Class PredictionServiceClient (2.33.0)

Version 2.33.0

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Beta

This library is covered by the Pre-GA Offerings Terms of the Terms of Service. Pre-GA libraries might have limited support, and changes to pre-GA libraries might not be compatible with other pre-GA versions. For more information, see the launch stage descriptions.

GitHub Repository

Product Reference

REST Documentation

RPC Documentation

Service Description: AutoML Prediction API.

On any input that is documented to expect a string parameter in snake_case or kebab-case, either of those cases is accepted.

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()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   ExamplePayload payload = ExamplePayload.newBuilder().build();
   Map<String, String> params = new HashMap<>();
   PredictResponse response = predictionServiceClient.predict(name, payload, params);
 }
 

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().

Method	Description	Method Variants
Predict	Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads: Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB. Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded. Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded. Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded. Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING prediction_type. Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.	Request object method variants only take one parameter, a request object, which must be constructed before the call. predict(PredictRequest request) "Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method. predict(ModelName name, ExamplePayload payload, Map<String, String> params) predict(String name, ExamplePayload payload, Map<String, String> params) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. predictCallable()
BatchPredict	Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems: Image Classification Image Object Detection Video Classification Video Object Tracking * Text Extraction Tables	Request object method variants only take one parameter, a request object, which must be constructed before the call. batchPredictAsync(BatchPredictRequest request) Methods that return long-running operations have "Async" method variants that return OperationFuture, which is used to track polling of the service. batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service. batchPredictOperationCallable() batchPredictCallable()

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);
 

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
 PredictionServiceSettings predictionServiceSettings =
     PredictionServiceSettings.newHttpJsonBuilder().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
Type	Description
PredictionServiceClient

Exceptions
Type	Description
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
Name	Description
settings	PredictionServiceSettings

Returns
Type	Description
PredictionServiceClient

Exceptions
Type	Description
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
Name	Description
stub	PredictionServiceStub

Returns
Type	Description
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
Name	Description
settings	PredictionServiceSettings

PredictionServiceClient(PredictionServiceStub stub)

protected PredictionServiceClient(PredictionServiceStub stub)

Parameter
Name	Description
stub	PredictionServiceStub

Methods

awaitTermination(long duration, TimeUnit unit)

public boolean awaitTermination(long duration, TimeUnit unit)

Parameters
Name	Description
duration	long
unit	TimeUnit

Returns
Type	Description
boolean

Exceptions
Type	Description
InterruptedException

batchPredictAsync(BatchPredictRequest request)

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(BatchPredictRequest request)

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems:

• Image Classification
• Image Object Detection
• Video Classification
• Video Object Tracking * Text Extraction
• Tables

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()) {
   BatchPredictRequest request =
       BatchPredictRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setInputConfig(BatchPredictInputConfig.newBuilder().build())
           .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
           .putAllParams(new HashMap<String, String>())
           .build();
   BatchPredictResult response = predictionServiceClient.batchPredictAsync(request).get();
 }
 

Parameter
Name	Description
request	BatchPredictRequest The request object containing all of the parameters for the API call.

Returns
Type	Description
OperationFuture<BatchPredictResult,OperationMetadata>

batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems:

• Image Classification
• Image Object Detection
• Video Classification
• Video Object Tracking * Text Extraction
• Tables

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()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().build();
   BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().build();
   Map<String, String> params = new HashMap<>();
   BatchPredictResult response =
       predictionServiceClient.batchPredictAsync(name, inputConfig, outputConfig, params).get();
 }
 

Parameters
Name	Description
name	ModelName Required. Name of the model requested to serve the batch prediction.
inputConfig	BatchPredictInputConfig Required. The input configuration for batch prediction.
outputConfig	BatchPredictOutputConfig Required. The Configuration specifying where output predictions should be written.
params	Map<String,String> Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. For Text Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5. For Image Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. For Image Object Detection: score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server. For Video Classification : score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. segment_classification - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". shot_classification - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". 1s_interval_classification - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". For Tables: feature_imp<span>ortan</span>ce - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false. For Video Object Tracking: score_threshold - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

Returns
Type	Description
OperationFuture<BatchPredictResult,OperationMetadata>

batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)

public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String,String> params)

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems:

• Image Classification
• Image Object Detection
• Video Classification
• Video Object Tracking * Text Extraction
• Tables

