hasktorch-0.2.0.0: Functional differentiable programming in Haskell
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Torch.Typed.NN.Recurrent.GRU

Synopsis

Documentation

data GRULayerSpec (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) Source #

Constructors

GRULayerSpec 

Instances

Instances details
Show (GRULayerSpec inputSize hiddenSize directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRULayerSpec inputSize hiddenSize directionality dtype device -> ShowS Source #

show :: GRULayerSpec inputSize hiddenSize directionality dtype device -> String Source #

showList :: [GRULayerSpec inputSize hiddenSize directionality dtype device] -> ShowS Source #

Eq (GRULayerSpec inputSize hiddenSize directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

(==) :: GRULayerSpec inputSize hiddenSize directionality dtype device -> GRULayerSpec inputSize hiddenSize directionality dtype device -> Bool Source #

(/=) :: GRULayerSpec inputSize hiddenSize directionality dtype device -> GRULayerSpec inputSize hiddenSize directionality dtype device -> Bool Source #

(RandDTypeIsValid device dtype, KnownNat inputSize, KnownNat hiddenSize, KnownDType dtype, KnownDevice device) => Randomizable (GRULayerSpec inputSize hiddenSize 'Bidirectional dtype device) (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerSpec inputSize hiddenSize 'Bidirectional dtype device -> IO (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source #

(RandDTypeIsValid device dtype, KnownNat inputSize, KnownNat hiddenSize, KnownDType dtype, KnownDevice device) => Randomizable (GRULayerSpec inputSize hiddenSize 'Unidirectional dtype device) (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerSpec inputSize hiddenSize 'Unidirectional dtype device -> IO (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source #

data GRULayer (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) where Source #

Constructors

GRUUnidirectionalLayer :: Parameter device dtype (GRUWIShape hiddenSize inputSize) -> Parameter device dtype (GRUWHShape hiddenSize inputSize) -> Parameter device dtype (GRUBIShape hiddenSize inputSize) -> Parameter device dtype (GRUBHShape hiddenSize inputSize) -> GRULayer inputSize hiddenSize 'Unidirectional dtype device 
GRUBidirectionalLayer :: Parameter device dtype (GRUWIShape hiddenSize inputSize) -> Parameter device dtype (GRUWHShape hiddenSize inputSize) -> Parameter device dtype (GRUBIShape hiddenSize inputSize) -> Parameter device dtype (GRUBHShape hiddenSize inputSize) -> Parameter device dtype (GRUWIShape hiddenSize inputSize) -> Parameter device dtype (GRUWHShape hiddenSize inputSize) -> Parameter device dtype (GRUBIShape hiddenSize inputSize) -> Parameter device dtype (GRUBHShape hiddenSize inputSize) -> GRULayer inputSize hiddenSize 'Bidirectional dtype device 

Instances

Instances details
Show (GRULayer inputSize hiddenSize directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRULayer inputSize hiddenSize directionality dtype device -> ShowS Source #

show :: GRULayer inputSize hiddenSize directionality dtype device -> String Source #

showList :: [GRULayer inputSize hiddenSize directionality dtype device] -> ShowS Source #

Parameterized (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRULayer inputSize hiddenSize 'Bidirectional dtype device) :: [Type] Source #

Methods

flattenParameters :: GRULayer inputSize hiddenSize 'Bidirectional dtype device -> HList (Parameters (GRULayer inputSize hiddenSize 'Bidirectional dtype device)) Source #

replaceParameters :: GRULayer inputSize hiddenSize 'Bidirectional dtype device -> HList (Parameters (GRULayer inputSize hiddenSize 'Bidirectional dtype device)) -> GRULayer inputSize hiddenSize 'Bidirectional dtype device Source #

Parameterized (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRULayer inputSize hiddenSize 'Unidirectional dtype device) :: [Type] Source #

Methods

flattenParameters :: GRULayer inputSize hiddenSize 'Unidirectional dtype device -> HList (Parameters (GRULayer inputSize hiddenSize 'Unidirectional dtype device)) Source #

replaceParameters :: GRULayer inputSize hiddenSize 'Unidirectional dtype device -> HList (Parameters (GRULayer inputSize hiddenSize 'Unidirectional dtype device)) -> GRULayer inputSize hiddenSize 'Unidirectional dtype device Source #

