- 3.48.0 (latest)
- 3.47.0
- 3.46.0
- 3.45.0
- 3.44.0
- 3.43.0
- 3.42.0
- 3.41.0
- 3.40.0
- 3.38.0
- 3.37.0
- 3.36.0
- 3.35.0
- 3.34.0
- 3.33.0
- 3.32.0
- 3.31.0
- 3.30.0
- 3.29.0
- 3.28.0
- 3.25.0
- 3.24.0
- 3.23.0
- 3.22.0
- 3.21.0
- 3.20.0
- 3.19.0
- 3.18.0
- 3.17.0
- 3.16.0
- 3.15.0
- 3.14.0
- 3.13.0
- 3.12.0
- 3.11.0
- 3.10.0
- 3.9.0
- 3.8.0
- 3.7.0
- 3.6.0
- 3.5.0
- 3.4.2
- 3.3.0
- 3.2.0
- 3.0.0
- 2.9.8
- 2.8.9
- 2.7.4
- 2.5.3
- 2.4.0
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.BuilderImplements
StudySpec.ConvexStopConfigOrBuilderStatic Methods
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()
Returns | |
---|---|
Type | Description |
Descriptor |
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 |
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 |
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 |
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 |
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 |
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 |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()
Returns | |
---|---|
Type | Description |
Descriptor |
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 |
isInitialized()
public final boolean isInitialized()
Returns | |
---|---|
Type | Description |
boolean |
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 |
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 |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final StudySpec.ConvexStopConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields |
UnknownFieldSet |
Returns | |
---|---|
Type | Description |
StudySpec.ConvexStopConfig.Builder |
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 |
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 |
setUnknownFields(UnknownFieldSet unknownFields)
public final StudySpec.ConvexStopConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)
Parameter | |
---|---|
Name | Description |
unknownFields |
UnknownFieldSet |
Returns | |
---|---|
Type | Description |
StudySpec.ConvexStopConfig.Builder |
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. |