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💣 Machine learning which might blow up in your face 💣
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123456789101112131415161718192021222324252627282930313233343536{-# LANGUAGE CPP #-}{-# LANGUAGE DataKinds #-}{-# LANGUAGE TypeFamilies #-}{-# LANGUAGE MultiParamTypeClasses #-}{-# LANGUAGE FlexibleContexts #-}{-# LANGUAGE FlexibleInstances #-}module Grenade.Recurrent.Core.Layer ( RecurrentLayer (..) , RecurrentUpdateLayer (..) ) where
#if MIN_VERSION_base(4,9,0)import Data.Kind (Type)#endif
import Grenade.Core
-- | Class for a recurrent layer.-- It's quite similar to a normal layer but for the input and output-- of an extra recurrent data shape.class UpdateLayer x => RecurrentUpdateLayer x where -- | Shape of data that is passed between each subsequent run of the layer type RecurrentShape x :: Type
class (RecurrentUpdateLayer x, Num (RecurrentShape x)) => RecurrentLayer x (i :: Shape) (o :: Shape) where -- | Wengert Tape type RecTape x i o :: Type -- | Used in training and scoring. Take the input from the previous -- layer, and give the output from this layer. runRecurrentForwards :: x -> RecurrentShape x -> S i -> (RecTape x i o, RecurrentShape x, S o) -- | Back propagate a step. Takes the current layer, the input that the -- layer gave from the input and the back propagated derivatives from -- the layer above. -- Returns the gradient layer and the derivatives to push back further. runRecurrentBackwards :: x -> RecTape x i o -> RecurrentShape x -> S o -> (Gradient x, RecurrentShape x, S i)