hasktorch 0.2.1.1 → 0.2.1.2

+ Torch.Data.CsvDatastream: ($dmparseNamedRecord) :: (FromNamedRecord a, Generic a, GFromNamedRecord (Rep a)) => NamedRecord -> Parser a

+ Torch.Data.CsvDatastream: ($dmparseRecord) :: (FromRecord a, Generic a, GFromRecord (Rep a)) => Record -> Parser a

+ Torch.Data.StreamedPipeline: type StM (m :: Type -> Type) a;

+ Torch.Lens: ($dmtypes_) :: (HasTypes s a, Generic s, GHasTypes (Rep s) a) => Traversal' s a

+ Torch.Lens: type Traversal s t a b = forall (f :: Type -> Type). Applicative f => a -> f b -> s -> f t

+ Torch.NN: ($dm_replaceParameters) :: (Parameterized f, Generic f, GParameterized (Rep f)) => f -> ParamStream f

+ Torch.NN: ($dmflattenParameters) :: (Parameterized f, Generic f, GParameterized (Rep f)) => f -> [Parameter]

+ Torch.NN: ($dmforward) :: (HasForward f a b, Generic f, Generic a, Generic b, GHasForward (Rep f) (Rep a) (Rep b)) => f -> a -> b

+ Torch.NN: ($dmforwardStoch) :: (HasForward f a b, Generic f, Generic a, Generic b, GHasForward (Rep f) (Rep a) (Rep b)) => f -> a -> IO b

+ Torch.NN: [bias] :: InstanceNorm -> Parameter

+ Torch.NN: [in_features] :: LinearSpec -> Int

+ Torch.NN: [inputChannelSize1d] :: Conv1dSpec -> Int

+ Torch.NN: [inputChannelSize2d] :: Conv2dSpec -> Int

+ Torch.NN: [inputChannelSize3d] :: Conv3dSpec -> Int

+ Torch.NN: [kernelDepth3d] :: Conv3dSpec -> Int

+ Torch.NN: [kernelHeight2d] :: Conv2dSpec -> Int

+ Torch.NN: [kernelHeight3d] :: Conv3dSpec -> Int

+ Torch.NN: [kernelSize] :: Conv1dSpec -> Int

+ Torch.NN: [kernelWidth2d] :: Conv2dSpec -> Int

+ Torch.NN: [kernelWidth3d] :: Conv3dSpec -> Int

+ Torch.NN: [numFeatures] :: InstanceNormSpec -> Int

+ Torch.NN: [out_features] :: LinearSpec -> Int

+ Torch.NN: [outputChannelSize1d] :: Conv1dSpec -> Int

+ Torch.NN: [outputChannelSize2d] :: Conv2dSpec -> Int

+ Torch.NN: [outputChannelSize3d] :: Conv3dSpec -> Int

+ Torch.NN: [runningMean] :: InstanceNorm -> MutableTensor

+ Torch.NN: [runningVar] :: InstanceNorm -> MutableTensor

+ Torch.NN: [trInputChannelSize1d] :: ConvTranspose1dSpec -> Int

+ Torch.NN: [trInputChannelSize2d] :: ConvTranspose2dSpec -> Int

+ Torch.NN: [trInputChannelSize3d] :: ConvTranspose3dSpec -> Int

+ Torch.NN: [trKernelDepth3d] :: ConvTranspose3dSpec -> Int

+ Torch.NN: [trKernelHeight2d] :: ConvTranspose2dSpec -> Int

+ Torch.NN: [trKernelHeight3d] :: ConvTranspose3dSpec -> Int

+ Torch.NN: [trKernelSize] :: ConvTranspose1dSpec -> Int

+ Torch.NN: [trKernelWidth2d] :: ConvTranspose2dSpec -> Int

+ Torch.NN: [trKernelWidth3d] :: ConvTranspose3dSpec -> Int

+ Torch.NN: [trOutputChannelSize1d] :: ConvTranspose1dSpec -> Int

+ Torch.NN: [trOutputChannelSize2d] :: ConvTranspose2dSpec -> Int

+ Torch.NN: [trOutputChannelSize3d] :: ConvTranspose3dSpec -> Int

+ Torch.NN: [upsampleInputFilters] :: UpSampleSpec -> Int

+ Torch.NN: [upsampleSpec] :: UpSample -> UpSampleSpec

+ Torch.NN: [upsampleStride] :: UpSampleSpec -> Int

+ Torch.NN: [weight] :: InstanceNorm -> Parameter

+ Torch.Tensor: ($dmtoLens) :: (TensorIndex a, TensorLike b) => a -> Lens' Tensor b

+ Torch.Tensor: ($dmtoTensors) :: (AsTensors as, Generic as, GAsTensors (Rep as)) => as -> Vector Tensor

+ Torch.Typed: ($dmflattenParameters) :: (Parameterized f, Generic f, GParameterized (Rep f), Parameters f ~ GParameters (Rep f)) => f -> HList (Parameters f)

+ Torch.Typed: ($dmreplaceParameters) :: (Parameterized f, Generic f, GParameterized (Rep f), Parameters f ~ GParameters (Rep f)) => f -> HList (Parameters f) -> f

+ Torch.Typed.Lens: ($dmfield) :: forall (device :: (DeviceType, Nat)) (dtype :: DType). (HasField field shape, FieldIdx field shape) => Lens' (NamedTensor device dtype shape) (NamedTensor device dtype (DropField field shape))

+ Torch.Typed.Lens: ($dmfieldId) :: (FieldId field a, Generic a, GFieldId field (Rep a)) => Proxy a -> Maybe Int

+ Torch.Typed.Lens: ($dmname) :: forall (device :: (DeviceType, Nat)) (dtype :: DType). (HasName name shape, KnownNat (NamedIdx name shape)) => Traversal' (NamedTensor device dtype shape) (NamedTensor device dtype (DropName name shape))

+ Torch.Typed.NN: ($dmforward) :: (HasForward f a b, Generic f, Generic a, Generic b, GHasForward (Rep f) (Rep a) (Rep b)) => f -> a -> b

+ Torch.Typed.NN: ($dmforwardStoch) :: (HasForward f a b, Generic f, Generic a, Generic b, GHasForward (Rep f) (Rep a) (Rep b)) => f -> a -> IO b

+ Torch.Typed.Parameter: ($dmflattenParameters) :: (Parameterized f, Generic f, GParameterized (Rep f), Parameters f ~ GParameters (Rep f)) => f -> HList (Parameters f)

+ Torch.Typed.Parameter: ($dmreplaceParameters) :: (Parameterized f, Generic f, GParameterized (Rep f), Parameters f ~ GParameters (Rep f)) => f -> HList (Parameters f) -> f

+ Torch.Typed.Parameter: type family GParameters (f :: Type -> Type) :: [Type]

+ Torch.Data.CsvDatastream: class FromField a

+ Torch.Data.CsvDatastream: class FromNamedRecord a

+ Torch.Data.CsvDatastream: class FromRecord a

+ Torch.Data.CsvDatastream: type CsvDatastream batches = CsvDatastream' batches 'Unnamed

+ Torch.Data.CsvDatastream: type CsvDatastreamNamed batches = CsvDatastream' batches 'Named

+ Torch.Data.Dataset: CollatedDataset :: dataset -> Int -> Pipe [batch] collatedBatch m () -> CollatedDataset (m :: Type -> Type) dataset batch collatedBatch

+ Torch.Data.Dataset: [chunkSize] :: CollatedDataset (m :: Type -> Type) dataset batch collatedBatch -> Int

+ Torch.Data.Dataset: [collateFn] :: CollatedDataset (m :: Type -> Type) dataset batch collatedBatch -> Pipe [batch] collatedBatch m ()

+ Torch.Data.Dataset: [set] :: CollatedDataset (m :: Type -> Type) dataset batch collatedBatch -> dataset

+ Torch.Data.Dataset: data CollatedDataset (m :: Type -> Type) dataset batch collatedBatch

+ Torch.Data.Internal: fromInput' :: forall (m :: Type -> Type) a. MonadBase IO m => Input a -> Producer' a m ()