(RandDTypeIsValid device dtype, KnownNat inputSize, KnownNat hiddenSize, KnownDType dtype, KnownDevice device) => Randomizable (GRULayerSpec inputSize hiddenSize 'Bidirectional dtype device) (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerSpec inputSize hiddenSize 'Bidirectional dtype device -> IO (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source #

(RandDTypeIsValid device dtype, KnownNat inputSize, KnownNat hiddenSize, KnownDType dtype, KnownDevice device) => Randomizable (GRULayerSpec inputSize hiddenSize 'Unidirectional dtype device) (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerSpec inputSize hiddenSize 'Unidirectional dtype device -> IO (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source #

type Parameters (GRULayer inputSize hiddenSize 'Bidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRULayer inputSize hiddenSize 'Bidirectional dtype device) = '[Parameter device dtype (GRUWIShape hiddenSize inputSize), Parameter device dtype (GRUWHShape hiddenSize inputSize), Parameter device dtype (GRUBIShape hiddenSize inputSize), Parameter device dtype (GRUBHShape hiddenSize inputSize), Parameter device dtype (GRUWIShape hiddenSize inputSize), Parameter device dtype (GRUWHShape hiddenSize inputSize), Parameter device dtype (GRUBIShape hiddenSize inputSize), Parameter device dtype (GRUBHShape hiddenSize inputSize)]
type Parameters (GRULayer inputSize hiddenSize 'Unidirectional dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRULayer inputSize hiddenSize 'Unidirectional dtype device) = '[Parameter device dtype (GRUWIShape hiddenSize inputSize), Parameter device dtype (GRUWHShape hiddenSize inputSize), Parameter device dtype (GRUBIShape hiddenSize inputSize), Parameter device dtype (GRUBHShape hiddenSize inputSize)]

data GRULayerStackSpec (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) Source #

Constructors

GRULayerStackSpec 

Instances

Instances details
Show (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> ShowS Source #

show :: GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> String Source #

showList :: [GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device] -> ShowS Source #

Eq (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

(==) :: GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> Bool Source #

(/=) :: GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> Bool Source #

(1 <= numLayers, (2 <=? numLayers) ~ flag, RandDTypeIsValid device dtype, KnownDType dtype, KnownDevice device, GRULayerStackRandomizable flag inputSize hiddenSize numLayers directionality dtype device) => Randomizable (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source #

data GRULayerStack (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) where Source #

Constructors

GRULayer1 :: GRULayer inputSize hiddenSize directionality dtype device -> GRULayerStack inputSize hiddenSize 1 directionality dtype device 
GRULayerK :: GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> GRULayerStack inputSize hiddenSize (numLayers + 1) directionality dtype device 

Instances

Instances details
Show (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> ShowS Source #

show :: GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> String Source #

showList :: [GRULayerStack inputSize hiddenSize numLayers directionality dtype device] -> ShowS Source #

(1 <= numLayers, (2 <=? numLayers) ~ flag, GRULayerStackParameterized flag inputSize hiddenSize numLayers directionality dtype device) => Parameterized (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) :: [Type] Source #

Methods

flattenParameters :: GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device)) Source #

replaceParameters :: GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device)) -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device Source #

(1 <= numLayers, (2 <=? numLayers) ~ flag, RandDTypeIsValid device dtype, KnownDType dtype, KnownDevice device, GRULayerStackRandomizable flag inputSize hiddenSize numLayers directionality dtype device) => Randomizable (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source #

type Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) = GRULayerStackParameters (2 <=? numLayers) inputSize hiddenSize numLayers directionality dtype device

class GRULayerStackParameterized (flag :: Bool) inputSize hiddenSize numLayers directionality dtype device where Source #

Associated Types

type GRULayerStackParameters flag inputSize hiddenSize numLayers directionality dtype device :: [Type] Source #

Methods

gruLayerStackFlattenParameters :: Proxy flag -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (GRULayerStackParameters flag inputSize hiddenSize numLayers directionality dtype device) Source #

gruLayerStackReplaceParameters :: Proxy flag -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (GRULayerStackParameters flag inputSize hiddenSize numLayers directionality dtype device) -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device Source #

