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Language	Haskell2010

Backprop.Learn.Model.Neural.LSTM

Contents

LSTM
GRU

Synopsis

lstm :: (KnownNat i, KnownNat o) => Model (Just (LSTMp i o)) (Just (R o :# R o)) (R i) (R o)
data LSTMp (i :: Nat) (o :: Nat) = LSTMp {
- _lstmForget :: !(FCp (i + o) o)
- _lstmInput :: !(FCp (i + o) o)
- _lstmUpdate :: !(FCp (i + o) o)
- _lstmOutput :: !(FCp (i + o) o)
}
lstmForget :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o)
lstmInput :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o)
lstmUpdate :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o)
lstmOutput :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o)
reshapeLSTMpInput :: (ContGen d, PrimMonad m, KnownNat i, KnownNat i', KnownNat o) => d -> Gen (PrimState m) -> LSTMp i o -> m (LSTMp i' o)
reshapeLSTMpOutput :: (ContGen d, PrimMonad m, KnownNat i, KnownNat o, KnownNat o') => d -> Gen (PrimState m) -> LSTMp i o -> m (LSTMp i o')
lstm' :: (KnownNat i, KnownNat o) => Model (Just (LSTMp i o)) (Just (R o)) (R (i + o)) (R o)
gru :: (KnownNat i, KnownNat o) => Model (Just (GRUp i o)) (Just (R o)) (R i) (R o)
data GRUp (i :: Nat) (o :: Nat) = GRUp {
- _gruMemory :: !(FCp (i + o) o)
- _gruUpdate :: !(FCp (i + o) o)
- _gruOutput :: !(FCp (i + o) o)
}
gruMemory :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o)
gruUpdate :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o)
gruOutput :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o)
gru' :: forall i o. (KnownNat i, KnownNat o) => Model (Just (GRUp i o)) Nothing (R (i + o)) (R o)

LSTM

lstm :: (KnownNat i, KnownNat o) => Model (Just (LSTMp i o)) (Just (R o :# R o)) (R i) (R o) Source #

Long-term short-term memory layer

http://colah.github.io/posts/2015-08-Understanding-LSTMs/

data LSTMp (i :: Nat) (o :: Nat) Source #

LSTM layer parmateters

Constructors

LSTMp
Fields _lstmForget :: !(FCp (i + o) o) _lstmInput :: !(FCp (i + o) o) _lstmUpdate :: !(FCp (i + o) o) _lstmOutput :: !(FCp (i + o) o)

