Package com.google.cloud.visionai.v1

Class VertexCustomConfig.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder>
com.google.cloud.visionai.v1.VertexCustomConfig.Builder
All Implemented Interfaces:
VertexCustomConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
VertexCustomConfig
public static final class VertexCustomConfig.Builder extends com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder> implements VertexCustomConfigOrBuilder
 Message describing VertexCustomConfig.
Protobuf type google.cloud.visionai.v1.VertexCustomConfig

  • Method Details

    • getDescriptor

      public static final com.google.protobuf.Descriptors.Descriptor getDescriptor()

    • internalGetFieldAccessorTable

      protected com.google.protobuf.GeneratedMessage.FieldAccessorTable internalGetFieldAccessorTable()
      Specified by:
      internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder>

    • clear

      public VertexCustomConfig.Builder clear()
      Specified by:
      clear in interface com.google.protobuf.Message.Builder
      Specified by:
      clear in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      clear in class com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder>

    • getDescriptorForType

      public com.google.protobuf.Descriptors.Descriptor getDescriptorForType()
      Specified by:
      getDescriptorForType in interface com.google.protobuf.Message.Builder
      Specified by:
      getDescriptorForType in interface com.google.protobuf.MessageOrBuilder
      Overrides:
      getDescriptorForType in class com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder>

    • getDefaultInstanceForType

      public VertexCustomConfig getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

    • build

      public VertexCustomConfig build()
      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder

    • buildPartial

      public VertexCustomConfig buildPartial()
      Specified by:
      buildPartial in interface com.google.protobuf.Message.Builder
      Specified by:
      buildPartial in interface com.google.protobuf.MessageLite.Builder

    • mergeFrom

      public VertexCustomConfig.Builder mergeFrom(com.google.protobuf.Message other)
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<VertexCustomConfig.Builder>

    • mergeFrom

      public VertexCustomConfig.Builder mergeFrom(VertexCustomConfig other)

    • isInitialized

      public final boolean isInitialized()
      Specified by:
      isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
      Overrides:
      isInitialized in class com.google.protobuf.GeneratedMessage.Builder<VertexCustomConfig.Builder>

    • mergeFrom

      public VertexCustomConfig.Builder mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry) throws IOException
      Specified by:
      mergeFrom in interface com.google.protobuf.Message.Builder
      Specified by:
      mergeFrom in interface com.google.protobuf.MessageLite.Builder
      Overrides:
      mergeFrom in class com.google.protobuf.AbstractMessage.Builder<VertexCustomConfig.Builder>
      Throws:
      IOException

    • getMaxPredictionFps

      public 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;
      Specified by:
      getMaxPredictionFps in interface VertexCustomConfigOrBuilder
      Returns:
      The maxPredictionFps.

    • setMaxPredictionFps

      public VertexCustomConfig.Builder setMaxPredictionFps(int value)
       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;
      Parameters:
      value - The maxPredictionFps to set.
      Returns:
      This builder for chaining.

    • clearMaxPredictionFps

      public VertexCustomConfig.Builder clearMaxPredictionFps()
       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:
      This builder for chaining.

    • hasDedicatedResources

      public 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;
      Specified by:
      hasDedicatedResources in interface VertexCustomConfigOrBuilder
      Returns:
      Whether the dedicatedResources field is set.

    • getDedicatedResources

      public 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;
      Specified by:
      getDedicatedResources in interface VertexCustomConfigOrBuilder
      Returns:
      The dedicatedResources.

    • setDedicatedResources

      public VertexCustomConfig.Builder setDedicatedResources(DedicatedResources value)
       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;

    • setDedicatedResources

      public VertexCustomConfig.Builder setDedicatedResources(DedicatedResources.Builder builderForValue)
       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;

    • mergeDedicatedResources

      public VertexCustomConfig.Builder mergeDedicatedResources(DedicatedResources value)
       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;

    • clearDedicatedResources

      public VertexCustomConfig.Builder clearDedicatedResources()
       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;

    • getDedicatedResourcesBuilder

      public DedicatedResources.Builder getDedicatedResourcesBuilder()
       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;

    • getDedicatedResourcesOrBuilder

      public 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;
      Specified by:
      getDedicatedResourcesOrBuilder in interface VertexCustomConfigOrBuilder

    • getPostProcessingCloudFunction

      public 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;
      Specified by:
      getPostProcessingCloudFunction in interface VertexCustomConfigOrBuilder
      Returns:
      The postProcessingCloudFunction.

    • getPostProcessingCloudFunctionBytes

      public 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;
      Specified by:
      getPostProcessingCloudFunctionBytes in interface VertexCustomConfigOrBuilder
      Returns:
      The bytes for postProcessingCloudFunction.

    • setPostProcessingCloudFunction

      public VertexCustomConfig.Builder setPostProcessingCloudFunction(String value)
       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;
      Parameters:
      value - The postProcessingCloudFunction to set.
      Returns:
      This builder for chaining.

    • clearPostProcessingCloudFunction

      public VertexCustomConfig.Builder clearPostProcessingCloudFunction()
       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:
      This builder for chaining.

    • setPostProcessingCloudFunctionBytes

      public VertexCustomConfig.Builder setPostProcessingCloudFunctionBytes(com.google.protobuf.ByteString value)
       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;
      Parameters:
      value - The bytes for postProcessingCloudFunction to set.
      Returns:
      This builder for chaining.

    • getAttachApplicationMetadata

      public 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;
      Specified by:
      getAttachApplicationMetadata in interface VertexCustomConfigOrBuilder
      Returns:
      The attachApplicationMetadata.

    • setAttachApplicationMetadata

      public VertexCustomConfig.Builder setAttachApplicationMetadata(boolean value)
       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;
      Parameters:
      value - The attachApplicationMetadata to set.
      Returns:
      This builder for chaining.

    • clearAttachApplicationMetadata

      public VertexCustomConfig.Builder clearAttachApplicationMetadata()
       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:
      This builder for chaining.

    • hasDynamicConfigInputTopic

      public 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];
      Specified by:
      hasDynamicConfigInputTopic in interface VertexCustomConfigOrBuilder
      Returns:
      Whether the dynamicConfigInputTopic field is set.

    • getDynamicConfigInputTopic

      public 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];
      Specified by:
      getDynamicConfigInputTopic in interface VertexCustomConfigOrBuilder
      Returns:
      The dynamicConfigInputTopic.

    • getDynamicConfigInputTopicBytes

      public 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];
      Specified by:
      getDynamicConfigInputTopicBytes in interface VertexCustomConfigOrBuilder
      Returns:
      The bytes for dynamicConfigInputTopic.

    • setDynamicConfigInputTopic

      public VertexCustomConfig.Builder setDynamicConfigInputTopic(String value)
       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];
      Parameters:
      value - The dynamicConfigInputTopic to set.
      Returns:
      This builder for chaining.

    • clearDynamicConfigInputTopic

      public VertexCustomConfig.Builder clearDynamicConfigInputTopic()
       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:
      This builder for chaining.

    • setDynamicConfigInputTopicBytes

      public VertexCustomConfig.Builder setDynamicConfigInputTopicBytes(com.google.protobuf.ByteString value)
       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];
      Parameters:
      value - The bytes for dynamicConfigInputTopic to set.
      Returns:
      This builder for chaining.