Class StudySpec.ConvexStopConfig.Builder (2.5.3)

Version 2.5.3

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public static final class StudySpec.ConvexStopConfig.Builder extends GeneratedMessageV3.Builder<StudySpec.ConvexStopConfig.Builder> implements StudySpec.ConvexStopConfigOrBuilder

Configuration for ConvexStopPolicy.

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

Inheritance

Object > AbstractMessageLite.Builder<MessageType,BuilderType> > AbstractMessage.Builder<BuilderType> > GeneratedMessageV3.Builder > StudySpec.ConvexStopConfig.Builder

Implements

StudySpec.ConvexStopConfigOrBuilder

Inherited Members

AbstractMessage.Builder.findInitializationErrors()

AbstractMessage.Builder.getInitializationErrorString()

AbstractMessage.Builder.internalMergeFrom(AbstractMessageLite)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream)

AbstractMessage.Builder.mergeDelimitedFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[])

AbstractMessage.Builder.mergeFrom(byte[],ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(byte[],int,int)

AbstractMessage.Builder.mergeFrom(byte[],int,int,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(ByteString)

AbstractMessage.Builder.mergeFrom(ByteString,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(CodedInputStream)

AbstractMessage.Builder.mergeFrom(CodedInputStream,ExtensionRegistryLite)

AbstractMessage.Builder.mergeFrom(Message)

AbstractMessage.Builder.mergeFrom(InputStream)

AbstractMessage.Builder.mergeFrom(InputStream,ExtensionRegistryLite)

AbstractMessage.Builder.newUninitializedMessageException(Message)

AbstractMessage.Builder.toString()

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,Collection<? super T>)

AbstractMessageLite.Builder.<T>addAll(Iterable<T>,List<? super T>)

AbstractMessageLite.Builder.internalMergeFrom(MessageType)

AbstractMessageLite.Builder.mergeFrom(MessageLite)

AbstractMessageLite.Builder.newUninitializedMessageException(MessageLite)

GeneratedMessageV3.Builder.addRepeatedField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.clear()

GeneratedMessageV3.Builder.clearField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.clearOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.clone()

GeneratedMessageV3.Builder.getAllFields()

GeneratedMessageV3.Builder.getDescriptorForType()

GeneratedMessageV3.Builder.getField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getFieldBuilder(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getOneofFieldDescriptor(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.getParentForChildren()

GeneratedMessageV3.Builder.getRepeatedField(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldBuilder(Descriptors.FieldDescriptor,int)

GeneratedMessageV3.Builder.getRepeatedFieldCount(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.getUnknownFields()

GeneratedMessageV3.Builder.hasField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.hasOneof(Descriptors.OneofDescriptor)

GeneratedMessageV3.Builder.internalGetFieldAccessorTable()

GeneratedMessageV3.Builder.internalGetMapField(int)

GeneratedMessageV3.Builder.internalGetMutableMapField(int)

GeneratedMessageV3.Builder.isClean()

GeneratedMessageV3.Builder.isInitialized()

GeneratedMessageV3.Builder.markClean()

GeneratedMessageV3.Builder.mergeUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.newBuilderForField(Descriptors.FieldDescriptor)

GeneratedMessageV3.Builder.onBuilt()

GeneratedMessageV3.Builder.onChanged()

GeneratedMessageV3.Builder.setField(Descriptors.FieldDescriptor,Object)

GeneratedMessageV3.Builder.setRepeatedField(Descriptors.FieldDescriptor,int,Object)

GeneratedMessageV3.Builder.setUnknownFields(UnknownFieldSet)

GeneratedMessageV3.Builder.setUnknownFieldsProto3(UnknownFieldSet)

Object.equals(Object)

Object.finalize()

Object.getClass()

Object.hashCode()

Object.notify()

Object.notifyAll()

Object.wait()

Object.wait(long)

Object.wait(long,int)

Methods

addRepeatedField(Descriptors.FieldDescriptor field, Object value)

public StudySpec.ConvexStopConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.addRepeatedField(Descriptors.FieldDescriptor field, Object value)

build()

public StudySpec.ConvexStopConfig build()

Returns

Type	Description
StudySpec.ConvexStopConfig

buildPartial()

public StudySpec.ConvexStopConfig buildPartial()

Returns

Type	Description
StudySpec.ConvexStopConfig

clear()

public StudySpec.ConvexStopConfig.Builder clear()

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clear()

