Package com.google.cloud.aiplatform.v1beta1

Class StudySpec.ConvexStopConfig.Builder

java.lang.Object
com.google.protobuf.AbstractMessageLite.Builder
com.google.protobuf.AbstractMessage.Builder<BuilderT>
com.google.protobuf.GeneratedMessage.Builder<StudySpec.ConvexStopConfig.Builder>
com.google.cloud.aiplatform.v1beta1.StudySpec.ConvexStopConfig.Builder
All Implemented Interfaces:
StudySpec.ConvexStopConfigOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable
Enclosing class:
StudySpec.ConvexStopConfig
public static final class StudySpec.ConvexStopConfig.Builder extends com.google.protobuf.GeneratedMessage.Builder<StudySpec.ConvexStopConfig.Builder> implements StudySpec.ConvexStopConfigOrBuilder
 Configuration for ConvexStopPolicy.
Protobuf type google.cloud.aiplatform.v1beta1.StudySpec.ConvexStopConfig

  • 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<StudySpec.ConvexStopConfig.Builder>

    • clear

      public StudySpec.ConvexStopConfig.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<StudySpec.ConvexStopConfig.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<StudySpec.ConvexStopConfig.Builder>

    • getDefaultInstanceForType

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

    • build

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

    • buildPartial

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

    • mergeFrom

      public StudySpec.ConvexStopConfig.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<StudySpec.ConvexStopConfig.Builder>

    • mergeFrom

      public StudySpec.ConvexStopConfig.Builder mergeFrom(StudySpec.ConvexStopConfig other)

    • isInitialized

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

    • mergeFrom

      public StudySpec.ConvexStopConfig.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<StudySpec.ConvexStopConfig.Builder>
      Throws:
      IOException

    • getMaxNumSteps

      public long getMaxNumSteps()
       Steps used in predicting the final objective for early stopped trials. In
 general, it's set to be the same as the defined steps in training /
 tuning. When use_steps is false, this field is set to the maximum elapsed
 seconds.
      int64 max_num_steps = 1;
      Specified by:
      getMaxNumSteps in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The maxNumSteps.

    • setMaxNumSteps

      public StudySpec.ConvexStopConfig.Builder setMaxNumSteps(long value)
       Steps used in predicting the final objective for early stopped trials. In
 general, it's set to be the same as the defined steps in training /
 tuning. When use_steps is false, this field is set to the maximum elapsed
 seconds.
      int64 max_num_steps = 1;
      Parameters:
      value - The maxNumSteps to set.
      Returns:
      This builder for chaining.

    • clearMaxNumSteps

      public StudySpec.ConvexStopConfig.Builder clearMaxNumSteps()
       Steps used in predicting the final objective for early stopped trials. In
 general, it's set to be the same as the defined steps in training /
 tuning. When use_steps is false, this field is set to the maximum elapsed
 seconds.
      int64 max_num_steps = 1;
      Returns:
      This builder for chaining.

    • getMinNumSteps

      public long getMinNumSteps()
       Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with num_steps > min_num_steps won't be considered for
 early stopping. It's ok to set it to 0, and a trial can be early stopped
 at any stage. By default, min_num_steps is set to be one-tenth of the
 max_num_steps.
 When use_steps is false, this field is set to the minimum elapsed
 seconds.
      int64 min_num_steps = 2;
      Specified by:
      getMinNumSteps in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The minNumSteps.

    • setMinNumSteps

      public StudySpec.ConvexStopConfig.Builder setMinNumSteps(long value)
       Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with num_steps > min_num_steps won't be considered for
 early stopping. It's ok to set it to 0, and a trial can be early stopped
 at any stage. By default, min_num_steps is set to be one-tenth of the
 max_num_steps.
 When use_steps is false, this field is set to the minimum elapsed
 seconds.
      int64 min_num_steps = 2;
      Parameters:
      value - The minNumSteps to set.
      Returns:
      This builder for chaining.

    • clearMinNumSteps

      public StudySpec.ConvexStopConfig.Builder clearMinNumSteps()
       Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with num_steps > min_num_steps won't be considered for
 early stopping. It's ok to set it to 0, and a trial can be early stopped
 at any stage. By default, min_num_steps is set to be one-tenth of the
 max_num_steps.
 When use_steps is false, this field is set to the minimum elapsed
 seconds.
      int64 min_num_steps = 2;
      Returns:
      This builder for chaining.

    • getAutoregressiveOrder

      public long getAutoregressiveOrder()
       The number of Trial measurements used in autoregressive model for
 value prediction. A trial won't be considered early stopping if has fewer
 measurement points.
      int64 autoregressive_order = 3;
      Specified by:
      getAutoregressiveOrder in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The autoregressiveOrder.