+ Torch.Data.Internal: toOutput' :: forall (m :: Type -> Type) a. MonadBase IO m => Output a -> Consumer' a m ()

+ Torch.Data.Pipeline: [Shuffle] :: forall g. RandomGen g => g -> Sample

+ Torch.Data.Pipeline: class Ord k1 => Dataset (m :: k -> Type) dataset k1 (sample :: k) | dataset -> m, dataset -> sample, dataset -> k1

+ Torch.Data.Pipeline: getItem :: Dataset m dataset k1 sample => dataset -> k1 -> m sample

+ Torch.Data.Pipeline: keys :: Dataset m dataset k1 sample => dataset -> Set k1

+ Torch.Data.Pipeline: streamFromMap :: forall (m :: Type -> Type) dataset k sample r. (Dataset m dataset k sample, MonadIO m, MonadBaseControl IO m) => DatasetOptions -> dataset -> ContT r m (ListT m sample, Sample)

+ Torch.Data.StreamedPipeline: class Monad m => Datastream (m :: Type -> Type) seed dataset sample | dataset -> sample

+ Torch.Data.StreamedPipeline: streamFrom :: forall sample (m :: Type -> Type) dataset seed b. (Datastream m seed dataset sample, MonadBaseControl IO m, MonadBase IO m) => DatastreamOptions -> dataset -> ListT m seed -> ContT b m (ListT m sample)

+ Torch.Data.StreamedPipeline: streamFrom' :: forall sample (m :: Type -> Type) f dataset seed b. (Show sample, Datastream m seed dataset sample, MonadBaseControl IO m, MonadBase IO m, MonadIO m, Foldable f) => DatastreamOptions -> dataset -> f seed -> ContT b m (ListT m sample)

+ Torch.Data.Utils: bufferedCollate :: forall (m :: Type -> Type) batch sample r. (MonadIO m, MonadBaseControl IO m) => Buffer batch -> Int -> ([sample] -> Maybe batch) -> ListT m sample -> ContT r m (ListT m batch)

+ Torch.Data.Utils: collate :: forall (m :: Type -> Type) sample batch. Monad m => Int -> ([sample] -> Maybe batch) -> ListT m sample -> ListT m batch

+ Torch.Data.Utils: enumerateData :: forall (m :: Type -> Type) a. Monad m => ListT m a -> Producer (a, Int) m ()

+ Torch.Data.Utils: pmap :: forall (m :: Type -> Type) b a r. (MonadIO m, MonadBaseControl IO m) => Buffer b -> (a -> b) -> ListT m a -> ContT r m (ListT m b)

+ Torch.Data.Utils: pmap' :: forall (m :: Type -> Type) b a r. (MonadIO m, MonadBaseControl IO m) => Buffer b -> Pipe a b m () -> ListT m a -> ContT r m (ListT m b)

+ Torch.Data.Utils: pmapGroup :: forall (m :: Type -> Type) b a r. (MonadIO m, MonadBaseControl IO m) => Buffer b -> (ListT m a -> ListT m b) -> ListT m a -> ContT r m (ListT m b)

+ Torch.HList: class HFoldr f acc (xs :: [k]) res | f acc xs -> res

+ Torch.HList: class HFoldrM (m :: k -> Type) f acc (xs :: [k1]) (res :: k) | m f acc xs -> res

+ Torch.HList: class HMapM (m :: Type -> Type) f (xs :: [k]) (ys :: [k])

+ Torch.HList: class HMapM' (m :: Type -> Type) f (xs :: [k]) (ys :: [k]) | f xs -> ys

+ Torch.HList: class HReplicateFD (n :: Nat) e (es :: [Type]) | n e -> es

+ Torch.HList: class Applicative f => HSequence (f :: Type -> Type) (xs :: [k]) (ys :: [k]) | xs -> ys, ys f -> xs

+ Torch.HList: class HUnfold f res (xs :: [k])

+ Torch.HList: class HUnfoldM (m :: Type -> Type) f res (xs :: [k])

+ Torch.HList: class HZipWithM (m :: Type -> Type) f (xs :: [k]) (ys :: [k]) (zs :: [k]) | f xs ys -> zs

+ Torch.HList: happend :: forall {k} (as :: [k]) (bs :: [k]). HAppend as bs => HList as -> HList bs -> HList (as ++ bs)

+ Torch.HList: hconcat :: forall (xs :: [Type]). HConcat xs => HList xs -> HList (HConcatR xs)

+ Torch.HList: hreplicate :: forall (n :: Nat) e. HReplicate n e => e -> HList (HReplicateR n e)

+ Torch.HList: htranspose :: forall (acc :: [Type]) (xs :: [Type]) (xxs :: [Type]) res. (HReplicateFD (ListLength xs) (HList ('[] :: [Type])) acc, HFoldr HZipF (HList acc) (HList xs ': xxs) res) => HList (HList xs ': xxs) -> res

+ Torch.HList: hunappend :: forall {k} (cs :: [k]) (as :: [k]) (bs :: [k]). (cs ~ (as ++ bs), HAppend as bs) => HList cs -> (HList as, HList bs)

+ Torch.HList: hunfoldrM :: forall m f res (xs :: [Type]) a. (HUnfoldM m f res xs, Apply f a res, res ~ HUnfoldMRes m a xs) => f -> a -> m (HList xs)

+ Torch.HList: pattern (:.) :: x -> HList xs -> HList (x ': xs)

+ Torch.HList: type HAppend (as :: [k]) (bs :: [k]) = HAppendFD as bs as ++ bs

+ Torch.HList: type HConcat (xs :: [Type]) = HConcatFD xs HConcatR xs

+ Torch.HList: type HReplicate (n :: Nat) e = HReplicateFD n e HReplicateR n e

+ Torch.Lens: class GHasTypes (s :: Type -> Type) a

+ Torch.Lens: gtypes :: GHasTypes s a => Traversal' (s b) a

+ Torch.Lens: types_ :: HasTypes s a => Traversal' s a

+ Torch.NN: _gReplaceParameters :: GParameterized f => f a -> ParamStream (f a)

+ Torch.NN: _replaceParameters :: Parameterized f => f -> ParamStream f

+ Torch.NN: class GParameterized (f :: Type -> Type)

+ Torch.NN: flattenParameters :: Parameterized f => f -> [Parameter]

+ Torch.NN: forward :: HasForward f a b => f -> a -> b

+ Torch.NN: forwardStoch :: HasForward f a b => f -> a -> IO b

+ Torch.NN: gFlattenParameters :: GParameterized f => f a -> [Parameter]

+ Torch.NN: gForward :: GHasForward f a b => f c -> a c' -> b c''

+ Torch.Scalar: class Castable a ForeignPtr Scalar => Scalar a

+ Torch.Tensor: class GAsTensors (record :: Type -> Type)

+ Torch.Tensor: toDevice :: HasTypes a Tensor => Device -> a -> a

+ Torch.Tensor: toTensors :: AsTensors as => as -> Vector Tensor

+ Torch.Tensor: toType :: HasTypes a Tensor => DType -> a -> a

+ Torch.TensorFactories: type FactoryType = ForeignPtr IntArray -> ForeignPtr TensorOptions -> IO ForeignPtr Tensor

+ Torch.TensorFactories: type FactoryTypeWithDimnames = ForeignPtr IntArray -> ForeignPtr DimnameList -> ForeignPtr TensorOptions -> IO ForeignPtr Tensor

+ Torch.Typed: (/=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: (<.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: (<=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: (==.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: (>.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: (>=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: UnknownShapeTensor :: Tensor device dtype shape -> UnknownShapeTensor (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed: [FromTensor] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: Shape) (shape1 :: [Nat]). shape1 ~ ToNats shape => Tensor device dtype shape1 -> NamedTensor device dtype shape

+ Torch.Typed: [UnsafeMkTensor] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor -> Tensor device dtype shape

+ Torch.Typed: add :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed: class Parameterized f where {

