ran

Documentation

Index

• type Model
  • func New(in, out int) *Model
  • func (m *Model) Forward(xs ...ag.Node) []ag.Node
  • func (m *Model) Importance() [][]mat.Float
  • func (m *Model) LastState() *State
  • func (m *Model) SetInitialState(state *State)
• type State

Types

type Model

type Model struct {
	nn.BaseModel
	WIn     nn.Param `spago:"type:weights"`
	WInRec  nn.Param `spago:"type:weights"`
	BIn     nn.Param `spago:"type:biases"`
	WFor    nn.Param `spago:"type:weights"`
	WForRec nn.Param `spago:"type:weights"`
	BFor    nn.Param `spago:"type:biases"`
	WCand   nn.Param `spago:"type:weights"`
	BCand   nn.Param `spago:"type:biases"`
	States  []*State `spago:"scope:processor"`
}

Model contains the serializable parameters.

func New

func New(in, out int) *Model

New returns a new model with parameters initialized to zeros.

func (*Model) Forward

func (m *Model) Forward(xs ...ag.Node) []ag.Node

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

func (*Model) Importance

func (m *Model) Importance() [][]mat.Float

Importance returns the "importance" score for each element of the processed sequence.

func (*Model) LastState

func (m *Model) LastState() *State

LastState returns the last state of the recurrent network. It returns nil if there are no states.

func (*Model) SetInitialState

func (m *Model) SetInitialState(state *State)

SetInitialState sets the initial state of the recurrent network. It panics if one or more states are already present.

type State

type State struct {
	InG  ag.Node
	ForG ag.Node
	Cand ag.Node
	C    ag.Node
	Y    ag.Node
}

State represent a state of the RAN recurrent network.