Class PredictionServiceClient (0.1.0)
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publicclass PredictionServiceClientimplementsBackgroundResourceService 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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
EndpointNameendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]");
List<Value>instances=newArrayList<>();
Valueparameters=Value.newBuilder().setBoolValue(true).build();
PredictResponseresponse=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:
- 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.
- 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.
- 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
PredictionServiceSettingspredictionServiceSettings=
PredictionServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
PredictionServiceClientpredictionServiceClient=
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
PredictionServiceSettingspredictionServiceSettings=
PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
PredictionServiceClientpredictionServiceClient=
PredictionServiceClient.create(predictionServiceSettings);
To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over the wire:
// 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
PredictionServiceSettingspredictionServiceSettings=
PredictionServiceSettings.newHttpJsonBuilder().build();
PredictionServiceClientpredictionServiceClient=
PredictionServiceClient.create(predictionServiceSettings);
Please refer to the GitHub repository's samples for more quickstart code snippets.
Implements
BackgroundResourceInherited Members
Static Methods
create()
publicstaticfinalPredictionServiceClientcreate()Constructs an instance of PredictionServiceClient with default settings.
| Returns | |
|---|---|
| Type | Description |
PredictionServiceClient |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
create(PredictionServiceSettings settings)
publicstaticfinalPredictionServiceClientcreate(PredictionServiceSettingssettings)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 | |
|---|---|
| Name | Description |
settings |
PredictionServiceSettings |
| Returns | |
|---|---|
| Type | Description |
PredictionServiceClient |
|
| Exceptions | |
|---|---|
| Type | Description |
IOException |
|
create(PredictionServiceStub stub)
publicstaticfinalPredictionServiceClientcreate(PredictionServiceStubstub)Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings).
| Parameter | |
|---|---|
| Name | Description |
stub |
PredictionServiceStub |
| Returns | |
|---|---|
| Type | Description |
PredictionServiceClient |
|
Constructors
PredictionServiceClient(PredictionServiceSettings settings)
protectedPredictionServiceClient(PredictionServiceSettingssettings)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 | |
|---|---|
| Name | Description |
settings |
PredictionServiceSettings |
PredictionServiceClient(PredictionServiceStub stub)
protectedPredictionServiceClient(PredictionServiceStubstub)| Parameter | |
|---|---|
| Name | Description |
stub |
PredictionServiceStub |
Methods
awaitTermination(long duration, TimeUnit unit)
publicbooleanawaitTermination(longduration,TimeUnitunit)| Parameters | |
|---|---|
| Name | Description |
duration |
long |
unit |
TimeUnit |
| Returns | |
|---|---|
| Type | Description |
boolean |
|
| Exceptions | |
|---|---|
| Type | Description |
InterruptedException |
|
close()
publicfinalvoidclose()countTokens(CountTokensRequest request)
publicfinalCountTokensResponsecountTokens(CountTokensRequestrequest)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
CountTokensRequestrequest=
CountTokensRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setModel("model104069929")
.addAllInstances(newArrayList<Value>())
.addAllContents(newArrayList<Content>())
.build();
CountTokensResponseresponse=predictionServiceClient.countTokens(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
CountTokensRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
CountTokensResponse |
|
countTokens(EndpointName endpoint, List<Value> instances)
publicfinalCountTokensResponsecountTokens(EndpointNameendpoint,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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
EndpointNameendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]");
List<Value>instances=newArrayList<>();
CountTokensResponseresponse=predictionServiceClient.countTokens(endpoint,instances);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
EndpointName Required. The name of the Endpoint requested to perform token counting. Format:
|
instances |
List<Value>Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. |
| Returns | |
|---|---|
| Type | Description |
CountTokensResponse |
|
countTokens(String endpoint, List<Value> instances)
publicfinalCountTokensResponsecountTokens(Stringendpoint,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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
Stringendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString();
List<Value>instances=newArrayList<>();
CountTokensResponseresponse=predictionServiceClient.countTokens(endpoint,instances);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
String Required. The name of the Endpoint requested to perform token counting. Format:
|
instances |
List<Value>Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. |
| Returns | |
|---|---|
| Type | Description |
CountTokensResponse |
|
countTokensCallable()
publicfinalUnaryCallable<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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
CountTokensRequestrequest=
CountTokensRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setModel("model104069929")
.addAllInstances(newArrayList<Value>())
.addAllContents(newArrayList<Content>())
.build();
ApiFuture<CountTokensResponse>future=
predictionServiceClient.countTokensCallable().futureCall(request);
// Do something.
CountTokensResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<CountTokensRequest,CountTokensResponse> |
|
directPredict(DirectPredictRequest request)
publicfinalDirectPredictResponsedirectPredict(DirectPredictRequestrequest)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
DirectPredictRequestrequest=
DirectPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInputs(newArrayList<Tensor>())
.setParameters(Tensor.newBuilder().build())
.build();
DirectPredictResponseresponse=predictionServiceClient.directPredict(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
DirectPredictRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
DirectPredictResponse |
|
directPredictCallable()
publicfinalUnaryCallable<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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
DirectPredictRequestrequest=
DirectPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInputs(newArrayList<Tensor>())
.setParameters(Tensor.newBuilder().build())
.build();
ApiFuture<DirectPredictResponse>future=
predictionServiceClient.directPredictCallable().futureCall(request);
// Do something.
DirectPredictResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<DirectPredictRequest,DirectPredictResponse> |
|
directRawPredict(DirectRawPredictRequest request)
publicfinalDirectRawPredictResponsedirectRawPredict(DirectRawPredictRequestrequest)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
DirectRawPredictRequestrequest=
DirectRawPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setMethodName("methodName-723163380")
.setInput(ByteString.EMPTY)
.build();
DirectRawPredictResponseresponse=predictionServiceClient.directRawPredict(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
DirectRawPredictRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
DirectRawPredictResponse |
|
directRawPredictCallable()
publicfinalUnaryCallable<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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
DirectRawPredictRequestrequest=
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.
DirectRawPredictResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<DirectRawPredictRequest,DirectRawPredictResponse> |
|
explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)
publicfinalExplainResponseexplain(EndpointNameendpoint,List<Value>instances,Valueparameters,StringdeployedModelId)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
EndpointNameendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]");
List<Value>instances=newArrayList<>();
Valueparameters=Value.newBuilder().setBoolValue(true).build();
StringdeployedModelId="deployedModelId-1817547906";
ExplainResponseresponse=
predictionServiceClient.explain(endpoint,instances,parameters,deployedModelId);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
EndpointName Required. The name of the Endpoint requested to serve the explanation. Format:
|
instances |
List<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. |
parameters |
Value 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. |
deployedModelId |
String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. |
| Returns | |
|---|---|
| Type | Description |
ExplainResponse |
|
explain(ExplainRequest request)
publicfinalExplainResponseexplain(ExplainRequestrequest)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
ExplainRequestrequest=
ExplainRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInstances(newArrayList<Value>())
.setParameters(Value.newBuilder().setBoolValue(true).build())
.setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
.putAllConcurrentExplanationSpecOverride(
newHashMap<String,ExplanationSpecOverride>())
.setDeployedModelId("deployedModelId-1817547906")
.build();
ExplainResponseresponse=predictionServiceClient.explain(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
ExplainRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
ExplainResponse |
|
explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)
publicfinalExplainResponseexplain(Stringendpoint,List<Value>instances,Valueparameters,StringdeployedModelId)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
Stringendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString();
List<Value>instances=newArrayList<>();
Valueparameters=Value.newBuilder().setBoolValue(true).build();
StringdeployedModelId="deployedModelId-1817547906";
ExplainResponseresponse=
predictionServiceClient.explain(endpoint,instances,parameters,deployedModelId);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
String Required. The name of the Endpoint requested to serve the explanation. Format:
|
instances |
List<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. |
parameters |
Value 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. |
deployedModelId |
String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. |
| Returns | |
|---|---|
| Type | Description |
ExplainResponse |
|
explainCallable()
publicfinalUnaryCallable<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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
ExplainRequestrequest=
ExplainRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInstances(newArrayList<Value>())
.setParameters(Value.newBuilder().setBoolValue(true).build())
.setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
.putAllConcurrentExplanationSpecOverride(
newHashMap<String,ExplanationSpecOverride>())
.setDeployedModelId("deployedModelId-1817547906")
.build();
ApiFuture<ExplainResponse>future=
predictionServiceClient.explainCallable().futureCall(request);
// Do something.
ExplainResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<ExplainRequest,ExplainResponse> |
|
getIamPolicy(GetIamPolicyRequest request)
publicfinalPolicygetIamPolicy(GetIamPolicyRequestrequest)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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
GetIamPolicyRequestrequest=
GetIamPolicyRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setOptions(GetPolicyOptions.newBuilder().build())
.build();
Policyresponse=predictionServiceClient.getIamPolicy(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
com.google.iam.v1.GetIamPolicyRequestThe request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
com.google.iam.v1.Policy |
|
getIamPolicyCallable()
publicfinalUnaryCallable<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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
GetIamPolicyRequestrequest=
GetIamPolicyRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setOptions(GetPolicyOptions.newBuilder().build())
.build();
ApiFuture<Policy>future=predictionServiceClient.getIamPolicyCallable().futureCall(request);
// Do something.
Policyresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.iam.v1.GetIamPolicyRequest,com.google.iam.v1.Policy> |
|
getLocation(GetLocationRequest request)
publicfinalLocationgetLocation(GetLocationRequestrequest)Gets information about a location.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
GetLocationRequestrequest=GetLocationRequest.newBuilder().setName("name3373707").build();
Locationresponse=predictionServiceClient.getLocation(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
com.google.cloud.location.GetLocationRequestThe request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
com.google.cloud.location.Location |
|
getLocationCallable()
publicfinalUnaryCallable<GetLocationRequest,Location>getLocationCallable()Gets information about a location.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
GetLocationRequestrequest=GetLocationRequest.newBuilder().setName("name3373707").build();
ApiFuture<Location>future=
predictionServiceClient.getLocationCallable().futureCall(request);
// Do something.
Locationresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.cloud.location.GetLocationRequest,com.google.cloud.location.Location> |
|
getSettings()
publicfinalPredictionServiceSettingsgetSettings()| Returns | |
|---|---|
| Type | Description |
PredictionServiceSettings |
|
getStub()
publicPredictionServiceStubgetStub()| Returns | |
|---|---|
| Type | Description |
PredictionServiceStub |
|
isShutdown()
publicbooleanisShutdown()| Returns | |
|---|---|
| Type | Description |
boolean |
|
isTerminated()
publicbooleanisTerminated()| Returns | |
|---|---|
| Type | Description |
boolean |
|
listLocations(ListLocationsRequest request)
publicfinalPredictionServiceClient.ListLocationsPagedResponselistLocations(ListLocationsRequestrequest)Lists information about the supported locations for this service.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
ListLocationsRequestrequest=
ListLocationsRequest.newBuilder()
.setName("name3373707")
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
for(Locationelement:predictionServiceClient.listLocations(request).iterateAll()){
// doThingsWith(element);
}
}
| Parameter | |
|---|---|
| Name | Description |
request |
com.google.cloud.location.ListLocationsRequestThe request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
PredictionServiceClient.ListLocationsPagedResponse |
|
listLocationsCallable()
publicfinalUnaryCallable<ListLocationsRequest,ListLocationsResponse>listLocationsCallable()Lists information about the supported locations for this service.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
ListLocationsRequestrequest=
ListLocationsRequest.newBuilder()
.setName("name3373707")
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
while(true){
ListLocationsResponseresponse=
predictionServiceClient.listLocationsCallable().call(request);
for(Locationelement:response.getLocationsList()){
// doThingsWith(element);
}
StringnextPageToken=response.getNextPageToken();
if(!Strings.isNullOrEmpty(nextPageToken)){
request=request.toBuilder().setPageToken(nextPageToken).build();
}else{
break;
}
}
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.cloud.location.ListLocationsRequest,com.google.cloud.location.ListLocationsResponse> |
|
listLocationsPagedCallable()
publicfinalUnaryCallable<ListLocationsRequest,PredictionServiceClient.ListLocationsPagedResponse>listLocationsPagedCallable()Lists information about the supported locations for this service.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
ListLocationsRequestrequest=
ListLocationsRequest.newBuilder()
.setName("name3373707")
.setFilter("filter-1274492040")
.setPageSize(883849137)
.setPageToken("pageToken873572522")
.build();
ApiFuture<Location>future=
predictionServiceClient.listLocationsPagedCallable().futureCall(request);
// Do something.