+ Torch.Typed: class Castable a ForeignPtr Scalar => Scalar a

+ Torch.Typed: data UnknownShapeTensor (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed: device :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> Device

+ Torch.Typed: dim :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> Int

+ Torch.Typed: div :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed: dtype :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> DType

+ Torch.Typed: eq :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: flattenParameters :: Parameterized f => f -> HList (Parameters f)

+ Torch.Typed: fromUnnamed :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). (Unnamed t, IsUnnamed t device dtype shape) => Tensor device dtype shape -> t

+ Torch.Typed: gFlattenParameters :: GParameterized f => f a -> HList (GParameters f)

+ Torch.Typed: gReplaceParameters :: GParameterized f => f a -> HList (GParameters f) -> f a

+ Torch.Typed: ge :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: getFiniteI :: forall (n :: Nat). Finite n -> Int

+ Torch.Typed: gt :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: le :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: lt :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: makeIndependent :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Parameter device dtype shape)

+ Torch.Typed: matmul :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape'' ~ MatMul shape shape', MatMulDTypeIsValid device dtype) => Tensor device dtype shape -> Tensor device dtype shape' -> Tensor device dtype shape''

+ Torch.Typed: mul :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed: ne :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed: replaceParameters :: Parameterized f => f -> HList (Parameters f) -> f

+ Torch.Typed: reshape :: forall (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownShape shape', Numel shape ~ Numel shape') => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed: select :: forall (dim :: Nat) (idx :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownNat idx, InRange shape dim idx, shape' ~ Remove shape dim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed: selectIdx :: forall (dim :: Nat) (n :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, n ~ Index shape dim, shape' ~ Remove shape dim) => Tensor device dtype shape -> Finite n -> Tensor device dtype shape'

+ Torch.Typed: shape :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> [Int]

+ Torch.Typed: sub :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed: toBool :: forall (device :: (DeviceType, Nat)). Tensor device 'Bool ('[] :: [Nat]) -> Bool

+ Torch.Typed: toCPU :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> CPUTensor dtype shape

+ Torch.Typed: toCUDA :: forall {k} (device' :: k) (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> CUDATensor 0 dtype shape

+ Torch.Typed: toDense :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed: toDependent :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype shape -> Tensor device dtype shape

+ Torch.Typed: toDouble :: forall (device :: (DeviceType, Nat)). Tensor device 'Double ('[] :: [Nat]) -> Double

+ Torch.Typed: toFloat :: forall (device :: (DeviceType, Nat)). Tensor device 'Float ('[] :: [Nat]) -> Float

+ Torch.Typed: toInt :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Int

+ Torch.Typed: toMPS :: forall {k} (device' :: k) (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> MPSTensor 0 dtype shape

+ Torch.Typed: toSparse :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed: toUnnamed :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). (Unnamed t, IsUnnamed t device dtype shape) => t -> Tensor device dtype shape

+ Torch.Typed: type Broadcast (shape :: [Nat]) (shape' :: [Nat]) = CheckBroadcast shape shape' ComputeBroadcast Reverse shape Reverse shape'

+ Torch.Typed: type CUDATensor (deviceIndex :: Nat) = Tensor '( 'CUDA, deviceIndex)

+ Torch.Typed: type GParameters (f :: Type -> Type) :: [Type];

+ Torch.Typed: type MPSTensor (deviceIndex :: k) = Tensor '( 'MPS, 0)

+ Torch.Typed: type MatMul (shape :: [Nat]) (shape' :: [Nat]) = CheckMatMul shape shape' ComputeMatMul Reverse shape Reverse shape'

+ Torch.Typed: type Parameters f = GParameters Rep f;

+ Torch.Typed: untypeParam :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Parameter device dtype shape -> Parameter

+ Torch.Typed: withTensor :: Tensor -> (forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDevice device, KnownDType dtype, KnownShape shape) => Tensor device dtype shape -> r) -> r

+ Torch.Typed: withTensorShape :: forall (device :: (DeviceType, Nat)) (dtype :: DType) r. (KnownDevice device, KnownDType dtype) => Tensor -> (forall (shape :: [Nat]). KnownShape shape => Tensor device dtype shape -> r) -> r

+ Torch.Typed.Autograd: grad :: forall (dtype :: DType) (device :: (DeviceType, Nat)). HasGrad a b => Tensor device dtype ('[] :: [Nat]) -> a -> b

+ Torch.Typed.Auxiliary: forEachNat :: forall (n :: Nat) a. KnownNat n => (forall (i :: Nat). KnownNat i => Proxy i -> a) -> [a]

+ Torch.Typed.Auxiliary: natValI :: forall (n :: Nat). KnownNat n => Int

+ Torch.Typed.Auxiliary: natValInt16 :: forall (n :: Nat). KnownNat n => Int16

+ Torch.Typed.Auxiliary: type (n :: Nat) >= (m :: Nat) = (IsAtLeast n m CmpNat n m, KnownNat n - m)

+ Torch.Typed.Auxiliary: type Backwards (l :: [a]) (n :: Nat) = BackwardsImpl LastDim l n

+ Torch.Typed.Auxiliary: type DTypePromotion (dtype :: DType) (dtype' :: DType) = DTypePromotionImpl dtype dtype' CmpDType dtype dtype'

+ Torch.Typed.Auxiliary: type DimOutOfBoundCheck (shape :: [a]) (dim :: Nat) = DimOutOfBoundCheckImpl shape dim shape dim

+ Torch.Typed.Auxiliary: type InRange (shape :: [Nat]) (dim :: Nat) (idx :: Nat) = InRangeCheck shape dim idx CmpNat idx Index shape dim

+ Torch.Typed.Auxiliary: type Index (l :: [k]) (n :: Nat) = CheckIndex l n IndexImpl l n

+ Torch.Typed.Auxiliary: type IsSuffixOf (xs :: [b]) (ys :: [b]) = CheckIsSuffixOf xs ys IsSuffixOfImpl xs ys DropLengthMaybe xs ys

+ Torch.Typed.Auxiliary: type Remove (l :: [a]) (n :: Nat) = CheckRemove l n RemoveImpl l n

+ Torch.Typed.Auxiliary: type Reverse (l :: [a]) = ReverseImpl l '[] :: [a]

+ Torch.Typed.Auxiliary: type family StandardDTypeValidation (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Auxiliary: unsafeConstraint :: (c => a) -> a

+ Torch.Typed.Auxiliary: withNat :: Int -> (forall (n :: Nat). KnownNat n => Proxy n -> r) -> r

+ Torch.Typed.DType: class HasToDType (dtype' :: k) (dtype :: k1) f g | dtype' dtype f -> g, dtype' dtype g -> f

+ Torch.Typed.DType: gToDType :: GHasToDType dtype' dtype f g => f a -> g a

+ Torch.Typed.Device: class HasGather (device' :: k) (devices :: k1) (fs :: [k2]) g | device' devices fs -> g

+ Torch.Typed.Device: class HasReplicate (devices' :: [(DeviceType, Nat)]) (device :: (DeviceType, Nat)) f (gs :: [Type]) | devices' device f -> gs

+ Torch.Typed.Device: class HasScatter (devices' :: k) (device :: k1) f (gs :: [k2]) | devices' device f -> gs

+ Torch.Typed.Device: class HasToDevice (device' :: (DeviceType, Nat)) (device :: (DeviceType, Nat)) f g | device' device f -> g, device' device g -> f

+ Torch.Typed.Device: gToDevice :: GHasToDevice device' device f g => f a -> g a

+ Torch.Typed.Factories: eyeSquare :: forall (n :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, TensorOptions '[n, n] dtype device) => Tensor device dtype '[n, n]

+ Torch.Typed.Factories: full :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) a. (TensorOptions shape dtype device, Scalar a) => a -> Tensor device dtype shape

+ Torch.Typed.Factories: linspace :: forall (steps :: Nat) (device :: (DeviceType, Nat)) start end. (Scalar start, Scalar end, KnownNat steps, TensorOptions '[steps] 'Float device) => start -> end -> Tensor device 'Float '[steps]