Instances

(PrimMonad m, KnownNat i, KnownNat o) => LinearInPlace m Double (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (.+.=) :: Ref m (LSTMp i o) -> LSTMp i o -> m () # (.=) :: Ref m (LSTMp i o) -> Double -> m () # (.+=) :: Ref m (LSTMp i o) -> (Double, LSTMp i o) -> m () #
KnownNat o => Linear Double (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (.+.) :: LSTMp i o -> LSTMp i o -> LSTMp i o # zeroL :: LSTMp i o # (.*) :: Double -> LSTMp i o -> LSTMp i o #
KnownNat o => Metric Double (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (<.>) :: LSTMp i o -> LSTMp i o -> Double # norm_inf :: LSTMp i o -> Double # norm_0 :: LSTMp i o -> Double # norm_1 :: LSTMp i o -> Double # norm_2 :: LSTMp i o -> Double # quadrance :: LSTMp i o -> Double #
(PrimMonad m, KnownNat i, KnownNat o) => Mutable m (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Associated Types type Ref m (LSTMp i o) = (v :: Type) # Methods thawRef :: LSTMp i o -> m (Ref m (LSTMp i o)) # freezeRef :: Ref m (LSTMp i o) -> m (LSTMp i o) # copyRef :: Ref m (LSTMp i o) -> LSTMp i o -> m () # modifyRef :: Ref m (LSTMp i o) -> (LSTMp i o -> LSTMp i o) -> m () # modifyRef' :: Ref m (LSTMp i o) -> (LSTMp i o -> LSTMp i o) -> m () # updateRef :: Ref m (LSTMp i o) -> (LSTMp i o -> (LSTMp i o, b)) -> m b # updateRef' :: Ref m (LSTMp i o) -> (LSTMp i o -> (LSTMp i o, b)) -> m b #
(PrimMonad m, KnownNat i, KnownNat o) => Learnable m (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM
(KnownNat i, KnownNat o) => Floating (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods pi :: LSTMp i o # exp :: LSTMp i o -> LSTMp i o # log :: LSTMp i o -> LSTMp i o # sqrt :: LSTMp i o -> LSTMp i o # (**) :: LSTMp i o -> LSTMp i o -> LSTMp i o # logBase :: LSTMp i o -> LSTMp i o -> LSTMp i o # sin :: LSTMp i o -> LSTMp i o # cos :: LSTMp i o -> LSTMp i o # tan :: LSTMp i o -> LSTMp i o # asin :: LSTMp i o -> LSTMp i o # acos :: LSTMp i o -> LSTMp i o # atan :: LSTMp i o -> LSTMp i o # sinh :: LSTMp i o -> LSTMp i o # cosh :: LSTMp i o -> LSTMp i o # tanh :: LSTMp i o -> LSTMp i o # asinh :: LSTMp i o -> LSTMp i o # acosh :: LSTMp i o -> LSTMp i o # atanh :: LSTMp i o -> LSTMp i o # log1p :: LSTMp i o -> LSTMp i o # expm1 :: LSTMp i o -> LSTMp i o # log1pexp :: LSTMp i o -> LSTMp i o # log1mexp :: LSTMp i o -> LSTMp i o #
(KnownNat i, KnownNat o) => Fractional (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (/) :: LSTMp i o -> LSTMp i o -> LSTMp i o # recip :: LSTMp i o -> LSTMp i o # fromRational :: Rational -> LSTMp i o #
(KnownNat i, KnownNat o) => Num (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (+) :: LSTMp i o -> LSTMp i o -> LSTMp i o # (-) :: LSTMp i o -> LSTMp i o -> LSTMp i o # (*) :: LSTMp i o -> LSTMp i o -> LSTMp i o # negate :: LSTMp i o -> LSTMp i o # abs :: LSTMp i o -> LSTMp i o # signum :: LSTMp i o -> LSTMp i o # fromInteger :: Integer -> LSTMp i o #
KnownNat o => Show (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods showsPrec :: Int -> LSTMp i o -> ShowS # show :: LSTMp i o -> String # showList :: [LSTMp i o] -> ShowS #
Generic (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Associated Types type Rep (LSTMp i o) :: Type -> Type # Methods from :: LSTMp i o -> Rep (LSTMp i o) x # to :: Rep (LSTMp i o) x -> LSTMp i o #
NFData (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods rnf :: LSTMp i o -> () #
KnownNat o => Backprop (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods zero :: LSTMp i o -> LSTMp i o # add :: LSTMp i o -> LSTMp i o -> LSTMp i o # one :: LSTMp i o -> LSTMp i o #
KnownNat o => Binary (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods put :: LSTMp i o -> Put # get :: Get (LSTMp i o) # putList :: [LSTMp i o] -> Put #
KnownNat o => Regularize (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods rnorm_1 :: LSTMp i o -> Double Source # rnorm_2 :: LSTMp i o -> Double Source # lasso :: Double -> LSTMp i o -> LSTMp i o Source # ridge :: Double -> LSTMp i o -> LSTMp i o Source #
(KnownNat i, KnownNat o) => Initialize (LSTMp i o) Source #	Forget biases initialized to 1
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods initialize :: (ContGen d, PrimMonad m) => d -> Gen (PrimState m) -> m (LSTMp i o) Source #
type Ref m (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM type Ref m (LSTMp i o) = GRef m (LSTMp i o)
type Rep (LSTMp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM type Rep (LSTMp i o) = D1 (MetaData "LSTMp" "Backprop.Learn.Model.Neural.LSTM" "backprop-learn-0.1.0.0-LYs2l1OGpKTGmGWQXOoOXm" False) (C1 (MetaCons "LSTMp" PrefixI True) ((S1 (MetaSel (Just "_lstmForget") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)) :: S1 (MetaSel (Just "_lstmInput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o))) :: (S1 (MetaSel (Just "_lstmUpdate") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)) :*: S1 (MetaSel (Just "_lstmOutput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)))))