    • setAutoregressiveOrder

      public StudySpec.ConvexStopConfig.Builder setAutoregressiveOrder(long value)
       The number of Trial measurements used in autoregressive model for
 value prediction. A trial won't be considered early stopping if has fewer
 measurement points.
      int64 autoregressive_order = 3;
      Parameters:
      value - The autoregressiveOrder to set.
      Returns:
      This builder for chaining.

    • clearAutoregressiveOrder

      public StudySpec.ConvexStopConfig.Builder clearAutoregressiveOrder()
       The number of Trial measurements used in autoregressive model for
 value prediction. A trial won't be considered early stopping if has fewer
 measurement points.
      int64 autoregressive_order = 3;
      Returns:
      This builder for chaining.

    • getLearningRateParameterName

      public String getLearningRateParameterName()
       The hyper-parameter name used in the tuning job that stands for learning
 rate. Leave it blank if learning rate is not in a parameter in tuning.
 The learning_rate is used to estimate the objective value of the ongoing
 trial.
      string learning_rate_parameter_name = 4;
      Specified by:
      getLearningRateParameterName in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The learningRateParameterName.

    • getLearningRateParameterNameBytes

      public com.google.protobuf.ByteString getLearningRateParameterNameBytes()
       The hyper-parameter name used in the tuning job that stands for learning
 rate. Leave it blank if learning rate is not in a parameter in tuning.
 The learning_rate is used to estimate the objective value of the ongoing
 trial.
      string learning_rate_parameter_name = 4;
      Specified by:
      getLearningRateParameterNameBytes in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The bytes for learningRateParameterName.

    • setLearningRateParameterName

      public StudySpec.ConvexStopConfig.Builder setLearningRateParameterName(String value)
       The hyper-parameter name used in the tuning job that stands for learning
 rate. Leave it blank if learning rate is not in a parameter in tuning.
 The learning_rate is used to estimate the objective value of the ongoing
 trial.
      string learning_rate_parameter_name = 4;
      Parameters:
      value - The learningRateParameterName to set.
      Returns:
      This builder for chaining.

    • clearLearningRateParameterName

      public StudySpec.ConvexStopConfig.Builder clearLearningRateParameterName()
       The hyper-parameter name used in the tuning job that stands for learning
 rate. Leave it blank if learning rate is not in a parameter in tuning.
 The learning_rate is used to estimate the objective value of the ongoing
 trial.
      string learning_rate_parameter_name = 4;
      Returns:
      This builder for chaining.

    • setLearningRateParameterNameBytes

      public StudySpec.ConvexStopConfig.Builder setLearningRateParameterNameBytes(com.google.protobuf.ByteString value)
       The hyper-parameter name used in the tuning job that stands for learning
 rate. Leave it blank if learning rate is not in a parameter in tuning.
 The learning_rate is used to estimate the objective value of the ongoing
 trial.
      string learning_rate_parameter_name = 4;
      Parameters:
      value - The bytes for learningRateParameterName to set.
      Returns:
      This builder for chaining.

    • getUseSeconds

      public boolean getUseSeconds()
       This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_seconds==false, the early stopping decision
 is made according to the predicted objective values according to the
 target steps. If use_seconds==true, elapsed_secs is used instead of
 steps. Also, in this case, the parameters max_num_steps and min_num_steps
 are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
      bool use_seconds = 5;
      Specified by:
      getUseSeconds in interface StudySpec.ConvexStopConfigOrBuilder
      Returns:
      The useSeconds.

    • setUseSeconds

      public StudySpec.ConvexStopConfig.Builder setUseSeconds(boolean value)
       This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_seconds==false, the early stopping decision
 is made according to the predicted objective values according to the
 target steps. If use_seconds==true, elapsed_secs is used instead of
 steps. Also, in this case, the parameters max_num_steps and min_num_steps
 are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
      bool use_seconds = 5;
      Parameters:
      value - The useSeconds to set.
      Returns:
      This builder for chaining.

    • clearUseSeconds

      public StudySpec.ConvexStopConfig.Builder clearUseSeconds()
       This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_seconds==false, the early stopping decision
 is made according to the predicted objective values according to the
 target steps. If use_seconds==true, elapsed_secs is used instead of
 steps. Also, in this case, the parameters max_num_steps and min_num_steps
 are overloaded to contain max_elapsed_seconds and min_elapsed_seconds.
      bool use_seconds = 5;
      Returns:
      This builder for chaining.