+ Torch.Typed.Factories: ones :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). TensorOptions shape dtype device => Tensor device dtype shape

+ Torch.Typed.Factories: rand :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (TensorOptions shape dtype device, RandDTypeIsValid device dtype) => IO (Tensor device dtype shape)

+ Torch.Typed.Factories: randint :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (TensorOptions shape dtype device, RandDTypeIsValid device dtype) => Int -> Int -> IO (Tensor device dtype shape)

+ Torch.Typed.Factories: randn :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (TensorOptions shape dtype device, RandDTypeIsValid device dtype) => IO (Tensor device dtype shape)

+ Torch.Typed.Factories: type family RandDTypeIsValid (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Factories: zeros :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). TensorOptions shape dtype device => Tensor device dtype shape

+ Torch.Typed.Functional: abs :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: acos :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: adaptiveAvgPool1d :: forall (outputSize :: Nat) (channelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize, batchSize, outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize] -> Tensor device dtype '[batchSize, channelSize, outputSize]

+ Torch.Typed.Functional: adaptiveAvgPool2d :: forall (outputSize :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize0, inputSize1, batchSize, Fst outputSize, Snd outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, Fst outputSize, Snd outputSize]

+ Torch.Typed.Functional: adaptiveAvgPool3d :: forall (outputSize :: (Nat, Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize0, inputSize1, inputSize2, batchSize, Fst3 outputSize, Snd3 outputSize, Trd3 outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1, inputSize2] -> Tensor device dtype '[batchSize, channelSize, Fst3 outputSize, Snd3 outputSize, Trd3 outputSize]

+ Torch.Typed.Functional: adaptiveMaxPool1d :: forall (outputSize :: Nat) (channelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize, batchSize, outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize] -> (Tensor device dtype '[batchSize, channelSize, outputSize], Tensor device 'Int64 '[batchSize, channelSize, outputSize])

+ Torch.Typed.Functional: adaptiveMaxPool2d :: forall (outputSize :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize0, inputSize1, batchSize, Fst outputSize, Snd outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> (Tensor device dtype '[batchSize, channelSize, Fst outputSize, Snd outputSize], Tensor device 'Int64 '[batchSize, channelSize, Fst outputSize, Snd outputSize])

+ Torch.Typed.Functional: adaptiveMaxPool3d :: forall (outputSize :: (Nat, Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize0, inputSize1, inputSize2, batchSize, Fst3 outputSize, Snd3 outputSize, Trd3 outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1, inputSize2] -> (Tensor device dtype '[batchSize, channelSize, Fst3 outputSize, Snd3 outputSize, Trd3 outputSize], Tensor device 'Int64 '[batchSize, channelSize, Fst3 outputSize, Snd3 outputSize, Trd3 outputSize])

+ Torch.Typed.Functional: addScalar :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: addmm :: forall (shape' :: [Nat]) (shape :: [Nat]) (n :: Nat) (k :: Nat) (m :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[n, k, m], shape' ~ Broadcast shape '[n, m]) => Float -> Float -> Tensor device dtype '[n, k] -> Tensor device dtype '[k, m] -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: addmv :: forall (shape' :: [Nat]) (shape :: [Nat]) (n :: Nat) (m :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, KnownNat m, shape' ~ Broadcast shape '[n]) => Float -> Float -> Tensor device dtype '[n, m] -> Tensor device dtype '[m] -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: alias :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: all :: forall (shape :: [Nat]) (device :: (DeviceType, Nat)). Tensor device 'Bool shape -> Tensor device 'Bool ('[] :: [Nat])

+ Torch.Typed.Functional: allDim :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim) => Tensor device 'Bool shape -> Tensor device 'Bool shape'

+ Torch.Typed.Functional: allclose :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Double -> Bool -> Tensor device dtype shape -> Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: alphaDropout :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Bool -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: any :: forall (shape :: [Nat]) (device :: (DeviceType, Nat)). Tensor device 'Bool shape -> Tensor device 'Bool ('[] :: [Nat])

+ Torch.Typed.Functional: anyDim :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim) => Tensor device 'Bool shape -> Tensor device 'Bool shape'

+ Torch.Typed.Functional: argSortDim :: forall (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, HasDim dim shape) => Bool -> Tensor device dtype shape -> Tensor device 'Int64 shape

+ Torch.Typed.Functional: argSortNamedDim :: forall (dim :: Size) (shape :: Shape) (dtype :: DType) (device :: (DeviceType, Nat)). KnownNat (FindDim dim shape) => Bool -> NamedTensor device dtype shape -> NamedTensor device 'Int64 shape

+ Torch.Typed.Functional: argmax :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim, StandardDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device 'Int64 shape'

+ Torch.Typed.Functional: argmin :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim, StandardDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device 'Int64 shape'

+ Torch.Typed.Functional: asin :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: atan :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: avgPool1d :: forall (kernelSize :: Nat) (stride :: Nat) (padding :: Nat) (channelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (outputSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[kernelSize, stride, padding, channelSize, inputSize, batchSize], ConvSideCheck inputSize kernelSize stride padding outputSize) => Tensor device dtype '[batchSize, channelSize, inputSize] -> Tensor device dtype '[batchSize, channelSize, outputSize]

+ Torch.Typed.Functional: avgPool2d :: forall (kernelSize :: (Nat, Nat)) (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst kernelSize, Snd kernelSize, Fst stride, Snd stride, Fst padding, Snd padding, channelSize, inputSize0, inputSize1, batchSize], ConvSideCheck inputSize0 (Fst kernelSize) (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 (Snd kernelSize) (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: avgPool3d :: forall (kernelSize :: (Nat, Nat, Nat)) (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (outputSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst3 kernelSize, Snd3 kernelSize, Trd3 kernelSize, Fst3 stride, Snd3 stride, Trd3 stride, Fst3 padding, Snd3 padding, Trd3 padding, channelSize, inputSize0, inputSize1, inputSize2, batchSize], ConvSideCheck inputSize0 (Fst3 kernelSize) (Fst3 stride) (Fst3 padding) outputSize0, ConvSideCheck inputSize1 (Snd3 kernelSize) (Snd3 stride) (Snd3 padding) outputSize1, ConvSideCheck inputSize2 (Trd3 kernelSize) (Trd3 stride) (Trd3 padding) outputSize2) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1, inputSize2] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1, outputSize2]

+ Torch.Typed.Functional: baddbmm :: forall (shape' :: [Nat]) (shape :: [Nat]) (batchSize :: Nat) (n :: Nat) (m :: Nat) (k :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, KnownNat m, KnownNat k, shape' ~ Broadcast shape '[batchSize, n, m]) => Float -> Float -> Tensor device dtype '[batchSize, n, k] -> Tensor device dtype '[batchSize, k, m] -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: binaryCrossEntropy :: forall (reduction :: Reduction) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownReduction reduction, shape' ~ ConditionalReduction shape reduction, StandardFloatingPointDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: bitwiseNot :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]). Tensor device 'Bool shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: bmm :: forall (batchSize :: Nat) (n :: Nat) (m :: Nat) (k :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[batchSize, n, k] -> Tensor device dtype '[batchSize, k, m] -> Tensor device dtype '[batchSize, n, m]

+ Torch.Typed.Functional: broadcastTensors :: forall {k} (tensors :: [k]) (tensors' :: [k]). (tensors' ~ BroadcastTensors tensors, Castable (HList tensors) [ATenTensor], Castable (HList tensors') [ATenTensor]) => HList tensors -> HList tensors'

+ Torch.Typed.Functional: cat :: forall {k} (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) (tensors :: [k]). (KnownNat dim, '(shape, dtype, device) ~ Cat dim tensors, Castable (HList tensors) [ATenTensor]) => HList tensors -> Tensor device dtype shape

+ Torch.Typed.Functional: ceil :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: celu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Float -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: cholesky :: forall (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape' ~ Square shape, CholeskyDTypeIsValid device dtype) => Tri -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: choleskyInverse :: forall (n :: Natural) (dtype :: DType) (device :: (DeviceType, Nat)). (1 <= n, CholeskyDTypeIsValid device dtype) => Tri -> Tensor device dtype '[n, n] -> Tensor device dtype '[n, n]

