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public static final class StudySpec.ConvexStopConfig.Builder extends GeneratedMessageV3.Builder<StudySpec.ConvexStopConfig.Builder> implements StudySpec.ConvexStopConfigOrBuilderConfiguration 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.ConvexStopConfigOrBuilderMethods
addRepeatedField(Descriptors.FieldDescriptor field, Object value)
public StudySpec.ConvexStopConfig.Builder addRepeatedField(Descriptors.FieldDescriptor field, Object value)| Name | Description |
| field | FieldDescriptor |
| value | Object |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder |
build()
public StudySpec.ConvexStopConfig build()| Type | Description |
| StudySpec.ConvexStopConfig |
buildPartial()
public StudySpec.ConvexStopConfig buildPartial()| Type | Description |
| StudySpec.ConvexStopConfig |
clear()
public StudySpec.ConvexStopConfig.Builder clear()| 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;
| Type | Description |
| StudySpec.ConvexStopConfig.Builder | This builder for chaining. |
clearField(Descriptors.FieldDescriptor field)
public StudySpec.ConvexStopConfig.Builder clearField(Descriptors.FieldDescriptor field)| Name | Description |
| field | FieldDescriptor |
| 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;
| 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;
| 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;
| Type | Description |
| StudySpec.ConvexStopConfig.Builder | This builder for chaining. |
clearOneof(Descriptors.OneofDescriptor oneof)
public StudySpec.ConvexStopConfig.Builder clearOneof(Descriptors.OneofDescriptor oneof)| Name | Description |
| oneof | OneofDescriptor |
| 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;
| Type | Description |
| StudySpec.ConvexStopConfig.Builder | This builder for chaining. |
clone()
public StudySpec.ConvexStopConfig.Builder clone()| 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;
| Type | Description |
| long | The autoregressiveOrder. |
getDefaultInstanceForType()
public StudySpec.ConvexStopConfig getDefaultInstanceForType()| Type | Description |
| StudySpec.ConvexStopConfig |
getDescriptor()
public static final Descriptors.Descriptor getDescriptor()| Type | Description |
| Descriptor |
getDescriptorForType()
public Descriptors.Descriptor getDescriptorForType()| 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;
| 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;
| 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;
| 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;
| 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;
| Type | Description |
| boolean | The useSeconds. |
internalGetFieldAccessorTable()
protected GeneratedMessageV3.FieldAccessorTable internalGetFieldAccessorTable()| Type | Description |
| FieldAccessorTable |
isInitialized()
public final boolean isInitialized()| Type | Description |
| boolean |
mergeFrom(StudySpec.ConvexStopConfig other)
public StudySpec.ConvexStopConfig.Builder mergeFrom(StudySpec.ConvexStopConfig other)| Name | Description |
| other | StudySpec.ConvexStopConfig |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder |
mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)
public StudySpec.ConvexStopConfig.Builder mergeFrom(CodedInputStream input, ExtensionRegistryLite extensionRegistry)| Name | Description |
| input | CodedInputStream |
| extensionRegistry | ExtensionRegistryLite |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder |
| Type | Description |
| IOException |
mergeFrom(Message other)
public StudySpec.ConvexStopConfig.Builder mergeFrom(Message other)| Name | Description |
| other | Message |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder |
mergeUnknownFields(UnknownFieldSet unknownFields)
public final StudySpec.ConvexStopConfig.Builder mergeUnknownFields(UnknownFieldSet unknownFields)| Name | Description |
| unknownFields | UnknownFieldSet |
| 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;
| Name | Description |
| value | longThe autoregressiveOrder to set. |
| 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)| Name | Description |
| field | FieldDescriptor |
| value | Object |
| 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;
| Name | Description |
| value | StringThe learningRateParameterName to set. |
| 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;
| Name | Description |
| value | ByteStringThe bytes for learningRateParameterName to set. |
| 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;
| Name | Description |
| value | longThe maxNumSteps to set. |
| 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;
| Name | Description |
| value | longThe minNumSteps to set. |
| 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)| Name | Description |
| field | FieldDescriptor |
| index | int |
| value | Object |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder |
setUnknownFields(UnknownFieldSet unknownFields)
public final StudySpec.ConvexStopConfig.Builder setUnknownFields(UnknownFieldSet unknownFields)| Name | Description |
| unknownFields | UnknownFieldSet |
| 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;
| Name | Description |
| value | booleanThe useSeconds to set. |
| Type | Description |
| StudySpec.ConvexStopConfig.Builder | This builder for chaining. |