com.intel.analytics.bigdl

optim

package optim

Visibility
  1. Public
  2. All

Type Members

  1. abstract class AbstractOptimizer extends AnyRef

  2. class AccuracyResult extends ValidationResult

    Represent an accuracy result.

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

    Adadelta implementation for SGD: http://arxiv.

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

    An implementation of Adagrad.

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

    An implementation of Adam http://arxiv.

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

    An implementation of Adamax http://arxiv.

  7. class ContiguousResult extends ValidationResult

    A generic result type who's data is contiguous float.

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

    The optimizer run on a distributed cluster.

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

    Validate model on a distributed cluster.

  10. class Evaluator[T] extends Serializable

    model evaluator

  11. class Ftrl[T] extends OptimMethod[T]

    An implementation of Ftrl https://www.

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

    Hit Ratio(HR).

  13. class L1L2Regularizer[T] extends Regularizer[T]

    Apply both L1 and L2 regularization

  14. case class L1Regularizer[T](l1: Double)(implicit evidence$3: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

    Apply L1 regularization

  15. case class L2Regularizer[T](l2: Double)(implicit evidence$4: ClassTag[T], ev: TensorNumeric[T]) extends L1L2Regularizer[T] with Product with Serializable

    Apply L2 regularization

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

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

  17. trait LineSearch[T] extends AnyRef

    Line Search strategy

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

    Optimize a model on a single machine

  19. class LocalPredictor[T] extends Serializable

    Predictor for local data

  20. 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

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

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

  22. class LossResult extends ContiguousResult

    Use loss as a validation result

  23. class MAE[T] extends ValidationMethod[T]

    This evaluation method is calculate mean absolute error of output with respect to target

  24. class Metrics extends Serializable

    Performance metrics for the training process.

  25. class NDCG[T] extends ValidationMethod[T]

    Normalized Discounted Cumulative Gain(NDCG).

  26. trait OptimMethod[T] extends Serializable

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

  27. 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.

  28. class ParallelAdam[T] extends OptimMethod[T]

    An multi-thread implementation of Adam http://arxiv.

  29. class ParallelOptimizer[T] extends Optimizer[T, MiniBatch[T]]

    The optimizer run on a distributed cluster.

  30. class PredictionService[T] extends AnyRef

    In this service, concurrency is kept not greater than numThreads by a BlockingQueue, which contains available model instances.

  31. class Predictor[T] extends Serializable

    Predictor for distributed data

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

    An implementation of RMSprop

  33. trait Regularizer[T] extends Serializable

    It is a trait for all regularizers.

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

    A plain implementation of SGD

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

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

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

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

  37. class TreeNNAccuracy[T] extends ValidationMethod[T]

    This is a metric to measure the accuracy of Tree Neural Network/Recursive Neural Network

  38. trait Trigger extends Serializable

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

  39. trait ValidationMethod[T] extends Serializable

    A method defined to evaluate the model.

  40. trait ValidationResult extends Serializable

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

  41. 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.

Value Members

  1. object DistriOptimizer extends AbstractOptimizer

  2. object DistriValidator

  3. object EvaluateMethods

  4. object Evaluator extends Serializable

  5. object L1L2Regularizer extends Serializable

  6. object LocalOptimizer

  7. object LocalPredictor extends Serializable

  8. object LocalValidator

  9. object OptimMethod extends Serializable

  10. object Optimizer

  11. object ParallelAdam extends Serializable

  12. object ParallelOptimizer extends AbstractOptimizer

  13. object PredictionService

  14. object Predictor extends Serializable

  15. object SGD extends Serializable

  16. object Trigger extends Serializable

Deprecated Value Members

  1. object Validator

    Annotations
    @deprecated
    Deprecated

    (Since version 0.2.0) Validator(model, dataset) is deprecated. Please use model.evaluate instead

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