Class PredictionServiceClient
- All Implemented Interfaces:
BackgroundResource,AutoCloseable
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:
[prediction_type][google.cloud.automl.v1beta1.TablesModelMetadata.prediction_type].
|
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
BatchPredict |
Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.response] field. Available for following ML problems:
|
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Methods that return long-running operations have "Async" method variants that return `OperationFuture`, which is used to track polling of the service.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
See the individual methods for example code.
Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.
This class can be customized by passing in a custom instance of PredictionServiceSettings to create(). For example:
To customize credentials:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
PredictionServiceSettings predictionServiceSettings =
PredictionServiceSettings.newBuilder()
.setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
.build();
PredictionServiceClient predictionServiceClient =
PredictionServiceClient.create(predictionServiceSettings);
To customize the endpoint:
// This snippet has been automatically generated and should be regarded as a code template only.
// It will require modifications to work:
// - It may require correct/in-range values for request initialization.
// - It may require specifying regional endpoints when creating the service client as shown in
// https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
PredictionServiceSettings predictionServiceSettings =
PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
PredictionServiceClient predictionServiceClient =
PredictionServiceClient.create(predictionServiceSettings);
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.
-
Constructor Summary
ConstructorsModifierConstructorDescriptionprotectedConstructs an instance of PredictionServiceClient, using the given settings.protected -
Method Summary
Modifier and TypeMethodDescriptionbooleanawaitTermination(long duration, TimeUnit unit) batchPredictAsync(BatchPredictRequest request) Perform a batch prediction.batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Perform a batch prediction.batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Perform a batch prediction.Perform a batch prediction.Perform a batch prediction.final voidclose()static final PredictionServiceClientcreate()Constructs an instance of PredictionServiceClient with default settings.static final PredictionServiceClientcreate(PredictionServiceSettings settings) Constructs an instance of PredictionServiceClient, using the given settings.static final PredictionServiceClientcreate(PredictionServiceStub stub) Constructs an instance of PredictionServiceClient, using the given stub for making calls.final OperationsClientReturns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.final OperationsClientReturns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call.getStub()booleanbooleanfinal PredictResponsePerform an online prediction.final PredictResponsepredict(PredictRequest request) Perform an online prediction.final PredictResponsePerform an online prediction.Perform an online prediction.voidshutdown()void
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Constructor Details
-
PredictionServiceClient
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.- Throws:
IOException
-
PredictionServiceClient
-
-
Method Details
-
create
Constructs an instance of PredictionServiceClient with default settings.- Throws:
IOException
-
create
public static final PredictionServiceClient create(PredictionServiceSettings settings) throws IOException 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.- Throws:
IOException
-
create
Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings). -
getSettings
-
getStub
-
getOperationsClient
Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call. -
getHttpJsonOperationsClient
Returns the OperationsClient that can be used to query the status of a long-running operation returned by another API method call. -
predict
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][google.cloud.automl.v1beta1.TablesModelMetadata.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- Required. Name of the model requested to serve the prediction.payload- Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.params- 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.
- Throws:
ApiException- if the remote call fails
-
predict
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][google.cloud.automl.v1beta1.TablesModelMetadata.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- Required. Name of the model requested to serve the prediction.payload- Required. Payload to perform a prediction on. The payload must match the problem type that the model was trained to solve.params- 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.
- Throws:
ApiException- if the remote call fails
-
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][google.cloud.automl.v1beta1.TablesModelMetadata.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); }- Parameters:
request- The request object containing all of the parameters for the API call.- Throws:
ApiException- if the remote call fails
-
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][google.cloud.automl.v1beta1.TablesModelMetadata.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(); } -
batchPredictAsync
public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(ModelName name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.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- Required. Name of the model requested to serve the batch prediction.inputConfig- Required. The input configuration for batch prediction.outputConfig- Required. The Configuration specifying where output predictions should be written.params- 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.
- Throws:
ApiException- if the remote call fails
-
batchPredictAsync
public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(String name, BatchPredictInputConfig inputConfig, BatchPredictOutputConfig outputConfig, Map<String, String> params) Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.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- Required. Name of the model requested to serve the batch prediction.inputConfig- Required. The input configuration for batch prediction.outputConfig- Required. The Configuration specifying where output predictions should be written.params- 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.
- Throws:
ApiException- if the remote call fails
-
batchPredictAsync
public final OperationFuture<BatchPredictResult,OperationMetadata> batchPredictAsync(BatchPredictRequest request) Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.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(); }- Parameters:
request- The request object containing all of the parameters for the API call.- Throws:
ApiException- if the remote call fails
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batchPredictOperationCallable
public final OperationCallable<BatchPredictRequest,BatchPredictResult, batchPredictOperationCallable()OperationMetadata> Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.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(); } -
batchPredictCallable
Perform a batch prediction. Unlike the online [Predict][google.cloud.automl.v1beta1.PredictionService.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][google.longrunning.Operations.GetOperation] method. Once the operation is done, [BatchPredictResult][google.cloud.automl.v1beta1.BatchPredictResult] is returned in the [response][google.longrunning.Operation.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(); } -
close
public final void close()- Specified by:
closein interfaceAutoCloseable
-
shutdown
public void shutdown()- Specified by:
shutdownin interfaceBackgroundResource
-
isShutdown
public boolean isShutdown()- Specified by:
isShutdownin interfaceBackgroundResource
-
isTerminated
public boolean isTerminated()- Specified by:
isTerminatedin interfaceBackgroundResource
-
shutdownNow
public void shutdownNow()- Specified by:
shutdownNowin interfaceBackgroundResource
-
awaitTermination
- Specified by:
awaitTerminationin interfaceBackgroundResource- Throws:
InterruptedException
-