+ Torch.Typed.Functional: choleskySolve :: forall (m_k :: [Nat]) (m_m :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (Square m_m ~ m_m, FstSquareDim m_m ~ FstSquareDim m_k, 1 <= FstSquareDim m_m, CholeskyDTypeIsValid device dtype) => Tri -> Tensor device dtype m_k -> Tensor device dtype m_m -> Tensor device dtype m_k

+ Torch.Typed.Functional: chunk :: forall {k} (chunks :: Nat) (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) (tensorChunks :: [k]). (KnownNat chunks, KnownNat dim, tensorChunks ~ (Chunk chunks dim shape dtype device :: [k]), Castable (HList tensorChunks) [ATenTensor]) => Tensor device dtype shape -> HList tensorChunks

+ Torch.Typed.Functional: clamp :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) a. Scalar a => a -> a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: clampMax :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) a. Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: clampMin :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) a. Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: class KnownEigenVectors (a :: k)

+ Torch.Typed.Functional: class KnownKeepOrDropDim (keepOrDropDim :: k)

+ Torch.Typed.Functional: class KnownReduction (reduction :: k)

+ Torch.Typed.Functional: clone :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.Functional: constantPadNd1d :: forall (pad :: (Nat, Nat)) (n :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[Fst pad, Snd pad, n] => Float -> Tensor device dtype '[n] -> Tensor device dtype '[(n + Fst pad) + Snd pad]

+ Torch.Typed.Functional: conv1d :: forall (stride :: Nat) (padding :: Nat) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (outputSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[stride, padding, inputChannelSize, outputChannelSize, kernelSize, inputSize, batchSize, outputSize], ConvSideCheck inputSize kernelSize stride padding outputSize) => Tensor device dtype '[outputChannelSize, inputChannelSize, kernelSize] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize]

+ Torch.Typed.Functional: conv2d :: forall (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst stride, Snd stride, Fst padding, Snd padding, inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, inputSize0, inputSize1, batchSize, outputSize0, outputSize1], ConvSideCheck inputSize0 kernelSize0 (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 kernelSize1 (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[outputChannelSize, inputChannelSize, kernelSize0, kernelSize1] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: conv3d :: forall (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (kernelSize2 :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (outputSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst3 stride, Snd3 stride, Trd3 stride, Fst3 padding, Snd3 padding, Trd3 padding, inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, kernelSize2, inputSize0, inputSize1, inputSize2, batchSize], ConvSideCheck inputSize0 kernelSize0 (Fst3 stride) (Fst3 padding) outputSize0, ConvSideCheck inputSize1 kernelSize1 (Snd3 stride) (Snd3 padding) outputSize1, ConvSideCheck inputSize2 kernelSize2 (Trd3 stride) (Trd3 padding) outputSize2) => Tensor device dtype '[outputChannelSize, inputChannelSize, kernelSize0, kernelSize1, kernelSize2] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize0, inputSize1, inputSize2] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize0, outputSize1, outputSize2]

+ Torch.Typed.Functional: convTBC :: forall (padding :: Nat) (timeSize :: Nat) (batchSize :: Nat) (kernelSize :: Nat) (inputChannels :: Nat) (outputChannels :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). KnownNat padding => Tensor device dtype '[kernelSize, inputChannels, outputChannels] -> Tensor device dtype '[outputChannels] -> Tensor device dtype '[timeSize, batchSize, inputChannels] -> Tensor device dtype '[((timeSize + (padding * 2)) + 1) - kernelSize, batchSize, outputChannels]

+ Torch.Typed.Functional: convTranspose1d :: forall (stride :: Nat) (padding :: Nat) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (outputSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[stride, padding, inputChannelSize, outputChannelSize, kernelSize, inputSize, batchSize, outputSize], ConvSideCheck inputSize kernelSize stride padding outputSize) => Tensor device dtype '[inputChannelSize, outputChannelSize, kernelSize] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize]

+ Torch.Typed.Functional: convTranspose2d :: forall (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst stride, Snd stride, Fst padding, Snd padding, inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, inputSize0, inputSize1, batchSize, outputSize0, outputSize1], ConvSideCheck inputSize0 kernelSize0 (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 kernelSize1 (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[inputChannelSize, outputChannelSize, kernelSize0, kernelSize1] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: convTranspose3d :: forall (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (kernelSize2 :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (outputSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst3 stride, Snd3 stride, Trd3 stride, Fst3 padding, Snd3 padding, Trd3 padding, inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, kernelSize2, inputSize0, inputSize1, inputSize2, batchSize], ConvSideCheck inputSize0 kernelSize0 (Fst3 stride) (Fst3 padding) outputSize0, ConvSideCheck inputSize1 kernelSize1 (Snd3 stride) (Snd3 padding) outputSize1, ConvSideCheck inputSize2 kernelSize2 (Trd3 stride) (Trd3 padding) outputSize2) => Tensor device dtype '[inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, kernelSize2] -> Tensor device dtype '[outputChannelSize] -> Tensor device dtype '[batchSize, inputChannelSize, inputSize0, inputSize1, inputSize2] -> Tensor device dtype '[batchSize, outputChannelSize, outputSize0, outputSize1, outputSize2]

+ Torch.Typed.Functional: cos :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) t. (StandardFloatingPointDTypeValidation device dtype, IsUnnamed t device dtype shape) => t -> t

+ Torch.Typed.Functional: cosh :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: cudnnIsAcceptable :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: det :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype (Det shape)

+ Torch.Typed.Functional: diag :: forall (tri :: Tri) (index :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (device :: (DeviceType, Nat)) (dtype :: DType). (KnownTri tri, KnownNat index, StandardDTypeValidation device dtype, shape' ~ DiagShape tri index shape) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: diagEmbed :: forall (index :: Nat) (dim1 :: Nat) (dim2 :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (device :: (DeviceType, Nat)) (dtype :: DType). (KnownNat index, KnownNat dim1, KnownNat dim2, shape' ~ DiagEmbedShape index dim1 dim2 shape, DimsDistinctAscending dim1 dim2, StandardDTypeValidation device dtype) => Tri -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: diagflat :: forall (index :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (device :: (DeviceType, Nat)) (dtype :: DType). (KnownNat index, shape' ~ DiagflatShape index shape, StandardDTypeValidation device dtype) => Tri -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: diagonal :: forall (tri :: Tri) (index :: Nat) (dim1 :: Nat) (dim2 :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (device :: (DeviceType, Nat)) (dtype :: DType). (KnownTri tri, KnownNat index, KnownNat dim1, KnownNat dim2, NDimAtLeast 2 shape, DimsDistinctAscending dim1 dim2, shape' ~ DiagonalShape tri index dim1 dim2 shape, StandardDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: digamma :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: divScalar :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: dot :: forall (size :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). DotDTypeIsValid device dtype => Tensor device dtype '[size] -> Tensor device dtype '[size] -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: dropout :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Bool -> Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.Functional: eig :: forall {k1} {k2} (eigenvectors :: k1) (n :: Nat) (shape :: k2) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, KnownEigenVectors eigenvectors, EigDTypeIsValid device dtype, KnownDType (ToComplexNumber dtype)) => Tensor device dtype '[n, n] -> (Tensor device (ToComplexNumber dtype) '[n], Tensor device (ToComplexNumber dtype) '[n, n])

+ Torch.Typed.Functional: elu :: forall (shape :: [Nat]) (dtype :: DType) a (device :: (DeviceType, Nat)). (Scalar a, StandardFloatingPointDTypeValidation device dtype) => a -> a -> a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: embedding :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedDim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownMaybeNat paddingIdx, PaddingIdxCheck paddingIdx numEmbeds) => Bool -> Bool -> Tensor device dtype '[numEmbeds, embedDim] -> Tensor device 'Int64 shape -> Tensor device dtype (Reverse (embedDim ': Reverse shape))

