com.google.cloud.aiplatform.v1beta1

Class StudySpec.ConvexAutomatedStoppingSpec.Builder

java.lang.Object

com.google.protobuf.AbstractMessageLite.Builder

com.google.protobuf.AbstractMessage.Builder<BuilderT>

com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

com.google.cloud.aiplatform.v1beta1.StudySpec.ConvexAutomatedStoppingSpec.Builder

All Implemented Interfaces:

StudySpec.ConvexAutomatedStoppingSpecOrBuilder, com.google.protobuf.Message.Builder, com.google.protobuf.MessageLite.Builder, com.google.protobuf.MessageLiteOrBuilder, com.google.protobuf.MessageOrBuilder, Cloneable

Enclosing class:

StudySpec.ConvexAutomatedStoppingSpec

public static final class StudySpec.ConvexAutomatedStoppingSpec.Builder
extends com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>
implements StudySpec.ConvexAutomatedStoppingSpecOrBuilder

 Configuration for ConvexAutomatedStoppingSpec.
 When there are enough completed trials (configured by
 min_measurement_count), for pending trials with enough measurements and
 steps, the policy first computes an overestimate of the objective value at
 max_num_steps according to the slope of the incomplete objective value
 curve. No prediction can be made if the curve is completely flat. If the
 overestimation is worse than the best objective value of the completed
 trials, this pending trial will be early-stopped, but a last measurement
 will be added to the pending trial with max_num_steps and predicted
 objective value from the autoregression model.
 

Protobuf type google.cloud.aiplatform.v1beta1.StudySpec.ConvexAutomatedStoppingSpec

Method Summary

Modifier and Type	Method and Description
StudySpec.ConvexAutomatedStoppingSpec.Builder	addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
StudySpec.ConvexAutomatedStoppingSpec	build()
StudySpec.ConvexAutomatedStoppingSpec	buildPartial()
StudySpec.ConvexAutomatedStoppingSpec.Builder	clear()
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearField(com.google.protobuf.Descriptors.FieldDescriptor field)
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearLearningRateParameterName() The hyper-parameter name used in the tuning job that stands for learning rate.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearMaxStepCount() Steps used in predicting the final objective for early stopped trials.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearMinMeasurementCount() The minimal number of measurements in a Trial.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearMinStepCount() Minimum number of steps for a trial to complete.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearUpdateAllStoppedTrials() ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clearUseElapsedDuration() This bool determines whether or not the rule is applied based on elapsed_secs or steps.
StudySpec.ConvexAutomatedStoppingSpec.Builder	clone()
StudySpec.ConvexAutomatedStoppingSpec	getDefaultInstanceForType()
static com.google.protobuf.Descriptors.Descriptor	getDescriptor()
com.google.protobuf.Descriptors.Descriptor	getDescriptorForType()
String	getLearningRateParameterName() The hyper-parameter name used in the tuning job that stands for learning rate.
com.google.protobuf.ByteString	getLearningRateParameterNameBytes() The hyper-parameter name used in the tuning job that stands for learning rate.
long	getMaxStepCount() Steps used in predicting the final objective for early stopped trials.
long	getMinMeasurementCount() The minimal number of measurements in a Trial.
long	getMinStepCount() Minimum number of steps for a trial to complete.
boolean	getUpdateAllStoppedTrials() ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model.
boolean	getUseElapsedDuration() This bool determines whether or not the rule is applied based on elapsed_secs or steps.
boolean	hasUpdateAllStoppedTrials() ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model.
protected com.google.protobuf.GeneratedMessageV3.FieldAccessorTable	internalGetFieldAccessorTable()
boolean	isInitialized()
StudySpec.ConvexAutomatedStoppingSpec.Builder	mergeFrom(com.google.protobuf.CodedInputStream input, com.google.protobuf.ExtensionRegistryLite extensionRegistry)
StudySpec.ConvexAutomatedStoppingSpec.Builder	mergeFrom(com.google.protobuf.Message other)
StudySpec.ConvexAutomatedStoppingSpec.Builder	mergeFrom(StudySpec.ConvexAutomatedStoppingSpec other)
StudySpec.ConvexAutomatedStoppingSpec.Builder	mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
StudySpec.ConvexAutomatedStoppingSpec.Builder	setField(com.google.protobuf.Descriptors.FieldDescriptor field, Object value)
StudySpec.ConvexAutomatedStoppingSpec.Builder	setLearningRateParameterName(String value) The hyper-parameter name used in the tuning job that stands for learning rate.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setLearningRateParameterNameBytes(com.google.protobuf.ByteString value) The hyper-parameter name used in the tuning job that stands for learning rate.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setMaxStepCount(long value) Steps used in predicting the final objective for early stopped trials.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setMinMeasurementCount(long value) The minimal number of measurements in a Trial.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setMinStepCount(long value) Minimum number of steps for a trial to complete.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field, int index, Object value)
StudySpec.ConvexAutomatedStoppingSpec.Builder	setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)
StudySpec.ConvexAutomatedStoppingSpec.Builder	setUpdateAllStoppedTrials(boolean value) ConvexAutomatedStoppingSpec by default only updates the trials that needs to be early stopped using a newly trained auto-regressive model.
StudySpec.ConvexAutomatedStoppingSpec.Builder	setUseElapsedDuration(boolean value) This bool determines whether or not the rule is applied based on elapsed_secs or steps.