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 name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   BatchPredictInputConfig inputConfig = BatchPredictInputConfig.newBuilder().build();
   BatchPredictOutputConfig outputConfig = BatchPredictOutputConfig.newBuilder().build();
   Map<String, String> params = new HashMap<>();
   BatchPredictResult response =
       predictionServiceClient.batchPredictAsync(name, inputConfig, outputConfig, params).get();
 }
 

Parameters
Name	Description
name	String Required. Name of the model requested to serve the batch prediction.
inputConfig	BatchPredictInputConfig Required. The input configuration for batch prediction.
outputConfig	BatchPredictOutputConfig Required. The Configuration specifying where output predictions should be written.
params	Map<String,String> Required. Additional domain-specific parameters for the predictions, any string must be up to 25000 characters long. For Text Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a text snippet, it will only produce results that have at least this confidence score. The default is 0.5. For Image Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. For Image Object Detection: score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be produced per image. Default is 100, the requested value may be limited by server. For Video Classification : score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for a video, it will only produce results that have at least this confidence score. The default is 0.5. segment_classification - (boolean) Set to true to request segment-level classification. AutoML Video Intelligence returns labels and their confidence scores for the entire segment of the video that user specified in the request configuration. The default is "true". shot_classification - (boolean) Set to true to request shot-level classification. AutoML Video Intelligence determines the boundaries for each camera shot in the entire segment of the video that user specified in the request configuration. AutoML Video Intelligence then returns labels and their confidence scores for each detected shot, along with the start and end time of the shot. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". 1s_interval_classification - (boolean) Set to true to request classification for a video at one-second intervals. AutoML Video Intelligence returns labels and their confidence scores for each second of the entire segment of the video that user specified in the request configuration. WARNING: Model evaluation is not done for this classification type, the quality of it depends on training data, but there are no metrics provided to describe that quality. The default is "false". For Tables: feature_imp<span>ortan</span>ce - (boolean) Whether feature importance should be populated in the returned TablesAnnotations. The default is false. For Video Object Tracking: score_threshold - (float) When Model detects objects on video frames, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned per frame. Default is 100, the requested value may be limited by server. min_bounding_box_size - (float) Only bounding boxes with shortest edge at least that long as a relative value of video frame size will be returned. Value in 0 to 1 range. Default is 0.

Returns
Type	Description
OperationFuture<BatchPredictResult,OperationMetadata>

batchPredictCallable()

public final UnaryCallable<BatchPredictRequest,Operation> batchPredictCallable()

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems:

• Image Classification
• Image Object Detection
• Video Classification
• Video Object Tracking * Text Extraction
• Tables

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()) {
   BatchPredictRequest request =
       BatchPredictRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setInputConfig(BatchPredictInputConfig.newBuilder().build())
           .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
           .putAllParams(new HashMap<String, String>())
           .build();
   ApiFuture<Operation> future =
       predictionServiceClient.batchPredictCallable().futureCall(request);
   // Do something.
   Operation response = future.get();
 }
 

Returns
Type	Description
UnaryCallable<BatchPredictRequest,Operation>

batchPredictOperationCallable()

public final OperationCallable<BatchPredictRequest,BatchPredictResult,OperationMetadata> batchPredictOperationCallable()

Perform a batch prediction. Unlike the online Predict, batch prediction result won't be immediately available in the response. Instead, a long running operation object is returned. User can poll the operation result via GetOperation method. Once the operation is done, BatchPredictResult is returned in the response field. Available for following ML problems:

• Image Classification
• Image Object Detection
• Video Classification
• Video Object Tracking * Text Extraction
• Tables

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()) {
   BatchPredictRequest request =
       BatchPredictRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setInputConfig(BatchPredictInputConfig.newBuilder().build())
           .setOutputConfig(BatchPredictOutputConfig.newBuilder().build())
           .putAllParams(new HashMap<String, String>())
           .build();
   OperationFuture<BatchPredictResult, OperationMetadata> future =
       predictionServiceClient.batchPredictOperationCallable().futureCall(request);
   // Do something.
   BatchPredictResult response = future.get();
 }
 

Returns
Type	Description
OperationCallable<BatchPredictRequest,BatchPredictResult,OperationMetadata>

close()

public final void close()

getHttpJsonOperationsClient()

public final OperationsClient getHttpJsonOperationsClient()

Beta

This feature is covered by the Pre-GA Offerings Terms of the Terms of Service. Pre-GA libraries might have limited support, and changes to pre-GA libraries might not be compatible with other pre-GA versions. For more information, see the launch stage descriptions.

Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.