for(Locationelement:future.get().iterateAll()){
// doThingsWith(element);
}
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.cloud.location.ListLocationsRequest,ListLocationsPagedResponse> |
|
predict(EndpointName endpoint, List<Value> instances, Value parameters)
publicfinalPredictResponsepredict(EndpointNameendpoint,List<Value>instances,Valueparameters)Perform an online prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
EndpointNameendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]");
List<Value>instances=newArrayList<>();
Valueparameters=Value.newBuilder().setBoolValue(true).build();
PredictResponseresponse=predictionServiceClient.predict(endpoint,instances,parameters);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
EndpointName Required. The name of the Endpoint requested to serve the prediction. Format:
|
instances |
List<Value>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 PredictSchemata's instance_schema_uri. |
parameters |
Value 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. |
| Returns | |
|---|---|
| Type | Description |
PredictResponse |
|
predict(PredictRequest request)
publicfinalPredictResponsepredict(PredictRequestrequest)Perform an online prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
PredictRequestrequest=
PredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInstances(newArrayList<Value>())
.setParameters(Value.newBuilder().setBoolValue(true).build())
.build();
PredictResponseresponse=predictionServiceClient.predict(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
PredictRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
PredictResponse |
|
predict(String endpoint, List<Value> instances, Value parameters)
publicfinalPredictResponsepredict(Stringendpoint,List<Value>instances,Valueparameters)Perform an online prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
Stringendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString();
List<Value>instances=newArrayList<>();
Valueparameters=Value.newBuilder().setBoolValue(true).build();
PredictResponseresponse=predictionServiceClient.predict(endpoint,instances,parameters);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
String Required. The name of the Endpoint requested to serve the prediction. Format:
|
instances |
List<Value>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 PredictSchemata's instance_schema_uri. |
parameters |
Value 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. |
| Returns | |
|---|---|
| Type | Description |
PredictResponse |
|
predictCallable()
publicfinalUnaryCallable<PredictRequest,PredictResponse>predictCallable()Perform an online prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
PredictRequestrequest=
PredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInstances(newArrayList<Value>())
.setParameters(Value.newBuilder().setBoolValue(true).build())
.build();
ApiFuture<PredictResponse>future=
predictionServiceClient.predictCallable().futureCall(request);
// Do something.
PredictResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<PredictRequest,PredictResponse> |
|
rawPredict(EndpointName endpoint, HttpBody httpBody)
publicfinalHttpBodyrawPredict(EndpointNameendpoint,HttpBodyhttpBody)Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction.
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
EndpointNameendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]");
HttpBodyhttpBody=HttpBody.newBuilder().build();
HttpBodyresponse=predictionServiceClient.rawPredict(endpoint,httpBody);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
EndpointName Required. The name of the Endpoint requested to serve the prediction. Format:
|
httpBody |
com.google.api.HttpBodyThe prediction input. Supports HTTP headers and arbitrary data payload. A 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 method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
predict_schemata.instance_schema_uri
field when you create a Model. This schema applies
when you deploy the |
| Returns | |
|---|---|
| Type | Description |
com.google.api.HttpBody |
|
rawPredict(RawPredictRequest request)
publicfinalHttpBodyrawPredict(RawPredictRequestrequest)Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction.