Methods inherited from class com.google.protobuf.GeneratedMessageV3.Builder

getAllFields, getField, getFieldBuilder, getOneofFieldDescriptor, getParentForChildren, getRepeatedField, getRepeatedFieldBuilder, getRepeatedFieldCount, getUnknownFields, getUnknownFieldSetBuilder, hasField, hasOneof, internalGetMapField, internalGetMapFieldReflection, internalGetMutableMapField, internalGetMutableMapFieldReflection, isClean, markClean, mergeUnknownLengthDelimitedField, mergeUnknownVarintField, newBuilderForField, onBuilt, onChanged, parseUnknownField, setUnknownFieldSetBuilder, setUnknownFieldsProto3

Methods inherited from class com.google.protobuf.AbstractMessage.Builder

findInitializationErrors, getInitializationErrorString, internalMergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, mergeFrom, newUninitializedMessageException, toString

Methods inherited from class com.google.protobuf.AbstractMessageLite.Builder

addAll, addAll, mergeDelimitedFrom, mergeDelimitedFrom, newUninitializedMessageException

Methods inherited from class java.lang.Object

equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Methods inherited from interface com.google.protobuf.MessageOrBuilder

findInitializationErrors, getAllFields, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof

Methods inherited from interface com.google.protobuf.Message.Builder

mergeDelimitedFrom, mergeDelimitedFrom

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<StudySpec.ConvexAutomatedStoppingSpec.Builder>

clear

public StudySpec.ConvexAutomatedStoppingSpec.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.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.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<StudySpec.ConvexAutomatedStoppingSpec.Builder>

getDefaultInstanceForType

public StudySpec.ConvexAutomatedStoppingSpec getDefaultInstanceForType()

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageLiteOrBuilder

Specified by:

getDefaultInstanceForType in interface com.google.protobuf.MessageOrBuilder

build

public StudySpec.ConvexAutomatedStoppingSpec build()

Specified by:

build in interface com.google.protobuf.Message.Builder

Specified by:

build in interface com.google.protobuf.MessageLite.Builder

buildPartial

public StudySpec.ConvexAutomatedStoppingSpec buildPartial()

Specified by:

buildPartial in interface com.google.protobuf.Message.Builder

Specified by:

buildPartial in interface com.google.protobuf.MessageLite.Builder

clone

public StudySpec.ConvexAutomatedStoppingSpec.Builder clone()

Specified by:

clone in interface com.google.protobuf.Message.Builder

Specified by:

clone in interface com.google.protobuf.MessageLite.Builder

Overrides:

clone in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

setField

public StudySpec.ConvexAutomatedStoppingSpec.Builder setField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                              Object value)

Specified by:

setField in interface com.google.protobuf.Message.Builder

Overrides:

setField in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

clearField

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearField(com.google.protobuf.Descriptors.FieldDescriptor field)

Specified by:

clearField in interface com.google.protobuf.Message.Builder

Overrides:

clearField in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

clearOneof

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearOneof(com.google.protobuf.Descriptors.OneofDescriptor oneof)

Specified by:

clearOneof in interface com.google.protobuf.Message.Builder

Overrides:

clearOneof in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

setRepeatedField

public StudySpec.ConvexAutomatedStoppingSpec.Builder setRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                                      int index,
                                                                      Object value)

