Package com.google.cloud.aiplatform.v1beta1.schema.trainingjob.definition

Class AutoMlImageObjectDetectionInputs.Builder

    • Method Detail

      • getDescriptor

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

      • internalGetFieldAccessorTable

        protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()
        Specified by:
        internalGetFieldAccessorTable in class com.google.protobuf.GeneratedMessageV3.Builder<AutoMlImageObjectDetectionInputs.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.GeneratedMessageV3.Builder<AutoMlImageObjectDetectionInputs.Builder>

      • getDefaultInstanceForType

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

      • build

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

      • buildPartial

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

      • isInitialized

        public final boolean isInitialized()
        Specified by:
        isInitialized in interface com.google.protobuf.MessageLiteOrBuilder
        Overrides:
        isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<AutoMlImageObjectDetectionInputs.Builder>

      • getModelTypeValue

        public int getModelTypeValue()
        .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
        Specified by:
        getModelTypeValue in interface AutoMlImageObjectDetectionInputsOrBuilder
        Returns:
        The enum numeric value on the wire for modelType.

      • setModelTypeValue

        public AutoMlImageObjectDetectionInputs.Builder setModelTypeValue​(int value)
        .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.ModelType model_type = 1;
        Parameters:
        value - The enum numeric value on the wire for modelType to set.
        Returns:
        This builder for chaining.

      • clearModelType

        public AutoMlImageObjectDetectionInputs.Builder clearModelType()
        .google.cloud.aiplatform.v1beta1.schema.trainingjob.definition.AutoMlImageObjectDetectionInputs.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.
 For modelType `cloud`(default), the budget must be between 20,000
 and 900,000 milli node hours, inclusive. The default value is 216,000
 which represents one day in wall time, considering 9 nodes are used.
 For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`,
 `mobile-tf-high-accuracy-1`
 the training budget must be between 1,000 and 100,000 milli node hours,
 inclusive. The default value is 24,000 which represents one day in
 wall time on a single node that is used.
        int64 budget_milli_node_hours = 2;
        Specified by:
        getBudgetMilliNodeHours in interface AutoMlImageObjectDetectionInputsOrBuilder
        Returns:
        The budgetMilliNodeHours.

      • setBudgetMilliNodeHours

        public AutoMlImageObjectDetectionInputs.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.
 For modelType `cloud`(default), the budget must be between 20,000
 and 900,000 milli node hours, inclusive. The default value is 216,000
 which represents one day in wall time, considering 9 nodes are used.
 For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`,
 `mobile-tf-high-accuracy-1`
 the training budget must be between 1,000 and 100,000 milli node hours,
 inclusive. The default value is 24,000 which represents one day in
 wall time on a single node that is used.
        int64 budget_milli_node_hours = 2;
        Parameters:
        value - The budgetMilliNodeHours to set.
        Returns:
        This builder for chaining.

      • clearBudgetMilliNodeHours

        public AutoMlImageObjectDetectionInputs.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.
 For modelType `cloud`(default), the budget must be between 20,000
 and 900,000 milli node hours, inclusive. The default value is 216,000
 which represents one day in wall time, considering 9 nodes are used.
 For model types `mobile-tf-low-latency-1`, `mobile-tf-versatile-1`,
 `mobile-tf-high-accuracy-1`
 the training budget must be between 1,000 and 100,000 milli node hours,
 inclusive. The default value is 24,000 which represents one day in
 wall time on a single node that is used.
        int64 budget_milli_node_hours = 2;
        Returns:
        This builder for chaining.

      • getDisableEarlyStopping

        public boolean getDisableEarlyStopping()
         Use the entire training budget. This disables the early stopping feature.
 When false the early stopping feature is enabled, which means that AutoML
 Image Object Detection might stop training before the entire training
 budget has been used.
        bool disable_early_stopping = 3;
        Specified by:
        getDisableEarlyStopping in interface AutoMlImageObjectDetectionInputsOrBuilder
        Returns:
        The disableEarlyStopping.

      • setDisableEarlyStopping

        public AutoMlImageObjectDetectionInputs.Builder setDisableEarlyStopping​(boolean value)
         Use the entire training budget. This disables the early stopping feature.
 When false the early stopping feature is enabled, which means that AutoML
 Image Object Detection might stop training before the entire training
 budget has been used.
        bool disable_early_stopping = 3;
        Parameters:
        value - The disableEarlyStopping to set.
        Returns:
        This builder for chaining.

      • clearDisableEarlyStopping

        public AutoMlImageObjectDetectionInputs.Builder clearDisableEarlyStopping()
         Use the entire training budget. This disables the early stopping feature.
 When false the early stopping feature is enabled, which means that AutoML
 Image Object Detection might stop training before the entire training
 budget has been used.
        bool disable_early_stopping = 3;
        Returns:
        This builder for chaining.