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
RawPredictRequestrequest=
RawPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setHttpBody(HttpBody.newBuilder().build())
.build();
HttpBodyresponse=predictionServiceClient.rawPredict(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
RawPredictRequest The request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
com.google.api.HttpBody |
|
rawPredict(String endpoint, HttpBody httpBody)
publicfinalHttpBodyrawPredict(Stringendpoint,HttpBodyhttpBody)Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction.
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
Stringendpoint=
EndpointName.ofProjectLocationEndpointName("[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString();
HttpBodyhttpBody=HttpBody.newBuilder().build();
HttpBodyresponse=predictionServiceClient.rawPredict(endpoint,httpBody);
}
| Parameters | |
|---|---|
| Name | Description |
endpoint |
String Required. The name of the Endpoint requested to serve the prediction. Format:
|
httpBody |
com.google.api.HttpBodyThe prediction input. Supports HTTP headers and arbitrary data payload. A 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 method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model. You can specify the schema for each instance in the
predict_schemata.instance_schema_uri
field when you create a Model. This schema applies
when you deploy the |
| Returns | |
|---|---|
| Type | Description |
com.google.api.HttpBody |
|
rawPredictCallable()
publicfinalUnaryCallable<RawPredictRequest,HttpBody>rawPredictCallable()Perform an online prediction with an arbitrary HTTP payload.
The response includes the following HTTP headers:
X-Vertex-AI-Endpoint-Id: ID of the Endpoint that served this prediction.
X-Vertex-AI-Deployed-Model-Id: ID of the Endpoint's DeployedModel that served this prediction.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
RawPredictRequestrequest=
RawPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setHttpBody(HttpBody.newBuilder().build())
.build();
ApiFuture<HttpBody>future=predictionServiceClient.rawPredictCallable().futureCall(request);
// Do something.
HttpBodyresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<RawPredictRequest,com.google.api.HttpBody> |
|
serverStreamingPredictCallable()
publicfinalServerStreamingCallable<StreamingPredictRequest,StreamingPredictResponse>serverStreamingPredictCallable()Perform a server-side streaming online prediction request for Vertex LLM streaming.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
StreamingPredictRequestrequest=
StreamingPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInputs(newArrayList<Tensor>())
.setParameters(Tensor.newBuilder().build())
.build();
ServerStream<StreamingPredictResponse>stream=
predictionServiceClient.serverStreamingPredictCallable().call(request);
for(StreamingPredictResponseresponse:stream){
// Do something when a response is received.
}
}
| Returns | |
|---|---|
| Type | Description |
ServerStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> |
|
setIamPolicy(SetIamPolicyRequest request)
publicfinalPolicysetIamPolicy(SetIamPolicyRequestrequest)Sets the access control policy on the specified resource. Replacesany existing policy.
Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIEDerrors.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
SetIamPolicyRequestrequest=
SetIamPolicyRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setPolicy(Policy.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
Policyresponse=predictionServiceClient.setIamPolicy(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
com.google.iam.v1.SetIamPolicyRequestThe request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
com.google.iam.v1.Policy |
|
setIamPolicyCallable()
publicfinalUnaryCallable<SetIamPolicyRequest,Policy>setIamPolicyCallable()Sets the access control policy on the specified resource. Replacesany existing policy.
Can return NOT_FOUND, INVALID_ARGUMENT, and PERMISSION_DENIEDerrors.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
SetIamPolicyRequestrequest=
SetIamPolicyRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setPolicy(Policy.newBuilder().build())
.setUpdateMask(FieldMask.newBuilder().build())
.build();
ApiFuture<Policy>future=predictionServiceClient.setIamPolicyCallable().futureCall(request);
// Do something.
Policyresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.iam.v1.SetIamPolicyRequest,com.google.iam.v1.Policy> |
|
shutdown()
publicvoidshutdown()shutdownNow()
publicvoidshutdownNow()streamGenerateContentCallable()
publicfinalServerStreamingCallable<GenerateContentRequest,GenerateContentResponse>streamGenerateContentCallable()Generate content with multimodal inputs with streaming support.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
GenerateContentRequestrequest=
GenerateContentRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setModel("model104069929")
.addAllContents(newArrayList<Content>())
.addAllTools(newArrayList<Tool>())
.addAllSafetySettings(newArrayList<SafetySetting>())
.setGenerationConfig(GenerationConfig.newBuilder().build())
.build();
ServerStream<GenerateContentResponse>stream=
predictionServiceClient.streamGenerateContentCallable().call(request);
for(GenerateContentResponseresponse:stream){
// Do something when a response is received.
}
}
| Returns | |
|---|---|
| Type | Description |
ServerStreamingCallable<GenerateContentRequest,GenerateContentResponse> |
|
streamingPredictCallable()
publicfinalBidiStreamingCallable<StreamingPredictRequest,StreamingPredictResponse>streamingPredictCallable()Perform a streaming 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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
BidiStream<StreamingPredictRequest,StreamingPredictResponse>bidiStream=
predictionServiceClient.streamingPredictCallable().call();
StreamingPredictRequestrequest=
StreamingPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllInputs(newArrayList<Tensor>())
.setParameters(Tensor.newBuilder().build())
.build();
bidiStream.send(request);
for(StreamingPredictResponseresponse:bidiStream){
// Do something when a response is received.
}
}
| Returns | |
|---|---|
| Type | Description |
BidiStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> |
|
streamingRawPredictCallable()
publicfinalBidiStreamingCallable<StreamingRawPredictRequest,StreamingRawPredictResponse>streamingRawPredictCallable()Perform a streaming 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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
BidiStream<StreamingRawPredictRequest,StreamingRawPredictResponse>bidiStream=
predictionServiceClient.streamingRawPredictCallable().call();
StreamingRawPredictRequestrequest=
StreamingRawPredictRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.setMethodName("methodName-723163380")
.setInput(ByteString.EMPTY)
.build();
bidiStream.send(request);
for(StreamingRawPredictResponseresponse:bidiStream){
// Do something when a response is received.
}
}
| Returns | |
|---|---|
| Type | Description |
BidiStreamingCallable<StreamingRawPredictRequest,StreamingRawPredictResponse> |
|
testIamPermissions(TestIamPermissionsRequest request)
publicfinalTestIamPermissionsResponsetestIamPermissions(TestIamPermissionsRequestrequest)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.
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.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
TestIamPermissionsRequestrequest=
TestIamPermissionsRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllPermissions(newArrayList<String>())
.build();
TestIamPermissionsResponseresponse=predictionServiceClient.testIamPermissions(request);
}
| Parameter | |
|---|---|
| Name | Description |
request |
com.google.iam.v1.TestIamPermissionsRequestThe request object containing all of the parameters for the API call. |
| Returns | |
|---|---|
| Type | Description |
com.google.iam.v1.TestIamPermissionsResponse |
|
testIamPermissionsCallable()
publicfinalUnaryCallable<TestIamPermissionsRequest,TestIamPermissionsResponse>testIamPermissionsCallable()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.
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.
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(PredictionServiceClientpredictionServiceClient=PredictionServiceClient.create()){
TestIamPermissionsRequestrequest=
TestIamPermissionsRequest.newBuilder()
.setResource(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]","[LOCATION]","[ENDPOINT]")
.toString())
.addAllPermissions(newArrayList<String>())
.build();
ApiFuture<TestIamPermissionsResponse>future=
predictionServiceClient.testIamPermissionsCallable().futureCall(request);
// Do something.
TestIamPermissionsResponseresponse=future.get();
}
| Returns | |
|---|---|
| Type | Description |
UnaryCallable<com.google.iam.v1.TestIamPermissionsRequest,com.google.iam.v1.TestIamPermissionsResponse> |
|