+ Torch.Typed.Functional: emptyLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.Functional: erf :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: erfc :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: erfinv :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: exp :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: expand :: forall (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownShape shape', shape' ~ Broadcast shape shape') => Bool -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: expm1 :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: featureAlphaDropout :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Bool -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: featureDropout :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Bool -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: flattenAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownShape shape => Tensor device dtype shape -> Tensor device dtype '[Product shape]

+ Torch.Typed.Functional: floor :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: frac :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: fullLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Float -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: gatherDim :: forall (dim :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, shape' ~ GatherDim shape shape' dim) => Tensor device 'Int64 shape' -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: gelu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). GeluDTypeIsValid device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: geqrf :: forall (m :: Nat) (n :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[m, n] -> (Tensor device dtype '[m, n], Tensor device dtype '[Min m n])

+ Torch.Typed.Functional: gru :: forall {k} (shapeOrder :: RNNShapeOrder) (directionality :: RNNDirectionality) (numLayers :: Nat) (seqLen :: Nat) (batchSize :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Natural) (inputShape :: [Nat]) (outputShape :: [Nat]) (hcShape :: [Natural]) (tensorParameters :: [k]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat numLayers, 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], tensorParameters ~ (GRUR inputSize hiddenSize numLayers directionality dtype device :: [k]), Castable (HList tensorParameters) [ATenTensor]) => HList tensorParameters -> Double -> Bool -> Tensor device dtype hcShape -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hcShape)

+ Torch.Typed.Functional: gruCell :: forall (inputSize :: Natural) (hiddenSize :: Natural) (batchSize :: Natural) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[3 * hiddenSize, inputSize] -> Tensor device dtype '[3 * hiddenSize, hiddenSize] -> Tensor device dtype '[3 * hiddenSize] -> Tensor device dtype '[3 * hiddenSize] -> Tensor device dtype '[batchSize, hiddenSize] -> Tensor device dtype '[batchSize, inputSize] -> Tensor device dtype '[batchSize, hiddenSize]

+ Torch.Typed.Functional: hardTanh :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Float -> Float -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: inverse :: forall (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape' ~ Square shape, InverseShapeIsValid device shape, InverseDTypeIsValid device dtype) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: isComplex :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: isDistributed :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: isFloatingPoint :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: isNaN :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: isNonZero :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Numel shape ~ 1 => Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: isSameSize :: forall (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape' -> Bool

+ Torch.Typed.Functional: isSigned :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Bool

+ Torch.Typed.Functional: isclose :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> Double -> Bool -> Tensor device dtype shape -> Tensor device dtype shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: l1Loss :: forall (reduction :: Reduction) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownReduction reduction => Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype (ConditionalReduction shape reduction)

+ Torch.Typed.Functional: layerNorm :: forall (normalizedShape :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownShape normalizedShape, IsSuffixOf normalizedShape shape) => Tensor device dtype normalizedShape -> Tensor device dtype normalizedShape -> Double -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: leakyRelu :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (Scalar a, StandardFloatingPointDTypeValidation device dtype) => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: lgamma :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: linear :: forall (batchSize :: Nat) (inputFeatures :: Nat) (outputFeatures :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[outputFeatures, inputFeatures] -> Tensor device dtype '[outputFeatures] -> Tensor device dtype '[batchSize, inputFeatures] -> Tensor device dtype '[batchSize, outputFeatures]

+ Torch.Typed.Functional: linear' :: forall (inputFeatures :: Nat) (outputFeatures :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) (shape'' :: [Nat]). (shape'' ~ MatMul shape '[inputFeatures, outputFeatures], shape' ~ Broadcast shape'' shape'') => Tensor device dtype '[outputFeatures, inputFeatures] -> Tensor device dtype '[outputFeatures] -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: log :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: log10 :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: log1p :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: log2 :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: logDet :: forall (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape' ~ Det shape => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: logSigmoid :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: logSoftmax :: forall (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, DimOutOfBoundCheck shape dim, KnownDType dtype, StandardFloatingPointDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: logSumExp :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, Reifies dtype DType, DTypeIsFloatingPoint device dtype, shape' ~ ConditionalDropDimension shape dim keepOrDropDim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: logicalAnd :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]). Tensor device 'Bool shape -> Tensor device 'Bool shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: logicalNot :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]). Tensor device 'Bool shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: logicalOr :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]). Tensor device 'Bool shape -> Tensor device 'Bool shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: logicalXor :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]). Tensor device 'Bool shape -> Tensor device 'Bool shape -> Tensor device 'Bool shape

+ Torch.Typed.Functional: lstm :: forall {k} (shapeOrder :: RNNShapeOrder) (directionality :: RNNDirectionality) (numLayers :: Nat) (seqLen :: Nat) (batchSize :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Natural) (inputShape :: [Nat]) (outputShape :: [Nat]) (hxShape :: [Natural]) (tensorParameters :: [k]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat numLayers, KnownRNNShapeOrder shapeOrder, KnownRNNDirectionality directionality, outputSize ~ (hiddenSize * NumberOfDirections directionality), inputShape ~ RNNShape shapeOrder seqLen batchSize inputSize, outputShape ~ RNNShape shapeOrder seqLen batchSize outputSize, hxShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], tensorParameters ~ (LSTMR inputSize hiddenSize numLayers directionality dtype device :: [k]), Castable (HList tensorParameters) [ATenTensor]) => HList tensorParameters -> Double -> Bool -> (Tensor device dtype hxShape, Tensor device dtype hxShape) -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hxShape, Tensor device dtype hxShape)

+ Torch.Typed.Functional: lstmCell :: forall (inputSize :: Natural) (hiddenSize :: Natural) (batchSize :: Natural) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[4 * hiddenSize, inputSize] -> Tensor device dtype '[4 * hiddenSize, hiddenSize] -> Tensor device dtype '[4 * hiddenSize] -> Tensor device dtype '[4 * hiddenSize] -> (Tensor device dtype '[batchSize, hiddenSize], Tensor device dtype '[batchSize, hiddenSize]) -> Tensor device dtype '[batchSize, inputSize] -> (Tensor device dtype '[batchSize, hiddenSize], Tensor device dtype '[batchSize, hiddenSize])

+ Torch.Typed.Functional: maskedFill :: forall a (shape :: [Nat]) (shape' :: [Nat]) (shape'' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (Scalar a, shape'' ~ Broadcast shape shape') => Tensor device 'Bool shape' -> a -> Tensor device dtype shape -> Tensor device dtype shape''

+ Torch.Typed.Functional: maskedSelect :: forall (shape :: [Nat]) (shape' :: [Nat]) (shape'' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape'' ~ Broadcast shape shape' => Tensor device 'Bool shape -> Tensor device dtype shape' -> UnknownShapeTensor device dtype

+ Torch.Typed.Functional: matrixPower :: forall (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape' ~ Square shape => Int -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: max :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (MinMaxDTypeIsValid device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: maxAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: maxDim :: forall (d :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownNat d => Tensor device dtype shape -> (Tensor device dtype (DropValue shape d), Tensor device 'Int64 (DropValue shape d))

+ Torch.Typed.Functional: maxPool1d :: forall (kernelSize :: Nat) (stride :: Nat) (padding :: Nat) (channelSize :: Nat) (inputSize :: Nat) (batchSize :: Nat) (outputSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[kernelSize, stride, padding, channelSize, inputSize, batchSize], ConvSideCheck inputSize kernelSize stride padding outputSize) => Tensor device dtype '[batchSize, channelSize, inputSize] -> Tensor device dtype '[batchSize, channelSize, outputSize]