Instances

Instances details
Parameterized (GRULayer inputSize hiddenSize directionality dtype device) => GRULayerStackParameterized 'False inputSize hiddenSize 1 directionality dtype device Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type GRULayerStackParameters 'False inputSize hiddenSize 1 directionality dtype device :: [Type] Source #

Methods

gruLayerStackFlattenParameters :: Proxy 'False -> GRULayerStack inputSize hiddenSize 1 directionality dtype device -> HList (GRULayerStackParameters 'False inputSize hiddenSize 1 directionality dtype device) Source #

gruLayerStackReplaceParameters :: Proxy 'False -> GRULayerStack inputSize hiddenSize 1 directionality dtype device -> HList (GRULayerStackParameters 'False inputSize hiddenSize 1 directionality dtype device) -> GRULayerStack inputSize hiddenSize 1 directionality dtype device Source #

(Parameterized (GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device), Parameterized (GRULayerStack inputSize hiddenSize (numLayers - 1) directionality dtype device), HAppendFD (Parameters (GRULayerStack inputSize hiddenSize (numLayers - 1) directionality dtype device)) (Parameters (GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device)) (Parameters (GRULayerStack inputSize hiddenSize (numLayers - 1) directionality dtype device) ++ Parameters (GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device))) => GRULayerStackParameterized 'True inputSize hiddenSize numLayers directionality dtype device Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type GRULayerStackParameters 'True inputSize hiddenSize numLayers directionality dtype device :: [Type] Source #

Methods

gruLayerStackFlattenParameters :: Proxy 'True -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (GRULayerStackParameters 'True inputSize hiddenSize numLayers directionality dtype device) Source #

gruLayerStackReplaceParameters :: Proxy 'True -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> HList (GRULayerStackParameters 'True inputSize hiddenSize numLayers directionality dtype device) -> GRULayerStack inputSize hiddenSize numLayers directionality dtype device Source #

class GRULayerStackRandomizable (flag :: Bool) inputSize hiddenSize numLayers directionality dtype device where Source #

Methods

gruLayerStackSample :: Proxy flag -> GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source #

Instances

Instances details
Randomizable (GRULayerSpec inputSize hiddenSize directionality dtype device) (GRULayer inputSize hiddenSize directionality dtype device) => GRULayerStackRandomizable 'False inputSize hiddenSize 1 directionality dtype device Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

gruLayerStackSample :: Proxy 'False -> GRULayerStackSpec inputSize hiddenSize 1 directionality dtype device -> IO (GRULayerStack inputSize hiddenSize 1 directionality dtype device) Source #

(1 <= numLayers, Randomizable (GRULayerSpec (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device) (GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device), Randomizable (GRULayerStackSpec inputSize hiddenSize (numLayers - 1) directionality dtype device) (GRULayerStack inputSize hiddenSize (numLayers - 1) directionality dtype device)) => GRULayerStackRandomizable 'True inputSize hiddenSize numLayers directionality dtype device Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

gruLayerStackSample :: Proxy 'True -> GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) Source #

newtype GRUSpec (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) Source #

Constructors

GRUSpec DropoutSpec 

Instances

Instances details
Generic (GRUSpec inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Rep (GRUSpec inputSize hiddenSize numLayers directionality dtype device) :: Type -> Type Source #

Methods

from :: GRUSpec inputSize hiddenSize numLayers directionality dtype device -> Rep (GRUSpec inputSize hiddenSize numLayers directionality dtype device) x Source #

to :: Rep (GRUSpec inputSize hiddenSize numLayers directionality dtype device) x -> GRUSpec inputSize hiddenSize numLayers directionality dtype device Source #

Show (GRUSpec inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRUSpec inputSize hiddenSize numLayers directionality dtype device -> ShowS Source #

show :: GRUSpec inputSize hiddenSize numLayers directionality dtype device -> String Source #

showList :: [GRUSpec inputSize hiddenSize numLayers directionality dtype device] -> ShowS Source #