Returns
Type	Description
OperationsClient

getOperationsClient()

public final OperationsClient getOperationsClient()

Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.

Returns
Type	Description
OperationsClient

getSettings()

public final PredictionServiceSettings getSettings()

Returns
Type	Description
PredictionServiceSettings

getStub()

public PredictionServiceStub getStub()

Returns
Type	Description
PredictionServiceStub

isShutdown()

public boolean isShutdown()

Returns
Type	Description
boolean

isTerminated()

public boolean isTerminated()

Returns
Type	Description
boolean

predict(ModelName name, ExamplePayload payload, Map<String,String> params)

public final PredictResponse predict(ModelName name, ExamplePayload payload, Map<String,String> params)

Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads:

• Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
• Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
• Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
• Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

prediction_type.

• Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

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()) {
   ModelName name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]");
   ExamplePayload payload = ExamplePayload.newBuilder().build();
   Map<String, String> params = new HashMap<>();
   PredictResponse response = predictionServiceClient.predict(name, payload, params);
 }
 

Parameters
Name	Description
name	ModelName Required. Name of the model requested to serve the prediction.
payload	ExamplePayload Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.
params	Map<String,String> Additional domain-specific parameters, any string must be up to 25000 characters long. For Image Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. * For Image Object Detection: score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned in the response. Default is 100, the requested value may be limited by server. For Tables: feature_imp<span>ortan</span>ce - (boolean) Whether feature importance should be populated in the returned TablesAnnotation. The default is false.

Returns
Type	Description
PredictResponse

predict(PredictRequest request)

public final PredictResponse predict(PredictRequest request)

Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads:

• Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
• Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
• Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
• Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

prediction_type.

• Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

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()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setPayload(ExamplePayload.newBuilder().build())
           .putAllParams(new HashMap<String, String>())
           .build();
   PredictResponse response = 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 name, ExamplePayload payload, Map<String,String> params)

public final PredictResponse predict(String name, ExamplePayload payload, Map<String,String> params)

Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads:

• Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
• Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
• Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
• Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

prediction_type.

• Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

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 name = ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString();
   ExamplePayload payload = ExamplePayload.newBuilder().build();
   Map<String, String> params = new HashMap<>();
   PredictResponse response = predictionServiceClient.predict(name, payload, params);
 }
 

Parameters
Name	Description
name	String Required. Name of the model requested to serve the prediction.
payload	ExamplePayload Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.
params	Map<String,String> Additional domain-specific parameters, any string must be up to 25000 characters long. For Image Classification: score_threshold - (float) A value from 0.0 to 1.0. When the model makes predictions for an image, it will only produce results that have at least this confidence score. The default is 0.5. * For Image Object Detection: score_threshold - (float) When Model detects objects on the image, it will only produce bounding boxes which have at least this confidence score. Value in 0 to 1 range, default is 0.5. max_bounding_box_count - (int64) No more than this number of bounding boxes will be returned in the response. Default is 100, the requested value may be limited by server. For Tables: feature_imp<span>ortan</span>ce - (boolean) Whether feature importance should be populated in the returned TablesAnnotation. The default is false.

Returns
Type	Description
PredictResponse

predictCallable()

public final UnaryCallable<PredictRequest,PredictResponse> predictCallable()

Perform an online prediction. The prediction result will be directly returned in the response. Available for following ML problems, and their expected request payloads:

• Image Classification - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Image Object Detection - Image in .JPEG, .GIF or .PNG format, image_bytes up to 30MB.
• Text Classification - TextSnippet, content up to 60,000 characters, UTF-8 encoded.
• Text Extraction - TextSnippet, content up to 30,000 characters, UTF-8 NFC encoded.
• Translation - TextSnippet, content up to 25,000 characters, UTF-8 encoded.
• Tables - Row, with column values matching the columns of the model, up to 5MB. Not available for FORECASTING

prediction_type.

• Text Sentiment - TextSnippet, content up 500 characters, UTF-8 encoded.

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()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setName(ModelName.of("[PROJECT]", "[LOCATION]", "[MODEL]").toString())
           .setPayload(ExamplePayload.newBuilder().build())
           .putAllParams(new HashMap<String, String>())
           .build();
   ApiFuture<PredictResponse> future =
       predictionServiceClient.predictCallable().futureCall(request);
   // Do something.
   PredictResponse response = future.get();
 }
 

Returns
Type	Description
UnaryCallable<PredictRequest,PredictResponse>

shutdown()

public void shutdown()

shutdownNow()

public void shutdownNow()