+ Torch.Typed.Functional: maxPool2d :: forall (kernelSize :: (Nat, Nat)) (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst kernelSize, Snd kernelSize, Fst stride, Snd stride, Fst padding, Snd padding, channelSize, inputSize0, inputSize1, batchSize], ConvSideCheck inputSize0 (Fst kernelSize) (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 (Snd kernelSize) (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: maxPool3d :: forall (kernelSize :: (Nat, Nat, Nat)) (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (inputSize2 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (outputSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst3 kernelSize, Snd3 kernelSize, Trd3 kernelSize, Fst3 stride, Snd3 stride, Trd3 stride, Fst3 padding, Snd3 padding, Trd3 padding, channelSize, inputSize0, inputSize1, inputSize2, batchSize], ConvSideCheck inputSize0 (Fst3 kernelSize) (Fst3 stride) (Fst3 padding) outputSize0, ConvSideCheck inputSize1 (Snd3 kernelSize) (Snd3 stride) (Snd3 padding) outputSize1, ConvSideCheck inputSize2 (Trd3 kernelSize) (Trd3 stride) (Trd3 padding) outputSize2) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1, inputSize2] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1, outputSize2]

+ Torch.Typed.Functional: maxValues :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: mean :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim, MeanDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: meanAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (MeanDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: meanDim :: forall (dim :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, shape' ~ DropValue shape dim, MeanDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: meanNamedDim :: forall (dim :: Size) (shape' :: Shape) (shape :: Shape) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat (FindDim dim shape), shape' ~ DropNamedValue shape dim, MeanDTypeValidation device dtype) => NamedTensor device dtype shape -> NamedTensor device dtype shape'

+ Torch.Typed.Functional: median :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim, StandardDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> (Tensor device dtype shape', Tensor device 'Int64 shape')

+ Torch.Typed.Functional: medianAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (StandardDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: medianDim :: forall (dim :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, shape' ~ DropValue shape dim, StandardDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> (Tensor device dtype shape', Tensor device 'Int64 shape')

+ Torch.Typed.Functional: min :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (MinMaxDTypeIsValid device dtype, AllDimsPositive shape) => Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: minAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: minDim :: forall (d :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownNat d => Tensor device dtype shape -> (Tensor device dtype (DropValue shape d), Tensor device 'Int64 (DropValue shape d))

+ Torch.Typed.Functional: minValues :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: mish :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (StandardFloatingPointDTypeValidation device dtype, BasicArithmeticDTypeIsValid device dtype, shape ~ Broadcast shape shape) => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: mkldnnAdaptiveAvgPool2d :: forall (outputSize :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). All KnownNat '[channelSize, inputSize0, inputSize1, batchSize, Fst outputSize, Snd outputSize] => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, Fst outputSize, Snd outputSize]

+ Torch.Typed.Functional: mkldnnLinear :: forall (batchSize :: Nat) (inputFeatures :: Nat) (outputFeatures :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[outputFeatures, inputFeatures] -> Tensor device dtype '[outputFeatures] -> Tensor device dtype '[batchSize, inputFeatures] -> Tensor device dtype '[batchSize, outputFeatures]

+ Torch.Typed.Functional: mkldnnMaxPool2d :: forall (kernelSize :: (Nat, Nat)) (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst kernelSize, Snd kernelSize, Fst stride, Snd stride, Fst padding, Snd padding, channelSize, inputSize0, inputSize1, batchSize], ConvSideCheck inputSize0 (Fst kernelSize) (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 (Snd kernelSize) (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: mm :: forall (n :: Nat) (k :: Nat) (m :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[n, k] -> Tensor device dtype '[k, m] -> Tensor device dtype '[n, m]

+ Torch.Typed.Functional: mode :: forall (dim :: Nat) (keepOrDropDim :: KeepOrDropDim) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownKeepOrDropDim keepOrDropDim, shape' ~ ConditionalDropDimension shape dim keepOrDropDim, StandardDTypeValidation device dtype, AllDimsPositive shape) => Tensor device dtype shape -> (Tensor device dtype shape', Tensor device 'Int64 shape')

+ Torch.Typed.Functional: mseLoss :: forall (reduction :: Reduction) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownReduction reduction, shape' ~ ConditionalReduction shape reduction, StandardFloatingPointDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: mulScalar :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: mv :: forall (n :: Nat) (m :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[n, m] -> Tensor device dtype '[m] -> Tensor device dtype '[n]

+ Torch.Typed.Functional: narrow :: forall {k1} {k2} (dim :: Nat) (start :: Nat) (length :: Nat) (shape :: [Nat]) (mbSize :: k1) (mbNewShape :: k2) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[dim, start, length], All KnownNat shape) => Tensor device dtype shape -> Tensor device dtype (Narrow shape dim start length)

+ Torch.Typed.Functional: neg :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: nllLoss :: forall (reduction :: Reduction) (n :: Nat) (c :: Nat) (ds :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownReduction reduction, KnownNat n, KnownNat c, KnownShape ds) => Tensor device dtype '[c] -> Int -> Tensor device dtype (n ': (c ': ds)) -> Tensor device 'Int64 (n ': ds) -> Tensor device dtype (ConditionalReduction (n ': ds) reduction)

+ Torch.Typed.Functional: nonzero :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: numel :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Int

+ Torch.Typed.Functional: onesLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: orgqr :: forall (m :: Nat) (n :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, KnownNat m, n <= m) => Tensor device dtype '[m, n] -> Tensor device dtype '[n] -> Tensor device dtype '[m, n]

+ Torch.Typed.Functional: polygamma :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Int -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: pow :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (BasicArithmeticDTypeIsValid device dtype, shape'' ~ Broadcast shape shape') => Tensor device dtype shape -> Tensor device dtype shape' -> Tensor device dtype shape''

+ Torch.Typed.Functional: powScalar :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: prelu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype ('[] :: [Nat]) -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: qScale :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Double

+ Torch.Typed.Functional: qZeroPoint :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Int

+ Torch.Typed.Functional: quantizedMaxPool2d :: forall (kernelSize :: (Nat, Nat)) (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) (channelSize :: Nat) (inputSize0 :: Nat) (inputSize1 :: Nat) (batchSize :: Nat) (outputSize0 :: Nat) (outputSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[Fst kernelSize, Snd kernelSize, Fst stride, Snd stride, Fst padding, Snd padding, channelSize, inputSize0, inputSize1, batchSize], ConvSideCheck inputSize0 (Fst kernelSize) (Fst stride) (Fst padding) outputSize0, ConvSideCheck inputSize1 (Snd kernelSize) (Snd stride) (Snd padding) outputSize1) => Tensor device dtype '[batchSize, channelSize, inputSize0, inputSize1] -> Tensor device dtype '[batchSize, channelSize, outputSize0, outputSize1]

+ Torch.Typed.Functional: randLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.Functional: randnLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.Functional: reciprocal :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: relu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) t. (StandardFloatingPointDTypeValidation device dtype, IsUnnamed t device dtype shape) => t -> t

+ Torch.Typed.Functional: round :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: rsqrt :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: selu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: sigmoid :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: sign :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: sin :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) t. (StandardFloatingPointDTypeValidation device dtype, IsUnnamed t device dtype shape) => t -> t

+ Torch.Typed.Functional: sinh :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) t. (StandardFloatingPointDTypeValidation device dtype, IsUnnamed t device dtype shape) => t -> t

+ Torch.Typed.Functional: smoothL1Loss :: forall (reduction :: Reduction) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownReduction reduction => Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype (ConditionalReduction shape reduction)

+ Torch.Typed.Functional: softMarginLoss :: forall (reduction :: Reduction) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). KnownReduction reduction => Tensor device dtype shape -> Tensor device dtype shape -> Tensor device dtype (ConditionalReduction shape reduction)

+ Torch.Typed.Functional: softShrink :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Float -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: softmax :: forall (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, DimOutOfBoundCheck shape dim, KnownDType dtype, StandardFloatingPointDTypeValidation device dtype) => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: softplus :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: solve :: forall (m_k :: [Nat]) (m_m :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (Square m_m ~ m_m, FstSquareDim m_m ~ FstSquareDim m_k, 1 <= FstSquareDim m_m, SolveDTypeIsValid device dtype) => Tensor device dtype m_k -> Tensor device dtype m_m -> Tensor device dtype m_k

+ Torch.Typed.Functional: sortDim :: forall (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, HasDim dim shape) => Bool -> Tensor device dtype shape -> (Tensor device dtype shape, Tensor device 'Int64 shape)