(KnownDType dtype, KnownDevice device, KnownNat inputSize, KnownNat hiddenSize, KnownNat (NumberOfDirections directionality), RandDTypeIsValid device dtype, Randomizable (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) (GRULayerStack inputSize hiddenSize numLayers directionality dtype device), 1 <= numLayers) => Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRU inputSize hiddenSize numLayers directionality dtype device) Source #

type Rep (GRUSpec inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Rep (GRUSpec inputSize hiddenSize numLayers directionality dtype device) = D1 ('MetaData "GRUSpec" "Torch.Typed.NN.Recurrent.GRU" "hasktorch-0.2.0.0-F6yFRaDiRF49lpq95SVuR8" 'True) (C1 ('MetaCons "GRUSpec" 'PrefixI 'False) (S1 ('MetaSel ('Nothing :: Maybe Symbol) 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 DropoutSpec)))

data GRU (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) where Source #

Constructors

GRU 

Fields

Instances

Instances details
1 <= numLayers => Generic (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Rep (GRU inputSize hiddenSize numLayers directionality dtype device) :: Type -> Type Source #

Methods

from :: GRU inputSize hiddenSize numLayers directionality dtype device -> Rep (GRU inputSize hiddenSize numLayers directionality dtype device) x Source #

to :: Rep (GRU inputSize hiddenSize numLayers directionality dtype device) x -> GRU inputSize hiddenSize numLayers directionality dtype device Source #

Show (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRU inputSize hiddenSize numLayers directionality dtype device -> ShowS Source #

show :: GRU inputSize hiddenSize numLayers directionality dtype device -> String Source #

showList :: [GRU inputSize hiddenSize numLayers directionality dtype device] -> ShowS Source #

(1 <= numLayers, Parameterized (GRULayerStack inputSize hiddenSize numLayers directionality dtype device), HAppendFD (Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device)) (Parameters Dropout) (Parameters (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) ++ Parameters Dropout)) => Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRU inputSize hiddenSize numLayers directionality dtype device) :: [Type] Source #

Methods

flattenParameters :: GRU inputSize hiddenSize numLayers directionality dtype device -> HList (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device)) Source #

replaceParameters :: GRU inputSize hiddenSize numLayers directionality dtype device -> HList (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device)) -> GRU inputSize hiddenSize numLayers directionality dtype device Source #

(KnownDType dtype, KnownDevice device, KnownNat inputSize, KnownNat hiddenSize, KnownNat (NumberOfDirections directionality), RandDTypeIsValid device dtype, Randomizable (GRULayerStackSpec inputSize hiddenSize numLayers directionality dtype device) (GRULayerStack inputSize hiddenSize numLayers directionality dtype device), 1 <= numLayers) => Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUSpec inputSize hiddenSize numLayers directionality dtype device -> IO (GRU inputSize hiddenSize numLayers directionality dtype device) Source #

type Rep (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Rep (GRU inputSize hiddenSize numLayers directionality dtype device) = Rec0 (GRULayerStack inputSize hiddenSize numLayers directionality dtype device) :*: Rec0 Dropout
type Parameters (GRU inputSize hiddenSize numLayers directionality dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRU inputSize hiddenSize numLayers directionality dtype device) = GParameters (Rep (GRU inputSize hiddenSize numLayers directionality dtype device))

xavierUniformGRU :: forall device dtype hiddenSize featureSize. (KnownDType dtype, KnownNat hiddenSize, KnownNat featureSize, KnownDevice device, RandDTypeIsValid device dtype) => IO (Tensor device dtype '[3 * hiddenSize, featureSize]) Source #

Helper to do xavier uniform initializations on weight matrices and orthagonal initializations for the gates. (When implemented.)

data GRUWithInitSpec (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (dtype :: DType) (device :: (DeviceType, Nat)) where Source #

A specification for a long, short-term memory layer.

Constructors

GRUWithZerosInitSpec :: forall inputSize hiddenSize numLayers directionality dtype device. GRUSpec inputSize hiddenSize numLayers directionality dtype device -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

Weights drawn from Xavier-Uniform with zeros-value initialized biases and cell states.

GRUWithConstInitSpec

Weights drawn from Xavier-Uniform with zeros-value initialized biases and user-provided cell states.

Fields

  • :: forall inputSize hiddenSize numLayers directionality dtype device. GRUSpec inputSize hiddenSize numLayers directionality dtype device
     
  • -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize]

    The initial values of the hidden state

  • -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device
     
GRUWithLearnedInitSpec

Weights drawn from Xavier-Uniform with zeros-value initialized biases and learned cell states.