lstmForget :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o) Source #

lstmInput :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o) Source #

lstmUpdate :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o) Source #

lstmOutput :: forall i o. Lens' (LSTMp i o) (FCp ((+) i o) o) Source #

reshapeLSTMpInput :: (ContGen d, PrimMonad m, KnownNat i, KnownNat i', KnownNat o) => d -> Gen (PrimState m) -> LSTMp i o -> m (LSTMp i' o) Source #

reshapeLSTMpOutput :: (ContGen d, PrimMonad m, KnownNat i, KnownNat o, KnownNat o') => d -> Gen (PrimState m) -> LSTMp i o -> m (LSTMp i o') Source #

lstm' :: (KnownNat i, KnownNat o) => Model (Just (LSTMp i o)) (Just (R o)) (R (i + o)) (R o) Source #

Stateless version of lstm that takes the "previous input" as a part of the input vector.

GRU

gru :: (KnownNat i, KnownNat o) => Model (Just (GRUp i o)) (Just (R o)) (R i) (R o) Source #

Gated Recurrent Unit

http://colah.github.io/posts/2015-08-Understanding-LSTMs/

data GRUp (i :: Nat) (o :: Nat) Source #

GRU layer parmateters

Constructors

GRUp
Fields _gruMemory :: !(FCp (i + o) o) _gruUpdate :: !(FCp (i + o) o) _gruOutput :: !(FCp (i + o) o)

