Safe Haskell	Safe-Inferred
Language	Haskell2010

Torch.GraduallyTyped.NN.Activation

Synopsis

data Softmax (selectDim :: SelectDim (By Symbol Nat)) where
- Softmax :: forall selectDim. {..} -> Softmax selectDim
data LogSoftmax (selectDim :: SelectDim (By Symbol Nat)) where
- LogSoftmax :: forall selectDim. {..} -> LogSoftmax selectDim
data Relu where
- Relu :: Relu
data Gelu where
- Gelu :: Gelu
data GeluNew where
- GeluNew :: GeluNew
data Tanh where
- Tanh :: Tanh

Documentation

data Softmax (selectDim :: SelectDim (By Symbol Nat)) where Source #

Softmax is a non-linear activation function.

Constructors

Softmax
Fields :: forall selectDim. { softmaxSelectDim :: SSelectDim selectDim } -> Softmax selectDim

Instances

Instances details

Generic (Softmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep (Softmax selectDim) :: Type -> Type Source # Methods from :: Softmax selectDim -> Rep (Softmax selectDim) x Source # to :: Rep (Softmax selectDim) x -> Softmax selectDim Source #
HasStateDict (Softmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec (Softmax selectDim) -> StateDictKey -> m (Softmax selectDim) Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> Softmax selectDim -> m () Source #
HasInitialize (Softmax selectDim) generatorDevice (Softmax selectDim) generatorDevice Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec (Softmax selectDim) -> Generator generatorDevice -> m (Softmax selectDim, Generator generatorDevice) Source #
(shape' ~ SoftmaxF selectDim shape, Catch shape', output ~ Tensor requiresGradient layout device dataType shape') => HasForward (Softmax selectDim) (Tensor requiresGradient layout device dataType shape) generator output generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => Softmax selectDim -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (output, Generator generator) Source #
type Rep (Softmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep (Softmax selectDim) = D1 ('MetaData "Softmax" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "Softmax" 'PrefixI 'True) (S1 ('MetaSel ('Just "softmaxSelectDim") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (SSelectDim selectDim))))
type ModelSpec (Softmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec (Softmax selectDim) = Softmax selectDim

data LogSoftmax (selectDim :: SelectDim (By Symbol Nat)) where Source #

LogSoftmax is a non-linear activation function.

Constructors

LogSoftmax
Fields :: forall selectDim. { logSoftmaxSelectDim :: SSelectDim selectDim } -> LogSoftmax selectDim

Instances

Instances details

Generic (LogSoftmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep (LogSoftmax selectDim) :: Type -> Type Source # Methods from :: LogSoftmax selectDim -> Rep (LogSoftmax selectDim) x Source # to :: Rep (LogSoftmax selectDim) x -> LogSoftmax selectDim Source #
HasStateDict (LogSoftmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec (LogSoftmax selectDim) -> StateDictKey -> m (LogSoftmax selectDim) Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> LogSoftmax selectDim -> m () Source #
HasInitialize (LogSoftmax selectDim) generatorDevice (LogSoftmax selectDim) generatorDevice Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec (LogSoftmax selectDim) -> Generator generatorDevice -> m (LogSoftmax selectDim, Generator generatorDevice) Source #
(shape' ~ SoftmaxF selectDim shape, Catch shape', output ~ Tensor requiresGradient layout device dataType shape') => HasForward (LogSoftmax selectDim) (Tensor requiresGradient layout device dataType shape) generator output generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => LogSoftmax selectDim -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (output, Generator generator) Source #
type Rep (LogSoftmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep (LogSoftmax selectDim) = D1 ('MetaData "LogSoftmax" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "LogSoftmax" 'PrefixI 'True) (S1 ('MetaSel ('Just "logSoftmaxSelectDim") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 (SSelectDim selectDim))))
type ModelSpec (LogSoftmax selectDim) Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec (LogSoftmax selectDim) = LogSoftmax selectDim

data Relu where Source #

Relu is a step-wise linear activation function.

Constructors

Relu :: Relu

Instances

Instances details

Generic Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep Relu :: Type -> Type Source # Methods from :: Relu -> Rep Relu x Source # to :: Rep Relu x -> Relu Source #
Show Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods showsPrec :: Int -> Relu -> ShowS Source # show :: Relu -> String Source # showList :: [Relu] -> ShowS Source #
Eq Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods (==) :: Relu -> Relu -> Bool Source # (/=) :: Relu -> Relu -> Bool Source #
Ord Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods compare :: Relu -> Relu -> Ordering Source # (<) :: Relu -> Relu -> Bool Source # (<=) :: Relu -> Relu -> Bool Source # (>) :: Relu -> Relu -> Bool Source # (>=) :: Relu -> Relu -> Bool Source # max :: Relu -> Relu -> Relu Source # min :: Relu -> Relu -> Relu Source #
HasStateDict Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec Relu -> StateDictKey -> m Relu Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> Relu -> m () Source #
HasInitialize Relu generatorDevice Relu generatorDevice Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec Relu -> Generator generatorDevice -> m (Relu, Generator generatorDevice) Source #
HasForward Relu (Tensor requiresGradient layout device dataType shape) generator (Tensor requiresGradient layout device dataType shape) generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => Relu -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (Tensor requiresGradient layout device dataType shape, Generator generator) Source #
type Rep Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep Relu = D1 ('MetaData "Relu" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "Relu" 'PrefixI 'False) (U1 :: Type -> Type))
type ModelSpec Relu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec Relu = Relu

data Gelu where Source #

Gelu is a non-linear activation function.