Fields

  • :: forall inputSize hiddenSize numLayers directionality dtype device. GRUSpec inputSize hiddenSize numLayers directionality dtype device
     
  • -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize]

    The initial (learnable) values of the hidden state

  • -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device
     

Instances

Instances details
Show (GRUWithInitSpec inputSize hiddenSize numLayers directionality initialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRUWithInitSpec inputSize hiddenSize numLayers directionality initialization dtype device -> ShowS Source #

show :: GRUWithInitSpec inputSize hiddenSize numLayers directionality initialization dtype device -> String Source #

showList :: [GRUWithInitSpec inputSize hiddenSize numLayers directionality initialization dtype device] -> ShowS Source #

(KnownNat hiddenSize, KnownNat numLayers, KnownNat (NumberOfDirections directionality), KnownDType dtype, KnownDevice device, Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device)) => Randomizable (GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device -> IO (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source #

(KnownNat hiddenSize, KnownNat numLayers, KnownNat (NumberOfDirections directionality), KnownDType dtype, KnownDevice device, Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device)) => Randomizable (GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device -> IO (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source #

data GRUWithInit (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (dtype :: DType) (device :: (DeviceType, Nat)) where Source #

A long, short-term memory layer with either fixed initial states for the memory cells and hidden state or learnable inital states for the memory cells and hidden state.

Constructors

GRUWithConstInit 

Fields

GRUWithLearnedInit 

Fields

Instances

Instances details
Generic (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) :: Type -> Type Source #

Methods

from :: GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device -> Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) x Source #

to :: Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) x -> GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device Source #

Generic (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) :: Type -> Type Source #

Methods

from :: GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device -> Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) x Source #

to :: Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) x -> GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device Source #

Show (GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

showsPrec :: Int -> GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> ShowS Source #

show :: GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> String Source #

showList :: [GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device] -> ShowS Source #

(Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device), HAppendFD (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device)) ('[] :: [Type]) (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device) ++ ('[] :: [Type]))) => Parameterized (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) :: [Type] Source #

Methods

flattenParameters :: GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device -> HList (Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device)) Source #

replaceParameters :: GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device -> HList (Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device)) -> GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device Source #

(Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device), HAppendFD (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device)) '[Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize]] (Parameters (GRU inputSize hiddenSize numLayers directionality dtype device) ++ '[Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize]])) => Parameterized (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Associated Types

type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) :: [Type] Source #

Methods

flattenParameters :: GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device -> HList (Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device)) Source #

replaceParameters :: GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device -> HList (Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device)) -> GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device Source #

(KnownNat hiddenSize, KnownNat numLayers, KnownNat (NumberOfDirections directionality), KnownDType dtype, KnownDevice device, Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device)) => Randomizable (GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device -> IO (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source #

(KnownNat hiddenSize, KnownNat numLayers, KnownNat (NumberOfDirections directionality), KnownDType dtype, KnownDevice device, Randomizable (GRUSpec inputSize hiddenSize numLayers directionality dtype device) (GRU inputSize hiddenSize numLayers directionality dtype device)) => Randomizable (GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

Methods

sample :: GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device -> IO (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source #

type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) = Rec0 (GRU inputSize hiddenSize numLayers directionality dtype device) :*: Rec0 (Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize])
type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) = Rec0 (GRU inputSize hiddenSize numLayers directionality dtype device) :*: Rec0 (Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize])
type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device) = GParameters (Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device))
type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) Source # 
Instance details

Defined in Torch.Typed.NN.Recurrent.GRU

type Parameters (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device) = GParameters (Rep (GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device))

gruForward :: forall shapeOrder batchSize seqLen directionality initialization numLayers inputSize outputSize hiddenSize inputShape outputShape hcShape parameters tensorParameters dtype device. (KnownNat (NumberOfDirections directionality), KnownNat numLayers, KnownNat batchSize, KnownNat hiddenSize, KnownRNNShapeOrder shapeOrder, KnownRNNDirectionality directionality, outputSize ~ (hiddenSize * NumberOfDirections directionality), inputShape ~ RNNShape shapeOrder seqLen batchSize inputSize, outputShape ~ RNNShape shapeOrder seqLen batchSize outputSize, hcShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (GRU inputSize hiddenSize numLayers directionality dtype device), Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ GRUR inputSize hiddenSize numLayers directionality dtype device, Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => Bool -> GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hcShape) Source #

