mist

Documentation

Overview

Implementation of the MIST (MIxed hiSTory) recurrent network as described in "Analyzing and Exploiting NARX Recurrent Neural Networks for Long-Term Dependencies" by Di Pietro et al., 2018 (https://arxiv.org/pdf/1702.07805.pdf).

Index

• type Model
  • func New(in, out, numberOfDelays int) *Model
  • func (m *Model) NewProc(ctx nn.Context) nn.Processor
• type Processor
  • func (p *Processor) Forward(xs ...ag.Node) []ag.Node
  • func (p *Processor) LastState() *State
  • func (p *Processor) SetInitialState(state *State)
• type State

Types

type Model

type Model struct {
	Wx  *nn.Param `type:"weights"`
	Wh  *nn.Param `type:"weights"`
	B   *nn.Param `type:"biases"`
	Wax *nn.Param `type:"weights"`
	Wah *nn.Param `type:"weights"`
	Ba  *nn.Param `type:"biases"`
	Wrx *nn.Param `type:"weights"`
	Wrh *nn.Param `type:"weights"`
	Br  *nn.Param `type:"biases"`
	// contains filtered or unexported fields
}

Model contains the serializable parameters.

func New

func New(in, out, numberOfDelays int) *Model

New returns a new model with parameters initialized to zeros.

func (*Model) NewProc

func (m *Model) NewProc(ctx nn.Context) nn.Processor

NewProc returns a new processor to execute the forward step.

type Processor

type Processor struct {
	nn.BaseProcessor

	States []*State
	// contains filtered or unexported fields
}

func (*Processor) Forward

func (p *Processor) Forward(xs ...ag.Node) []ag.Node

Forward performs the forward step for each input and returns the result.

func (*Processor) LastState

func (p *Processor) LastState() *State

func (*Processor) SetInitialState

func (p *Processor) SetInitialState(state *State)

type State

type State struct {
	Y ag.Node
}