Constructors

Gelu :: Gelu

Instances

Instances details

Generic Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep Gelu :: Type -> Type Source # Methods from :: Gelu -> Rep Gelu x Source # to :: Rep Gelu x -> Gelu Source #
Show Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods showsPrec :: Int -> Gelu -> ShowS Source # show :: Gelu -> String Source # showList :: [Gelu] -> ShowS Source #
Eq Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods (==) :: Gelu -> Gelu -> Bool Source # (/=) :: Gelu -> Gelu -> Bool Source #
Ord Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods compare :: Gelu -> Gelu -> Ordering Source # (<) :: Gelu -> Gelu -> Bool Source # (<=) :: Gelu -> Gelu -> Bool Source # (>) :: Gelu -> Gelu -> Bool Source # (>=) :: Gelu -> Gelu -> Bool Source # max :: Gelu -> Gelu -> Gelu Source # min :: Gelu -> Gelu -> Gelu Source #
HasStateDict Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec Gelu -> StateDictKey -> m Gelu Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> Gelu -> m () Source #
HasInitialize Gelu generatorDevice Gelu generatorDevice Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec Gelu -> Generator generatorDevice -> m (Gelu, Generator generatorDevice) Source #
HasForward Gelu (Tensor requiresGradient layout device dataType shape) generator (Tensor requiresGradient layout device dataType shape) generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => Gelu -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (Tensor requiresGradient layout device dataType shape, Generator generator) Source #
type Rep Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep Gelu = D1 ('MetaData "Gelu" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "Gelu" 'PrefixI 'False) (U1 :: Type -> Type))
type ModelSpec Gelu Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec Gelu = Gelu

data GeluNew where Source #

GeluNew is a non-linear activation function. It is a modified version of the Gelu function.

Constructors

GeluNew :: GeluNew

Instances

Instances details

Generic GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep GeluNew :: Type -> Type Source # Methods from :: GeluNew -> Rep GeluNew x Source # to :: Rep GeluNew x -> GeluNew Source #
Show GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods showsPrec :: Int -> GeluNew -> ShowS Source # show :: GeluNew -> String Source # showList :: [GeluNew] -> ShowS Source #
Eq GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods (==) :: GeluNew -> GeluNew -> Bool Source # (/=) :: GeluNew -> GeluNew -> Bool Source #
Ord GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods compare :: GeluNew -> GeluNew -> Ordering Source # (<) :: GeluNew -> GeluNew -> Bool Source # (<=) :: GeluNew -> GeluNew -> Bool Source # (>) :: GeluNew -> GeluNew -> Bool Source # (>=) :: GeluNew -> GeluNew -> Bool Source # max :: GeluNew -> GeluNew -> GeluNew Source # min :: GeluNew -> GeluNew -> GeluNew Source #
HasStateDict GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec GeluNew -> StateDictKey -> m GeluNew Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> GeluNew -> m () Source #
HasInitialize GeluNew generator GeluNew generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec GeluNew -> Generator generator -> m (GeluNew, Generator generator) Source #
HasForward GeluNew (Tensor requiresGradient layout device dataType shape) generator (Tensor requiresGradient layout device dataType shape) generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => GeluNew -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (Tensor requiresGradient layout device dataType shape, Generator generator) Source #
type Rep GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep GeluNew = D1 ('MetaData "GeluNew" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "GeluNew" 'PrefixI 'False) (U1 :: Type -> Type))
type ModelSpec GeluNew Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec GeluNew = GeluNew

data Tanh where Source #

Tanh is a non-linear activation function.

Constructors

Tanh :: Tanh

Instances

Instances details

Generic Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Associated Types type Rep Tanh :: Type -> Type Source # Methods from :: Tanh -> Rep Tanh x Source # to :: Rep Tanh x -> Tanh Source #
Show Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods showsPrec :: Int -> Tanh -> ShowS Source # show :: Tanh -> String Source # showList :: [Tanh] -> ShowS Source #
Eq Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods (==) :: Tanh -> Tanh -> Bool Source # (/=) :: Tanh -> Tanh -> Bool Source #
Ord Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods compare :: Tanh -> Tanh -> Ordering Source # (<) :: Tanh -> Tanh -> Bool Source # (<=) :: Tanh -> Tanh -> Bool Source # (>) :: Tanh -> Tanh -> Bool Source # (>=) :: Tanh -> Tanh -> Bool Source # max :: Tanh -> Tanh -> Tanh Source # min :: Tanh -> Tanh -> Tanh Source #
HasStateDict Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods fromStateDict :: (MonadIO m, MonadThrow m, MonadState StateDict m) => ModelSpec Tanh -> StateDictKey -> m Tanh Source # toStateDict :: (MonadThrow m, MonadState StateDict m) => StateDictKey -> Tanh -> m () Source #
HasInitialize Tanh generator Tanh generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods initialize :: MonadThrow m => ModelSpec Tanh -> Generator generator -> m (Tanh, Generator generator) Source #
HasForward Tanh (Tensor requiresGradient layout device dataType shape) generator (Tensor requiresGradient layout device dataType shape) generator Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation Methods forward :: MonadThrow m => Tanh -> Tensor requiresGradient layout device dataType shape -> Generator generator -> m (Tensor requiresGradient layout device dataType shape, Generator generator) Source #
type Rep Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type Rep Tanh = D1 ('MetaData "Tanh" "Torch.GraduallyTyped.NN.Activation" "hasktorch-gradually-typed-0.2.0.0-1KV1aIPzzbp6JpSr37tC1K" 'False) (C1 ('MetaCons "Tanh" 'PrefixI 'False) (U1 :: Type -> Type))
type ModelSpec Tanh Source #
Instance details Defined in Torch.GraduallyTyped.NN.Activation type ModelSpec Tanh = Tanh