Safe Haskell | None |
---|---|
Language | Haskell98 |
- trainRecurrent :: forall shapes layers. (SingI (Last shapes), Num (RecurrentInputs layers)) => LearningParameters -> RecurrentNetwork layers shapes -> RecurrentInputs layers -> [(S (Head shapes), Maybe (S (Last shapes)))] -> (RecurrentNetwork layers shapes, RecurrentInputs layers)
- runRecurrent :: RecurrentNetwork layers shapes -> RecurrentInputs layers -> S (Head shapes) -> (RecurrentInputs layers, S (Last shapes))
- backPropagateRecurrent :: forall shapes layers. (SingI (Last shapes), Num (RecurrentInputs layers)) => RecurrentNetwork layers shapes -> RecurrentInputs layers -> [(S (Head shapes), Maybe (S (Last shapes)))] -> (RecurrentGradients layers, RecurrentInputs layers)
Documentation
trainRecurrent :: forall shapes layers. (SingI (Last shapes), Num (RecurrentInputs layers)) => LearningParameters -> RecurrentNetwork layers shapes -> RecurrentInputs layers -> [(S (Head shapes), Maybe (S (Last shapes)))] -> (RecurrentNetwork layers shapes, RecurrentInputs layers) Source #
runRecurrent :: RecurrentNetwork layers shapes -> RecurrentInputs layers -> S (Head shapes) -> (RecurrentInputs layers, S (Last shapes)) Source #
Just forwards propagation with no training.
backPropagateRecurrent :: forall shapes layers. (SingI (Last shapes), Num (RecurrentInputs layers)) => RecurrentNetwork layers shapes -> RecurrentInputs layers -> [(S (Head shapes), Maybe (S (Last shapes)))] -> (RecurrentGradients layers, RecurrentInputs layers) Source #
Drive and network and collect its back propogated gradients.