Class AutoMlImageSegmentationInputs.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<AutoMlImageSegmentationInputs.Builder>
com.google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.Builder
All Implemented Interfaces:
AutoMlImageSegmentationInputsOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
AutoMlImageSegmentationInputs

public static final class AutoMlImageSegmentationInputs.Builder extends com.google.protobuf.GeneratedMessage.Builder<AutoMlImageSegmentationInputs.Builder> implements AutoMlImageSegmentationInputsOrBuilder
Protobuf type google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs
  • 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<AutoMlImageSegmentationInputs.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<AutoMlImageSegmentationInputs.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<AutoMlImageSegmentationInputs.Builder>
    • getDefaultInstanceForType

      public AutoMlImageSegmentationInputs getDefaultInstanceForType()
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder
      Specified by:
      getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder
    • build

      Specified by:
      build in interface com.google.protobuf.Message.Builder
      Specified by:
      build in interface com.google.protobuf.MessageLite.Builder
    • buildPartial

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

      public AutoMlImageSegmentationInputs.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<AutoMlImageSegmentationInputs.Builder>
    • mergeFrom

    • isInitialized

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

      public AutoMlImageSegmentationInputs.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<AutoMlImageSegmentationInputs.Builder>
      Throws:
      IOException
    • getModelTypeValue

      public int getModelTypeValue()
      .google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
      Specified by:
      getModelTypeValue in interface AutoMlImageSegmentationInputsOrBuilder
      Returns:
      The enum numeric value on the wire for modelType.
    • setModelTypeValue

      public AutoMlImageSegmentationInputs.Builder setModelTypeValue(int value)
      .google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
      Parameters:
      value - The enum numeric value on the wire for modelType to set.
      Returns:
      This builder for chaining.
    • getModelType

      .google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
      Specified by:
      getModelType in interface AutoMlImageSegmentationInputsOrBuilder
      Returns:
      The modelType.
    • setModelType

      .google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
      Parameters:
      value - The modelType to set.
      Returns:
      This builder for chaining.
    • clearModelType

      public AutoMlImageSegmentationInputs.Builder clearModelType()
      .google.cloud.aiplatform.v1.schema.trainingjob.definition.AutoMlImageSegmentationInputs.ModelType model_type = 1;
      Returns:
      This builder for chaining.
    • getBudgetMilliNodeHours

      public long getBudgetMilliNodeHours()
       The training budget of creating this model, expressed in milli node
       hours i.e. 1,000 value in this field means 1 node hour. The actual
       metadata.costMilliNodeHours will be equal or less than this value.
       If further model training ceases to provide any improvements, it will
       stop without using the full budget and the metadata.successfulStopReason
       will be `model-converged`.
       Note, node_hour  = actual_hour * number_of_nodes_involved. Or
       actaul_wall_clock_hours = train_budget_milli_node_hours /
       (number_of_nodes_involved * 1000)
       For modelType `cloud-high-accuracy-1`(default), the budget must be between
       20,000 and 2,000,000 milli node hours, inclusive. The default value is
       192,000 which represents one day in wall time
       (1000 milli * 24 hours * 8 nodes).
       
      int64 budget_milli_node_hours = 2;
      Specified by:
      getBudgetMilliNodeHours in interface AutoMlImageSegmentationInputsOrBuilder
      Returns:
      The budgetMilliNodeHours.
    • setBudgetMilliNodeHours

      public AutoMlImageSegmentationInputs.Builder setBudgetMilliNodeHours(long value)
       The training budget of creating this model, expressed in milli node
       hours i.e. 1,000 value in this field means 1 node hour. The actual
       metadata.costMilliNodeHours will be equal or less than this value.
       If further model training ceases to provide any improvements, it will
       stop without using the full budget and the metadata.successfulStopReason
       will be `model-converged`.
       Note, node_hour  = actual_hour * number_of_nodes_involved. Or
       actaul_wall_clock_hours = train_budget_milli_node_hours /
       (number_of_nodes_involved * 1000)
       For modelType `cloud-high-accuracy-1`(default), the budget must be between
       20,000 and 2,000,000 milli node hours, inclusive. The default value is
       192,000 which represents one day in wall time
       (1000 milli * 24 hours * 8 nodes).
       
      int64 budget_milli_node_hours = 2;
      Parameters:
      value - The budgetMilliNodeHours to set.
      Returns:
      This builder for chaining.
    • clearBudgetMilliNodeHours

      public AutoMlImageSegmentationInputs.Builder clearBudgetMilliNodeHours()
       The training budget of creating this model, expressed in milli node
       hours i.e. 1,000 value in this field means 1 node hour. The actual
       metadata.costMilliNodeHours will be equal or less than this value.
       If further model training ceases to provide any improvements, it will
       stop without using the full budget and the metadata.successfulStopReason
       will be `model-converged`.
       Note, node_hour  = actual_hour * number_of_nodes_involved. Or
       actaul_wall_clock_hours = train_budget_milli_node_hours /
       (number_of_nodes_involved * 1000)
       For modelType `cloud-high-accuracy-1`(default), the budget must be between
       20,000 and 2,000,000 milli node hours, inclusive. The default value is
       192,000 which represents one day in wall time
       (1000 milli * 24 hours * 8 nodes).
       
      int64 budget_milli_node_hours = 2;
      Returns:
      This builder for chaining.
    • getBaseModelId

      public String getBaseModelId()
       The ID of the `base` model. If it is specified, the new model will be
       trained based on the `base` model. Otherwise, the new model will be
       trained from scratch. The `base` model must be in the same
       Project and Location as the new Model to train, and have the same
       modelType.
       
      string base_model_id = 3;
      Specified by:
      getBaseModelId in interface AutoMlImageSegmentationInputsOrBuilder
      Returns:
      The baseModelId.
    • getBaseModelIdBytes

      public com.google.protobuf.ByteString getBaseModelIdBytes()
       The ID of the `base` model. If it is specified, the new model will be
       trained based on the `base` model. Otherwise, the new model will be
       trained from scratch. The `base` model must be in the same
       Project and Location as the new Model to train, and have the same
       modelType.
       
      string base_model_id = 3;
      Specified by:
      getBaseModelIdBytes in interface AutoMlImageSegmentationInputsOrBuilder
      Returns:
      The bytes for baseModelId.
    • setBaseModelId

      public AutoMlImageSegmentationInputs.Builder setBaseModelId(String value)
       The ID of the `base` model. If it is specified, the new model will be
       trained based on the `base` model. Otherwise, the new model will be
       trained from scratch. The `base` model must be in the same
       Project and Location as the new Model to train, and have the same
       modelType.
       
      string base_model_id = 3;
      Parameters:
      value - The baseModelId to set.
      Returns:
      This builder for chaining.
    • clearBaseModelId

      public AutoMlImageSegmentationInputs.Builder clearBaseModelId()
       The ID of the `base` model. If it is specified, the new model will be
       trained based on the `base` model. Otherwise, the new model will be
       trained from scratch. The `base` model must be in the same
       Project and Location as the new Model to train, and have the same
       modelType.
       
      string base_model_id = 3;
      Returns:
      This builder for chaining.
    • setBaseModelIdBytes

      public AutoMlImageSegmentationInputs.Builder setBaseModelIdBytes(com.google.protobuf.ByteString value)
       The ID of the `base` model. If it is specified, the new model will be
       trained based on the `base` model. Otherwise, the new model will be
       trained from scratch. The `base` model must be in the same
       Project and Location as the new Model to train, and have the same
       modelType.
       
      string base_model_id = 3;
      Parameters:
      value - The bytes for baseModelId to set.
      Returns:
      This builder for chaining.