optim

Type Members

1. class AccuracyResult extends ValidationResult

   

   Represent an accuracy result.

   Represent an accuracy result. Accuracy means a ratio of correct number and total number.

2. class Adadelta[T] extends OptimMethod[T]

   

3. class Adagrad[T] extends OptimMethod[T]

   

   An implementation of Adagrad.

   An implementation of Adagrad. See the original paper: http://jmlr.org/papers/volume12/duchi11a/duchi11a.pdf

   T

   numeric type

4. class Adam[T] extends OptimMethod[T]

   

5. class Adamax[T] extends OptimMethod[T]

   

6. class DistriOptimizer[T] extends Optimizer[T, MiniBatch[T]]

   

   The optimizer run on a distributed cluster.

7. class DistriValidator[T] extends Validator[T, MiniBatch[T]]

   

   Validate model on a distributed cluster.

8. class LBFGS[T] extends OptimMethod[T]

   

   This implementation of L-BFGS relies on a user-provided line search function (state.lineSearch).

   This implementation of L-BFGS relies on a user-provided line search function (state.lineSearch). If this function is not provided, then a simple learningRate is used to produce fixed size steps. Fixed size steps are much less costly than line searches, and can be useful for stochastic problems.

   The learning rate is used even when a line search is provided. This is also useful for large-scale stochastic problems, where opfunc is a noisy approximation of f(x). In that case, the learning rate allows a reduction of confidence in the step size.

9. trait LineSearch[T] extends AnyRef

   

   Line Search strategy

10. class LocalOptimizer[T] extends Optimizer[T, MiniBatch[T]]

    

    Optimize a model on a single machine

11. class LocalValidator[T] extends Validator[T, MiniBatch[T]]

    

    Validate a model on a single machine Use given dataset with certain validation methods such as Top1Accuracy as an argument of its test method

12. class Loss[T] extends ValidationMethod[T]

    

    This evaluation method is calculate loss of output with respect to target

13. class LossResult extends ValidationResult

    

    Use loss as a validation result

14. class Metrics extends Serializable

    

    Performance metrics for the training process.

    Performance metrics for the training process. Beyond collect local metrics(e.g. throughput) in driver node, it can also be used to collect distributed metrics (e.g. time of some steps among the workers). The is useful for performance analysis.

15. trait OptimMethod[T] extends Serializable

    

    Similar to torch Optim method, which is used to update the parameter

16. abstract class Optimizer[T, D] extends AnyRef

    

    Optimizer is an abstract class which is used to train a model automatically with some certain optimization algorithms.

    Optimizer is an abstract class which is used to train a model automatically with some certain optimization algorithms.

    T

    numeric type, which can be Float or Double

    D

    the type of elements in DataSet, such as MiniBatch

17. class Predictor[T] extends Serializable

    

18. class RMSprop[T] extends OptimMethod[T]

    

19. class SGD[T] extends OptimMethod[T]

    

    A plain implementation of SGD

    A plain implementation of SGD

    T

    data type

20. class Top1Accuracy[T] extends ValidationMethod[T]

    

    Caculate the percentage that output's max probability index equals target

21. class Top5Accuracy[T] extends ValidationMethod[T]

    

    Caculate the percentage that target in output's top5 probability indexes

22. trait Trigger extends AnyRef

    

    A trigger specifies a timespot or several timespots during training, and a corresponding action will be taken when the timespot(s) is reached.

23. trait ValidationMethod[T] extends Serializable

    

    A method defined to evaluate the model.

    A method defined to evaluate the model. This trait can be extended by user-defined method. Such as Top1Accuracy

24. trait ValidationResult extends Serializable

    

    A result that calculate the numeric value of a validation method.

    A result that calculate the numeric value of a validation method. User-defined valuation results must override the + operation and result() method. It is executed over the samples in each batch.

25. abstract class Validator[T, D] extends AnyRef

    

    Validator is an abstract class which is used to test a model automatically with some certain validation methods such as Top1Accuracy, as an argument of its test method.

    Validator is an abstract class which is used to test a model automatically with some certain validation methods such as Top1Accuracy, as an argument of its test method.

    T

    numeric type, which can be Float or Double

    D

    the type of elements in DataSet, such as MiniBatch