Package com.google.cloud.visionai.v1
Interface VertexCustomConfigOrBuilder
- All Superinterfaces:
com.google.protobuf.MessageLiteOrBuilder,com.google.protobuf.MessageOrBuilder
- All Known Implementing Classes:
VertexCustomConfig,VertexCustomConfig.Builder
@Generated
public interface VertexCustomConfigOrBuilder
extends com.google.protobuf.MessageOrBuilder
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Method Summary
Modifier and TypeMethodDescriptionbooleanIf true, the prediction request received by custom model will also contain metadata with the following schema: 'appPlatformMetadata': { 'ingestionTime': DOUBLE; (UNIX timestamp) 'application': STRING; 'instanceId': STRING; 'node': STRING; 'processor': STRING; }A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.Optional.com.google.protobuf.ByteStringOptional.intThe max prediction frame per second.If not empty, the prediction result will be sent to the specified cloud function for post processingcom.google.protobuf.ByteStringIf not empty, the prediction result will be sent to the specified cloud function for post processingbooleanA description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.booleanOptional.Methods inherited from interface com.google.protobuf.MessageLiteOrBuilder
isInitializedMethods inherited from interface com.google.protobuf.MessageOrBuilder
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
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Method Details
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getMaxPredictionFps
int getMaxPredictionFps()The max prediction frame per second. This attribute sets how fast the operator sends prediction requests to Vertex AI endpoint. Default value is 0, which means there is no max prediction fps limit. The operator sends prediction requests at input fps.
int32 max_prediction_fps = 1;- Returns:
- The maxPredictionFps.
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hasDedicatedResources
boolean hasDedicatedResources()A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
.google.cloud.visionai.v1.DedicatedResources dedicated_resources = 2;- Returns:
- Whether the dedicatedResources field is set.
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getDedicatedResources
DedicatedResources getDedicatedResources()A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
.google.cloud.visionai.v1.DedicatedResources dedicated_resources = 2;- Returns:
- The dedicatedResources.
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getDedicatedResourcesOrBuilder
DedicatedResourcesOrBuilder getDedicatedResourcesOrBuilder()A description of resources that are dedicated to the DeployedModel, and that need a higher degree of manual configuration.
.google.cloud.visionai.v1.DedicatedResources dedicated_resources = 2; -
getPostProcessingCloudFunction
String getPostProcessingCloudFunction()If not empty, the prediction result will be sent to the specified cloud function for post processing. * The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of proto PredictResponse. * The cloud function should return AppPlatformCloudFunctionResponse with PredictResponse stored in the annotations field. * To drop the prediction output, simply clear the payload field in the returned AppPlatformCloudFunctionResponse.
string post_processing_cloud_function = 3;- Returns:
- The postProcessingCloudFunction.
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getPostProcessingCloudFunctionBytes
com.google.protobuf.ByteString getPostProcessingCloudFunctionBytes()If not empty, the prediction result will be sent to the specified cloud function for post processing. * The cloud function will receive AppPlatformCloudFunctionRequest where the annotations field will be the json format of proto PredictResponse. * The cloud function should return AppPlatformCloudFunctionResponse with PredictResponse stored in the annotations field. * To drop the prediction output, simply clear the payload field in the returned AppPlatformCloudFunctionResponse.
string post_processing_cloud_function = 3;- Returns:
- The bytes for postProcessingCloudFunction.
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getAttachApplicationMetadata
boolean getAttachApplicationMetadata()If true, the prediction request received by custom model will also contain metadata with the following schema: 'appPlatformMetadata': { 'ingestionTime': DOUBLE; (UNIX timestamp) 'application': STRING; 'instanceId': STRING; 'node': STRING; 'processor': STRING; }bool attach_application_metadata = 4;- Returns:
- The attachApplicationMetadata.
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hasDynamicConfigInputTopic
boolean hasDynamicConfigInputTopic()Optional. By setting the configuration_input_topic, processor will subscribe to given topic, only pub/sub topic is supported now. Example channel: //pubsub.googleapis.com/projects/visionai-testing-stable/topics/test-topic message schema should be: message Message { // The ID of the stream that associates with the application instance. string stream_id = 1; // The target fps. By default, the custom processor will *not* send any data to the Vertex Prediction container. Note that once the dynamic_config_input_topic is set, max_prediction_fps will not work and be preceded by the fps set inside the topic. int32 fps = 2; }optional string dynamic_config_input_topic = 6 [(.google.api.field_behavior) = OPTIONAL];- Returns:
- Whether the dynamicConfigInputTopic field is set.
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getDynamicConfigInputTopic
String getDynamicConfigInputTopic()Optional. By setting the configuration_input_topic, processor will subscribe to given topic, only pub/sub topic is supported now. Example channel: //pubsub.googleapis.com/projects/visionai-testing-stable/topics/test-topic message schema should be: message Message { // The ID of the stream that associates with the application instance. string stream_id = 1; // The target fps. By default, the custom processor will *not* send any data to the Vertex Prediction container. Note that once the dynamic_config_input_topic is set, max_prediction_fps will not work and be preceded by the fps set inside the topic. int32 fps = 2; }optional string dynamic_config_input_topic = 6 [(.google.api.field_behavior) = OPTIONAL];- Returns:
- The dynamicConfigInputTopic.
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getDynamicConfigInputTopicBytes
com.google.protobuf.ByteString getDynamicConfigInputTopicBytes()Optional. By setting the configuration_input_topic, processor will subscribe to given topic, only pub/sub topic is supported now. Example channel: //pubsub.googleapis.com/projects/visionai-testing-stable/topics/test-topic message schema should be: message Message { // The ID of the stream that associates with the application instance. string stream_id = 1; // The target fps. By default, the custom processor will *not* send any data to the Vertex Prediction container. Note that once the dynamic_config_input_topic is set, max_prediction_fps will not work and be preceded by the fps set inside the topic. int32 fps = 2; }optional string dynamic_config_input_topic = 6 [(.google.api.field_behavior) = OPTIONAL];- Returns:
- The bytes for dynamicConfigInputTopic.
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