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

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

clearField(Descriptors.FieldDescriptor field)

public StudySpec.ConvexStopConfig.Builder clearField(Descriptors.FieldDescriptor field)

Parameter

Name	Description
field	FieldDescriptor

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearField(Descriptors.FieldDescriptor field)

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

Type	Description
StudySpec.ConvexStopConfig.Builder	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

Type	Description
StudySpec.ConvexStopConfig.Builder	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

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

clearOneof(Descriptors.OneofDescriptor oneof)

public StudySpec.ConvexStopConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)

Parameter

Name	Description
oneof	OneofDescriptor

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clearOneof(Descriptors.OneofDescriptor oneof)

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

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

clone()

public StudySpec.ConvexStopConfig.Builder clone()

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.clone()

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;

Returns

Type	Description
long	The autoregressiveOrder.

getDefaultInstanceForType()

public StudySpec.ConvexStopConfig getDefaultInstanceForType()

Returns

Type	Description
StudySpec.ConvexStopConfig

getDescriptor()

public static final Descriptors.Descriptor getDescriptor()

Returns

Type	Description
Descriptor

getDescriptorForType()

public Descriptors.Descriptor getDescriptorForType()

Returns

Type	Description
Descriptor

Overrides

GeneratedMessageV3.Builder<BuilderType>.getDescriptorForType()

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;

Returns

Type	Description
String	The learningRateParameterName.

getLearningRateParameterNameBytes()

public 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;

Returns

Type	Description
ByteString	The bytes for learningRateParameterName.

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;

Returns

Type	Description
long	The maxNumSteps.

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;

Returns

Type	Description
long	The minNumSteps.

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;

Returns

Type	Description
boolean	The useSeconds.

internalGetFieldAccessorTable()

protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()

Returns

Type	Description
FieldAccessorTable

Overrides

GeneratedMessageV3.Builder<BuilderType>.internalGetFieldAccessorTable()

isInitialized()

public final boolean isInitialized()

Returns

Type	Description
boolean

Overrides

GeneratedMessageV3.Builder<BuilderType>.isInitialized()

mergeFrom(StudySpec.ConvexStopConfig other)

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

Parameter

Name	Description
other	StudySpec.ConvexStopConfig

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

public StudySpec.ConvexStopConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Parameters

Name	Description
input	CodedInputStream
extensionRegistry	ExtensionRegistryLite

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)

Exceptions

Type	Description
IOException

mergeFrom(Message other)

public StudySpec.ConvexStopConfig.Builder mergeFrom(Message other)

Parameter

Name	Description
other	Message

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

AbstractMessage.Builder<BuilderType>.mergeFrom(Message other)

mergeUnknownFields(UnknownFieldSet unknownFields)

public final StudySpec.ConvexStopConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.mergeUnknownFields(UnknownFieldSet unknownFields)

setAutoregressiveOrder(long value)

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;

Parameter

Name	Description
value	long The autoregressiveOrder to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

setField(Descriptors.FieldDescriptor field, Object value)

public StudySpec.ConvexStopConfig.Builder setField(Descriptors.FieldDescriptor field, Object value)

Parameters

Name	Description
field	FieldDescriptor
value	Object

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setField(Descriptors.FieldDescriptor field, Object value)

setLearningRateParameterName(String value)

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;

Parameter

Name	Description
value	String The learningRateParameterName to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

setLearningRateParameterNameBytes(ByteString value)

public StudySpec.ConvexStopConfig.Builder setLearningRateParameterNameBytes(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;

Parameter

Name	Description
value	ByteString The bytes for learningRateParameterName to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

setMaxNumSteps(long value)

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;

Parameter

Name	Description
value	long The maxNumSteps to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

setMinNumSteps(long value)

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;

Parameter

Name	Description
value	long The minNumSteps to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.

setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

public StudySpec.ConvexStopConfig.Builder setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

Parameters

Name	Description
field	FieldDescriptor
index	int
value	Object

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setRepeatedField(Descriptors.FieldDescriptor field, int index, Object value)

setUnknownFields(UnknownFieldSet unknownFields)

public final StudySpec.ConvexStopConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)

Parameter

Name	Description
unknownFields	UnknownFieldSet

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder

Overrides

GeneratedMessageV3.Builder<BuilderType>.setUnknownFields(UnknownFieldSet unknownFields)

setUseSeconds(boolean value)

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;

Parameter

Name	Description
value	boolean The useSeconds to set.

Returns

Type	Description
StudySpec.ConvexStopConfig.Builder	This builder for chaining.