Class

org.apache.mxnet.javaapi

RNNParam

Related Doc: package javaapi

Permalink

class RNNParam extends AnyRef

This Param Object is specifically used for RNN

Linear Supertypes
AnyRef, Any
Ordering
  1. Alphabetic
  2. By Inheritance
Inherited
  1. RNNParam
  2. AnyRef
  3. Any
  1. Hide All
  2. Show All
Visibility
  1. Public
  2. All

Instance Constructors

  1. new RNNParam(data: NDArray, parameters: NDArray, state: NDArray, state_cell: NDArray, sequence_length: NDArray, state_size: Integer, num_layers: Integer, mode: String)

    Permalink

    data

    Input data to RNN

    parameters

    Vector of all RNN trainable parameters concatenated

    state

    initial hidden state of the RNN

    state_cell

    initial cell state for LSTM networks (only for LSTM)

    sequence_length

    Vector of valid sequence lengths for each element in batch. (Only used if use_sequence_length kwarg is True)

    state_size

    size of the state for each layer

    num_layers

    number of stacked layers

    mode

    the type of RNN to compute

Value Members

  1. final def !=(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  4. final def asInstanceOf[T0]: T0

    Permalink
    Definition Classes
    Any
  5. def clone(): AnyRef

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  6. final def eq(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  7. def equals(arg0: Any): Boolean

    Permalink
    Definition Classes
    AnyRef → Any
  8. def finalize(): Unit

    Permalink
    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  9. def getBidirectional(): Boolean

    Permalink
  10. final def getClass(): Class[_]

    Permalink
    Definition Classes
    AnyRef → Any
  11. def getData(): NDArray

    Permalink
  12. def getLstm_state_clip_max(): Double

    Permalink
  13. def getLstm_state_clip_min(): Double

    Permalink
  14. def getLstm_state_clip_nan(): Boolean

    Permalink
  15. def getMode(): String

    Permalink
  16. def getNum_layers(): Integer

    Permalink
  17. def getOut(): mxnet.NDArray

    Permalink
  18. def getP(): Float

    Permalink
  19. def getParameters(): NDArray

    Permalink
  20. def getProjection_size(): Integer

    Permalink
  21. def getSequence_length(): NDArray

    Permalink
  22. def getState(): NDArray

    Permalink
  23. def getState_cell(): NDArray

    Permalink
  24. def getState_outputs(): Boolean

    Permalink
  25. def getState_size(): Integer

    Permalink
  26. def getUse_sequence_length(): Boolean

    Permalink
  27. def hashCode(): Int

    Permalink
    Definition Classes
    AnyRef → Any
  28. final def isInstanceOf[T0]: Boolean

    Permalink
    Definition Classes
    Any
  29. final def ne(arg0: AnyRef): Boolean

    Permalink
    Definition Classes
    AnyRef
  30. final def notify(): Unit

    Permalink
    Definition Classes
    AnyRef
  31. final def notifyAll(): Unit

    Permalink
    Definition Classes
    AnyRef
  32. def setBidirectional(bidirectional: Boolean): RNNParam

    Permalink

    bidirectional

    whether to use bidirectional recurrent layers

  33. def setLstm_state_clip_max(lstm_state_clip_max: Double): RNNParam

    Permalink

    lstm_state_clip_max

    Maximum clip value of LSTM states. This option must be used together with lstm_state_clip_min.

  34. def setLstm_state_clip_min(lstm_state_clip_min: Double): RNNParam

    Permalink

    lstm_state_clip_min

    Minimum clip value of LSTM states. This option must be used together with lstm_state_clip_max.

  35. def setLstm_state_clip_nan(lstm_state_clip_nan: Boolean): RNNParam

    Permalink

    lstm_state_clip_nan

    Whether to stop NaN from propagating in state by clipping it to min/max. If clipping range is not specified, this option is ignored.

  36. def setOut(out: NDArray): RNNParam

    Permalink
  37. def setP(p: Float): RNNParam

    Permalink

    p

    drop rate of the dropout on the outputs of each RNN layer, except the last layer.

  38. def setProjection_size(projection_size: Integer): RNNParam

    Permalink

    projection_size

    size of project size

  39. def setState_outputs(state_outputs: Boolean): RNNParam

    Permalink

    state_outputs

    Whether to have the states as symbol outputs.

  40. def setUse_sequence_length(use_sequence_length: Boolean): RNNParam

    Permalink

    use_sequence_length

    If set to true, this layer takes in an extra input parameter sequence_length to specify variable length sequence

  41. final def synchronized[T0](arg0: ⇒ T0): T0

    Permalink
    Definition Classes
    AnyRef
  42. def toString(): String

    Permalink
    Definition Classes
    AnyRef → Any
  43. final def wait(): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  44. final def wait(arg0: Long, arg1: Int): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  45. final def wait(arg0: Long): Unit

    Permalink
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from AnyRef

Inherited from Any

Ungrouped