Specified by:

setRepeatedField in interface com.google.protobuf.Message.Builder

Overrides:

setRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

addRepeatedField

public StudySpec.ConvexAutomatedStoppingSpec.Builder addRepeatedField(com.google.protobuf.Descriptors.FieldDescriptor field,
                                                                      Object value)

Specified by:

addRepeatedField in interface com.google.protobuf.Message.Builder

Overrides:

addRepeatedField in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

mergeFrom

public StudySpec.ConvexAutomatedStoppingSpec.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.ConvexAutomatedStoppingSpec.Builder>

mergeFrom

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

isInitialized

public final boolean isInitialized()

Specified by:

isInitialized in interface com.google.protobuf.MessageLiteOrBuilder

Overrides:

isInitialized in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

mergeFrom

public StudySpec.ConvexAutomatedStoppingSpec.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.ConvexAutomatedStoppingSpec.Builder>

Throws:

IOException

getMaxStepCount

public long getMaxStepCount()

 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. If not defined, it will learn it from the completed trials. When
 use_steps is false, this field is set to the maximum elapsed seconds.
 

int64 max_step_count = 1;

Specified by:

getMaxStepCount in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The maxStepCount.

setMaxStepCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder setMaxStepCount(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. If not defined, it will learn it from the completed trials. When
 use_steps is false, this field is set to the maximum elapsed seconds.
 

int64 max_step_count = 1;

Parameters:

value - The maxStepCount to set.

Returns:

This builder for chaining.

clearMaxStepCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearMaxStepCount()

 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. If not defined, it will learn it from the completed trials. When
 use_steps is false, this field is set to the maximum elapsed seconds.
 

int64 max_step_count = 1;

Returns:

This builder for chaining.

getMinStepCount

public long getMinStepCount()

 Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with step_count > min_step_count 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_step_count is set to be one-tenth of the
 max_step_count.
 When use_elapsed_duration is true, this field is set to the minimum
 elapsed seconds.
 

int64 min_step_count = 2;

Specified by:

getMinStepCount in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The minStepCount.

setMinStepCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder setMinStepCount(long value)

 Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with step_count > min_step_count 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_step_count is set to be one-tenth of the
 max_step_count.
 When use_elapsed_duration is true, this field is set to the minimum
 elapsed seconds.
 

int64 min_step_count = 2;

Parameters:

value - The minStepCount to set.

Returns:

This builder for chaining.

clearMinStepCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearMinStepCount()

 Minimum number of steps for a trial to complete. Trials which do not have
 a measurement with step_count > min_step_count 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_step_count is set to be one-tenth of the
 max_step_count.
 When use_elapsed_duration is true, this field is set to the minimum
 elapsed seconds.
 

int64 min_step_count = 2;

Returns:

This builder for chaining.

getMinMeasurementCount

public long getMinMeasurementCount()

 The minimal number of measurements in a Trial.  Early-stopping checks
 will not trigger if less than min_measurement_count+1 completed trials or
 pending trials with less than min_measurement_count measurements. If not
 defined, the default value is 5.
 

int64 min_measurement_count = 3;

Specified by:

getMinMeasurementCount in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The minMeasurementCount.

setMinMeasurementCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder setMinMeasurementCount(long value)

 The minimal number of measurements in a Trial.  Early-stopping checks
 will not trigger if less than min_measurement_count+1 completed trials or
 pending trials with less than min_measurement_count measurements. If not
 defined, the default value is 5.
 

int64 min_measurement_count = 3;

Parameters:

value - The minMeasurementCount to set.

