@Deprecated public static interface StudySpec.ConvexStopConfigOrBuilder extends com.google.protobuf.MessageOrBuilder
| Modifier and Type | Method and Description |
|---|---|
long |
getAutoregressiveOrder()
Deprecated.
The number of Trial measurements used in autoregressive model for
value prediction.
|
String |
getLearningRateParameterName()
Deprecated.
The hyper-parameter name used in the tuning job that stands for learning
rate.
|
com.google.protobuf.ByteString |
getLearningRateParameterNameBytes()
Deprecated.
The hyper-parameter name used in the tuning job that stands for learning
rate.
|
long |
getMaxNumSteps()
Deprecated.
Steps used in predicting the final objective for early stopped trials.
|
long |
getMinNumSteps()
Deprecated.
Minimum number of steps for a trial to complete.
|
boolean |
getUseSeconds()
Deprecated.
This bool determines whether or not the rule is applied based on
elapsed_secs or steps.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneoflong 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;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;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;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;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;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;Copyright © 2024 Google LLC. All rights reserved.