Instances

(KnownNat i, KnownNat o, Mutable m (GRUp i o)) => LinearInPlace m Double (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (.+.=) :: Ref m (GRUp i o) -> GRUp i o -> m () # (.=) :: Ref m (GRUp i o) -> Double -> m () # (.+=) :: Ref m (GRUp i o) -> (Double, GRUp i o) -> m () #
KnownNat o => Linear Double (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (.+.) :: GRUp i o -> GRUp i o -> GRUp i o # zeroL :: GRUp i o # (.*) :: Double -> GRUp i o -> GRUp i o #
KnownNat o => Metric Double (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (<.>) :: GRUp i o -> GRUp i o -> Double # norm_inf :: GRUp i o -> Double # norm_0 :: GRUp i o -> Double # norm_1 :: GRUp i o -> Double # norm_2 :: GRUp i o -> Double # quadrance :: GRUp i o -> Double #
(PrimMonad m, KnownNat i, KnownNat o) => Mutable m (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Associated Types type Ref m (GRUp i o) = (v :: Type) # Methods thawRef :: GRUp i o -> m (Ref m (GRUp i o)) # freezeRef :: Ref m (GRUp i o) -> m (GRUp i o) # copyRef :: Ref m (GRUp i o) -> GRUp i o -> m () # modifyRef :: Ref m (GRUp i o) -> (GRUp i o -> GRUp i o) -> m () # modifyRef' :: Ref m (GRUp i o) -> (GRUp i o -> GRUp i o) -> m () # updateRef :: Ref m (GRUp i o) -> (GRUp i o -> (GRUp i o, b)) -> m b # updateRef' :: Ref m (GRUp i o) -> (GRUp i o -> (GRUp i o, b)) -> m b #
(KnownNat i, KnownNat o, PrimMonad m) => Learnable m (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM
(KnownNat i, KnownNat o) => Floating (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods pi :: GRUp i o # exp :: GRUp i o -> GRUp i o # log :: GRUp i o -> GRUp i o # sqrt :: GRUp i o -> GRUp i o # (**) :: GRUp i o -> GRUp i o -> GRUp i o # logBase :: GRUp i o -> GRUp i o -> GRUp i o # sin :: GRUp i o -> GRUp i o # cos :: GRUp i o -> GRUp i o # tan :: GRUp i o -> GRUp i o # asin :: GRUp i o -> GRUp i o # acos :: GRUp i o -> GRUp i o # atan :: GRUp i o -> GRUp i o # sinh :: GRUp i o -> GRUp i o # cosh :: GRUp i o -> GRUp i o # tanh :: GRUp i o -> GRUp i o # asinh :: GRUp i o -> GRUp i o # acosh :: GRUp i o -> GRUp i o # atanh :: GRUp i o -> GRUp i o # log1p :: GRUp i o -> GRUp i o # expm1 :: GRUp i o -> GRUp i o # log1pexp :: GRUp i o -> GRUp i o # log1mexp :: GRUp i o -> GRUp i o #
(KnownNat i, KnownNat o) => Fractional (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (/) :: GRUp i o -> GRUp i o -> GRUp i o # recip :: GRUp i o -> GRUp i o # fromRational :: Rational -> GRUp i o #
(KnownNat i, KnownNat o) => Num (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods (+) :: GRUp i o -> GRUp i o -> GRUp i o # (-) :: GRUp i o -> GRUp i o -> GRUp i o # (*) :: GRUp i o -> GRUp i o -> GRUp i o # negate :: GRUp i o -> GRUp i o # abs :: GRUp i o -> GRUp i o # signum :: GRUp i o -> GRUp i o # fromInteger :: Integer -> GRUp i o #
KnownNat o => Show (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods showsPrec :: Int -> GRUp i o -> ShowS # show :: GRUp i o -> String # showList :: [GRUp i o] -> ShowS #
Generic (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Associated Types type Rep (GRUp i o) :: Type -> Type # Methods from :: GRUp i o -> Rep (GRUp i o) x # to :: Rep (GRUp i o) x -> GRUp i o #
NFData (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods rnf :: GRUp i o -> () #
KnownNat o => Backprop (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods zero :: GRUp i o -> GRUp i o # add :: GRUp i o -> GRUp i o -> GRUp i o # one :: GRUp i o -> GRUp i o #
KnownNat o => Binary (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods put :: GRUp i o -> Put # get :: Get (GRUp i o) # putList :: [GRUp i o] -> Put #
KnownNat o => Regularize (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods rnorm_1 :: GRUp i o -> Double Source # rnorm_2 :: GRUp i o -> Double Source # lasso :: Double -> GRUp i o -> GRUp i o Source # ridge :: Double -> GRUp i o -> GRUp i o Source #
KnownNat o => Initialize (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM Methods initialize :: (ContGen d, PrimMonad m) => d -> Gen (PrimState m) -> m (GRUp i o) Source #
type Ref m (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM type Ref m (GRUp i o) = GRef m (GRUp i o)
type Rep (GRUp i o) Source #
Instance details Defined in Backprop.Learn.Model.Neural.LSTM type Rep (GRUp i o) = D1 (MetaData "GRUp" "Backprop.Learn.Model.Neural.LSTM" "backprop-learn-0.1.0.0-LYs2l1OGpKTGmGWQXOoOXm" False) (C1 (MetaCons "GRUp" PrefixI True) (S1 (MetaSel (Just "_gruMemory") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)) :: (S1 (MetaSel (Just "_gruUpdate") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)) :: S1 (MetaSel (Just "_gruOutput") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (FCp (i + o) o)))))

gruMemory :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o) Source #

gruUpdate :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o) Source #

gruOutput :: forall i o. Lens' (GRUp i o) (FCp ((+) i o) o) Source #

gru' :: forall i o. (KnownNat i, KnownNat o) => Model (Just (GRUp i o)) Nothing (R (i + o)) (R o) Source #

Stateless version of gru that takes the "previous input" as a part of the input vector.