Returns:

This builder for chaining.

clearMinMeasurementCount

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearMinMeasurementCount()

 The minimal number of measurements in a Trial.  Early-stopping checks
 will not trigger if less than min_measurement_count+1 completed trials or
 pending trials with less than min_measurement_count measurements. If not
 defined, the default value is 5.
 

int64 min_measurement_count = 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.ConvexAutomatedStoppingSpecOrBuilder

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.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The bytes for learningRateParameterName.

setLearningRateParameterName

public StudySpec.ConvexAutomatedStoppingSpec.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.ConvexAutomatedStoppingSpec.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.ConvexAutomatedStoppingSpec.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.

getUseElapsedDuration

public boolean getUseElapsedDuration()

 This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_elapsed_duration==false, the early stopping
 decision is made according to the predicted objective values according to
 the target steps. If use_elapsed_duration==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_elapsed_duration = 5;

Specified by:

getUseElapsedDuration in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The useElapsedDuration.

setUseElapsedDuration

public StudySpec.ConvexAutomatedStoppingSpec.Builder setUseElapsedDuration(boolean value)

 This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_elapsed_duration==false, the early stopping
 decision is made according to the predicted objective values according to
 the target steps. If use_elapsed_duration==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_elapsed_duration = 5;

Parameters:

value - The useElapsedDuration to set.

Returns:

This builder for chaining.

clearUseElapsedDuration

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearUseElapsedDuration()

 This bool determines whether or not the rule is applied based on
 elapsed_secs or steps. If use_elapsed_duration==false, the early stopping
 decision is made according to the predicted objective values according to
 the target steps. If use_elapsed_duration==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_elapsed_duration = 5;

Returns:

This builder for chaining.

hasUpdateAllStoppedTrials

public boolean hasUpdateAllStoppedTrials()

 ConvexAutomatedStoppingSpec by default only updates the trials that needs
 to be early stopped using a newly trained auto-regressive model. When
 this flag is set to True, all stopped trials from the beginning are
 potentially updated in terms of their `final_measurement`. Also, note
 that the training logic of autoregressive models is different in this
 case. Enabling this option has shown better results and this may be the
 default option in the future.
 

optional bool update_all_stopped_trials = 6;

Specified by:

hasUpdateAllStoppedTrials in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

Whether the updateAllStoppedTrials field is set.

getUpdateAllStoppedTrials

public boolean getUpdateAllStoppedTrials()

 ConvexAutomatedStoppingSpec by default only updates the trials that needs
 to be early stopped using a newly trained auto-regressive model. When
 this flag is set to True, all stopped trials from the beginning are
 potentially updated in terms of their `final_measurement`. Also, note
 that the training logic of autoregressive models is different in this
 case. Enabling this option has shown better results and this may be the
 default option in the future.
 

optional bool update_all_stopped_trials = 6;

Specified by:

getUpdateAllStoppedTrials in interface StudySpec.ConvexAutomatedStoppingSpecOrBuilder

Returns:

The updateAllStoppedTrials.

setUpdateAllStoppedTrials

public StudySpec.ConvexAutomatedStoppingSpec.Builder setUpdateAllStoppedTrials(boolean value)

 ConvexAutomatedStoppingSpec by default only updates the trials that needs
 to be early stopped using a newly trained auto-regressive model. When
 this flag is set to True, all stopped trials from the beginning are
 potentially updated in terms of their `final_measurement`. Also, note
 that the training logic of autoregressive models is different in this
 case. Enabling this option has shown better results and this may be the
 default option in the future.
 

optional bool update_all_stopped_trials = 6;

Parameters:

value - The updateAllStoppedTrials to set.

Returns:

This builder for chaining.

clearUpdateAllStoppedTrials

public StudySpec.ConvexAutomatedStoppingSpec.Builder clearUpdateAllStoppedTrials()

 ConvexAutomatedStoppingSpec by default only updates the trials that needs
 to be early stopped using a newly trained auto-regressive model. When
 this flag is set to True, all stopped trials from the beginning are
 potentially updated in terms of their `final_measurement`. Also, note
 that the training logic of autoregressive models is different in this
 case. Enabling this option has shown better results and this may be the
 default option in the future.
 

optional bool update_all_stopped_trials = 6;

Returns:

This builder for chaining.

setUnknownFields

public final StudySpec.ConvexAutomatedStoppingSpec.Builder setUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Specified by:

setUnknownFields in interface com.google.protobuf.Message.Builder

Overrides:

setUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>

mergeUnknownFields

public final StudySpec.ConvexAutomatedStoppingSpec.Builder mergeUnknownFields(com.google.protobuf.UnknownFieldSet unknownFields)

Specified by:

mergeUnknownFields in interface com.google.protobuf.Message.Builder

Overrides:

mergeUnknownFields in class com.google.protobuf.GeneratedMessageV3.Builder<StudySpec.ConvexAutomatedStoppingSpec.Builder>