- 3.52.0 (latest)
- 3.50.0
- 3.49.0
- 3.48.0
- 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 interface StudySpec.ConvexStopConfigOrBuilder extends MessageOrBuilder
Implements
MessageOrBuilderMethods
getAutoregressiveOrder()
public abstract 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. |
getLearningRateParameterName()
public abstract 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 abstract 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 abstract 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 abstract 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 abstract 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. |