RNN (DiffSharp)

RNN Type

Namespace: DiffSharp.Model
Assembly: DiffSharp.Core.dll
Base Type: Model

Recurrent neural network.

Constructors

Constructor Description

Constructor	Description
`RNN(inputSize, hiddenSize, ?numLayers, ?nonlinearity, ?bias, ?batchFirst, ?dropout, ?bidirectional)` Full Usage: `RNN(inputSize, hiddenSize, ?numLayers, ?nonlinearity, ?bias, ?batchFirst, ?dropout, ?bidirectional)` Parameters: inputSize : `int` hiddenSize : `int` ?numLayers : `int` ?nonlinearity : `Tensor -> Tensor` ?bias : `bool` ?batchFirst : `bool` ?dropout : `float` ?bidirectional : `bool` Returns: `RNN`	inputSize : `int` hiddenSize : `int` ?numLayers : `int` ?nonlinearity : `Tensor -> Tensor` ?bias : `bool` ?batchFirst : `bool` ?dropout : `float` ?bidirectional : `bool` Returns: `RNN`


                
                  
                    
                      RNN(inputSize, hiddenSize, ?numLayers, ?nonlinearity, ?bias, ?batchFirst, ?dropout, ?bidirectional)

Full Usage: RNN(inputSize, hiddenSize, ?numLayers, ?nonlinearity, ?bias, ?batchFirst, ?dropout, ?bidirectional)

Parameters:

inputSize : int

hiddenSize : int

?numLayers : int

?nonlinearity : Tensor -> Tensor

?bias : bool

?batchFirst : bool

?dropout : float

?bidirectional : bool

Returns: RNN

inputSize : int
hiddenSize : int
?numLayers : int
?nonlinearity : Tensor -> Tensor
?bias : bool
?batchFirst : bool
?dropout : float
?bidirectional : bool

Returns: RNN

Instance members

Instance member	Description
`this.forwardWithHidden (input, hidden)` Full Usage: `this.forwardWithHidden (input, hidden)` Parameters: input : `Tensor` hidden : `Tensor` Returns: `Tensor * Tensor`	input : `Tensor` hidden : `Tensor` Returns: `Tensor * Tensor`
`this.hiddenSize` Full Usage: `this.hiddenSize` Returns: `int`	Returns: `int`
`this.inputSize` Full Usage: `this.inputSize` Returns: `int`	Returns: `int`
`this.newHidden batchSize` Full Usage: `this.newHidden batchSize` Parameters: batchSize : `int` Returns: `Tensor`	batchSize : `int` Returns: `Tensor`