gruForwardWithDropout :: forall shapeOrder batchSize seqLen directionality initialization numLayers inputSize outputSize hiddenSize inputShape outputShape hcShape parameters tensorParameters dtype device. (KnownNat (NumberOfDirections directionality), KnownNat numLayers, KnownNat batchSize, KnownNat hiddenSize, KnownRNNShapeOrder shapeOrder, KnownRNNDirectionality directionality, outputSize ~ (hiddenSize * NumberOfDirections directionality), inputShape ~ RNNShape shapeOrder seqLen batchSize inputSize, outputShape ~ RNNShape shapeOrder seqLen batchSize outputSize, hcShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (GRU inputSize hiddenSize numLayers directionality dtype device), Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ GRUR inputSize hiddenSize numLayers directionality dtype device, Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hcShape) Source #

Forward propagate the GRU module (without applying dropout on the outputs of each layer).

>>> input :: CPUTensor 'D.Float '[5,16,10] <- randn
>>> spec = GRUWithZerosInitSpec @10 @30 @3 @'Bidirectional @'D.Float @'( 'D.CPU, 0) (GRUSpec (DropoutSpec 0.5))
>>> model <- A.sample spec
>>> :t gruForwardWithoutDropout @'BatchFirst model input
gruForwardWithoutDropout @'BatchFirst model input
  :: (Tensor '( 'D.CPU, 0) 'D.Float '[5, 16, 60],
      Tensor '( 'D.CPU, 0) 'D.Float '[6, 5, 30])
>>> (a,b) = gruForwardWithoutDropout @'BatchFirst model input
>>> ((dtype a, shape a), (dtype b, shape b))
((Float,[5,16,60]),(Float,[6,5,30]))

Forward propagate the GRU module and apply dropout on the outputs of each layer.

>>> input :: CPUTensor 'D.Float '[5,16,10] <- randn
>>> spec = GRUWithZerosInitSpec @10 @30 @3 @'Bidirectional @'D.Float @'( 'D.CPU, 0) (GRUSpec (DropoutSpec 0.5))
>>> model <- A.sample spec
>>> :t gruForwardWithDropout @'BatchFirst model input
gruForwardWithDropout @'BatchFirst model input
  :: (Tensor '( 'D.CPU, 0) 'D.Float '[5, 16, 60],
      Tensor '( 'D.CPU, 0) 'D.Float '[6, 5, 30])
>>> (a,b) = gruForwardWithDropout @'BatchFirst model input
>>> ((dtype a, shape a), (dtype b, shape b))
((Float,[5,16,60]),(Float,[6,5,30]))

gruForwardWithoutDropout :: forall shapeOrder batchSize seqLen directionality initialization numLayers inputSize outputSize hiddenSize inputShape outputShape hcShape parameters tensorParameters dtype device. (KnownNat (NumberOfDirections directionality), KnownNat numLayers, KnownNat batchSize, KnownNat hiddenSize, KnownRNNShapeOrder shapeOrder, KnownRNNDirectionality directionality, outputSize ~ (hiddenSize * NumberOfDirections directionality), inputShape ~ RNNShape shapeOrder seqLen batchSize inputSize, outputShape ~ RNNShape shapeOrder seqLen batchSize outputSize, hcShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (GRU inputSize hiddenSize numLayers directionality dtype device), Parameterized (GRU inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ GRUR inputSize hiddenSize numLayers directionality dtype device, Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => GRUWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hcShape) Source #

Forward propagate the GRU module and apply dropout on the outputs of each layer.

>>> input :: CPUTensor 'D.Float '[5,16,10] <- randn
>>> spec = GRUWithZerosInitSpec @10 @30 @3 @'Bidirectional @'D.Float @'( 'D.CPU, 0) (GRUSpec (DropoutSpec 0.5))
>>> model <- A.sample spec
>>> :t gruForwardWithDropout @'BatchFirst model input
gruForwardWithDropout @'BatchFirst model input
  :: (Tensor '( 'D.CPU, 0) 'D.Float '[5, 16, 60],
      Tensor '( 'D.CPU, 0) 'D.Float '[6, 5, 30])
>>> (a,b) = gruForwardWithDropout @'BatchFirst model input
>>> ((dtype a, shape a), (dtype b, shape b))
((Float,[5,16,60]),(Float,[6,5,30]))