample 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()) {
   CountTokensRequest request =
       CountTokensRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .build();
   ApiFuture<CountTokensResponse> future =
       predictionServiceClient.countTokensCallable().futureCall(request);
   // Do something.
   CountTokensResponse response = future.get();
 }
Returns
TypeDescription
UnaryCallable<CountTokensRequest,CountTokensResponse>

directPredict(DirectPredictRequest request)

public final DirectPredictResponse directPredict(DirectPredictRequest request)

Perform an unary online prediction request for Vertex first-party products and frameworks.

Sample 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()) {
   DirectPredictRequest request =
       DirectPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   DirectPredictResponse response = predictionServiceClient.directPredict(request);
 }
Parameter
NameDescription
requestDirectPredictRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
DirectPredictResponse

directPredictCallable()

public final UnaryCallable<DirectPredictRequest,DirectPredictResponse> directPredictCallable()

Perform an unary online prediction request for Vertex first-party products and frameworks.

Sample 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()) {
   DirectPredictRequest request =
       DirectPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   ApiFuture<DirectPredictResponse> future =
       predictionServiceClient.directPredictCallable().futureCall(request);
   // Do something.
   DirectPredictResponse response = future.get();
 }
Returns
TypeDescription
UnaryCallable<DirectPredictRequest,DirectPredictResponse>

directRawPredict(DirectRawPredictRequest request)

public final DirectRawPredictResponse directRawPredict(DirectRawPredictRequest request)

Perform an online prediction request through gRPC.

Sample 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()) {
   DirectRawPredictRequest request =
       DirectRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   DirectRawPredictResponse response = predictionServiceClient.directRawPredict(request);
 }
Parameter
NameDescription
requestDirectRawPredictRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
DirectRawPredictResponse

directRawPredictCallable()

public final UnaryCallable<DirectRawPredictRequest,DirectRawPredictResponse> directRawPredictCallable()

Perform an online prediction request through gRPC.

Sample 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()) {
   DirectRawPredictRequest request =
       DirectRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   ApiFuture<DirectRawPredictResponse> future =
       predictionServiceClient.directRawPredictCallable().futureCall(request);
   // Do something.
   DirectRawPredictResponse response = future.get();
 }
Returns
TypeDescription
UnaryCallable<DirectRawPredictRequest,DirectRawPredictResponse>

explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)

public final ExplainResponse explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)

Perform an online explanation.

If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.

Sample 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.ofProjectLocationEndpointName("[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);
 }
Parameters
NameDescription
endpointEndpointName

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesList<Value>

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 PredictSchemata's instance_schema_uri.

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.

deployedModelIdString

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

Returns
TypeDescription
ExplainResponse

explain(ExplainRequest request)

public final ExplainResponse explain(ExplainRequest request)

Perform an online explanation.

If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.

Sample 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.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
           .putAllConcurrentExplanationSpecOverride(
               new HashMap<String, ExplanationSpecOverride>())
           .setDeployedModelId("deployedModelId-1817547906")
           .build();
   ExplainResponse response = predictionServiceClient.explain(request);
 }
Parameter
NameDescription
requestExplainRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
ExplainResponse

explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)

public final ExplainResponse explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)

Perform an online explanation.

If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.

Sample 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.ofProjectLocationEndpointName("[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);
 }
Parameters
NameDescription
endpointString

Required. The name of the Endpoint requested to serve the explanation. Format: projects/{project}/locations/{location}/endpoints/{endpoint}

instancesList<Value>

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 PredictSchemata's instance_schema_uri.

parametersValue

The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri.

deployedModelIdString

If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split.

Returns
TypeDescription
ExplainResponse

explainCallable()

public final UnaryCallable<ExplainRequest,ExplainResponse> explainCallable()

Perform an online explanation.

If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated.

Sample 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.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
           .putAllConcurrentExplanationSpecOverride(
               new HashMap<String, ExplanationSpecOverride>())
           .setDeployedModelId("deployedModelId-1817547906")
           .build();
   ApiFuture<ExplainResponse> future =
       predictionServiceClient.explainCallable().futureCall(request);
   // Do something.
   ExplainResponse response = future.get();
 }
Returns
TypeDescription
UnaryCallable<ExplainRequest,ExplainResponse>

getIamPolicy(GetIamPolicyRequest request)

public final Policy getIamPolicy(GetIamPolicyRequest request)

Gets the access control policy for a resource. Returns an empty policyif the resource exists and does not have a policy set.

Sample 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(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setOptions(GetPolicyOptions.newBuilder().build())
           .build();
   Policy response = predictionServiceClient.getIamPolicy(request);
 }
Parameter
NameDescription
requestcom.google.iam.v1.GetIamPolicyRequest

The request object containing all of the parameters for the API call.

Returns
TypeDescription
com.google.iam.v1.Policy

getIamPolicyCallable()

public final UnaryCallable<GetIamPolicyRequest,Policy> getIamPolicyCallable()

Gets the access control policy for a resource. Returns an empty policyif the resource exists and does not have a policy set.

Sample 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(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setOptions(GetPolicyOptions.newBuilder().build())
           .build();
   ApiFuture<Policy> future = predictionServiceClient.getIamPolicyCallable().futureCall(request);
   // Do something.
   Policy response = future.get();
 }
Returns
TypeDescription
UnaryCallable<com.google.iam.v1.GetIamPolicyRequest,com.google.iam.v1.Policy>

getLocation(GetLocationRequest request)

public fina