+ Torch.Typed.Functional: sortNamedDim :: forall (dim :: Size) (shape :: Shape) (dtype :: DType) (device :: (DeviceType, Nat)). KnownNat (FindDim dim shape) => Bool -> NamedTensor device dtype shape -> (NamedTensor device dtype shape, NamedTensor device 'Int64 shape)

+ Torch.Typed.Functional: sqrt :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) t. (StandardFloatingPointDTypeValidation device dtype, IsUnnamed t device dtype shape) => t -> t

+ Torch.Typed.Functional: squeezeAll :: forall (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape' ~ SqueezeAll shape => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: squeezeDim :: forall (dim :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, shape' ~ SqueezeDim shape dim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: stack :: forall {k} (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) (tensors :: [k]). (KnownNat dim, '(shape, dtype, device) ~ Stack dim tensors, Castable (HList tensors) [ATenTensor]) => HList tensors -> Tensor device dtype shape

+ Torch.Typed.Functional: subScalar :: forall a (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Scalar a => a -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: sumAll :: forall (shape :: [Nat]) (dtype' :: DType) (dtype :: DType) (device :: (DeviceType, Nat)). (SumDTypeIsValid device dtype, dtype' ~ SumDType dtype) => Tensor device dtype shape -> Tensor device dtype' ('[] :: [Nat])

+ Torch.Typed.Functional: sumDim :: forall (d :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (KnownNat d, shape' ~ DropValue shape d, SumDTypeIsValid device dtype, dtype' ~ SumDType dtype) => Tensor device dtype shape -> Tensor device dtype' shape'

+ Torch.Typed.Functional: svd :: forall (reduced :: ReducedSVD) (shape :: [Nat]) (shapeU :: [Nat]) (shapeS :: [Nat]) (shapeV :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownReducedSVD reduced, '(shapeU, shapeS, shapeV) ~ SVDShapes shape reduced, SVDDTypeIsValid device dtype) => Tensor device dtype shape -> (Tensor device dtype shapeU, Tensor device dtype shapeS, Tensor device dtype shapeV)

+ Torch.Typed.Functional: symeig :: forall (shape :: [Nat]) (shape' :: [Nat]) (shape'' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape' ~ VectorOfSquare shape, shape'' ~ Square shape, SymeigDTypeIsValid device dtype) => Tri -> Tensor device dtype shape -> (Tensor device dtype shape', Tensor device dtype shape'')

+ Torch.Typed.Functional: symeigvalues :: forall (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape' ~ VectorOfSquare shape, SymeigDTypeIsValid device dtype) => Tri -> Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: t :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: tan :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: tanh :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: topk :: forall (k :: Nat) (dim :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat k, KnownNat dim, All KnownNat shape, TopKDeviceAndDTypeCheck dtype device, shape' ~ TopK k shape dim) => Bool -> Bool -> Tensor device dtype shape -> (Tensor device dtype shape', Tensor device 'Int64 shape')

+ Torch.Typed.Functional: trace :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: transpose :: forall (n :: Nat) (m :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat n, KnownNat m, shape' ~ Transpose shape n m) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: transpose2D :: forall (i :: Nat) (j :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[i, j] -> Tensor device dtype '[j, i]

+ Torch.Typed.Functional: tril :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape ~ MatrixOrMatrixBatch shape => Int -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: triu :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). shape ~ MatrixOrMatrixBatch shape => Int -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: trunc :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). StandardFloatingPointDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Functional: type BroadcastTensors (tensors :: [a]) = BroadcastTensorsCheck tensors BroadcastTensorsImpl tensors 'Nothing :: Maybe ([Nat], DType, (DeviceType, Nat))

+ Torch.Typed.Functional: type Cat (dim :: Nat) (tensors :: [a]) = CatCheck CatImpl dim tensors 'Nothing :: Maybe ([Nat], DType, (DeviceType, Nat))

+ Torch.Typed.Functional: type Chunk (chunks :: Nat) (dim :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)) = ChunkCheck shape dim ChunkImpl ChunkShapes chunks dim shape dtype device :: Maybe k

+ Torch.Typed.Functional: type ChunkShapes (chunks :: Nat) (dim :: Nat) (shape :: [Nat]) = ChunkShapesImpl ComputeChunks ExtractDim dim shape chunks dim shape

+ Torch.Typed.Functional: type ConvSideCheck (inputSize :: Nat) (kernelSize :: Nat) (stride :: Nat) (padding :: Nat) (outputSize :: Nat) = (1 <= kernelSize, 1 <= stride, kernelSize - 1 <= inputSize + 2 * padding, 1 <= outputSize, outputSize ~ ConvOutputSize inputSize kernelSize stride padding)

+ Torch.Typed.Functional: type GRUBHShape (hiddenSize :: Natural) (inputSize :: k) = '[3 * hiddenSize]

+ Torch.Typed.Functional: type GRUBIShape (hiddenSize :: Natural) (inputSize :: k) = '[3 * hiddenSize]

+ Torch.Typed.Functional: type GRUR (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) = GRUR' GRURImpl inputSize hiddenSize numLayers directionality dtype device :: [a]

+ Torch.Typed.Functional: type GRUWHShape (hiddenSize :: Natural) (inputSize :: k) = '[3 * hiddenSize, hiddenSize]

+ Torch.Typed.Functional: type GRUWIShape (hiddenSize :: Natural) (inputSize :: Natural) = '[3 * hiddenSize, inputSize]

+ Torch.Typed.Functional: type GatherDim (shape :: [Nat]) (shape' :: [Nat]) (dim :: Nat) = GatherDimCheck shape shape' dim GatherDimImpl shape shape' dim

+ Torch.Typed.Functional: type LSTMBHShape (hiddenSize :: Natural) (inputSize :: k) = '[4 * hiddenSize]

+ Torch.Typed.Functional: type LSTMBIShape (hiddenSize :: Natural) (inputSize :: k) = '[4 * hiddenSize]

+ Torch.Typed.Functional: type LSTMR (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) = LSTMR' LSTMRImpl inputSize hiddenSize numLayers directionality dtype device :: [a]

+ Torch.Typed.Functional: type LSTMWHShape (hiddenSize :: Natural) (inputSize :: k) = '[4 * hiddenSize, hiddenSize]

+ Torch.Typed.Functional: type LSTMWIShape (hiddenSize :: Natural) (inputSize :: Natural) = '[4 * hiddenSize, inputSize]

+ Torch.Typed.Functional: type SqueezeDim (shape :: [a]) (dim :: Nat) = SqueezeDimCheck shape dim SqueezeDimImpl shape dim

+ Torch.Typed.Functional: type Stack (dim :: Nat) (tensors :: [a]) = StackCheck StackImpl dim tensors 1

+ Torch.Typed.Functional: type TopK (k :: Nat) (shape :: [Nat]) (dim :: Nat) = TopKCheck k shape dim ExtractDim dim shape ReplaceDim dim shape k

+ Torch.Typed.Functional: type Unsqueeze (shape :: [a]) (dim :: Nat) = UnsqueezeCheck shape dim UnsqueezeImpl shape dim

+ Torch.Typed.Functional: type Upsample2d (shape :: [a]) (h :: a) (w :: a) = Upsample2dCheck shape h w

+ Torch.Typed.Functional: type family Upsample2dCheck (shape :: [a]) (h :: a) (w :: a) :: [a]

+ Torch.Typed.Functional: unsafeMeanAll :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). MeanDTypeValidation device dtype => Tensor device dtype shape -> Tensor device dtype ('[] :: [Nat])

+ Torch.Typed.Functional: unsqueeze :: forall (dim :: Nat) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, shape' ~ Unsqueeze shape dim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Functional: upsample_bicubic2d :: forall (w :: Nat) (h :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat h, KnownNat w, All KnownNat shape) => Bool -> Tensor device dtype shape -> Tensor device dtype (Upsample2d shape h w)

+ Torch.Typed.Functional: upsample_bilinear2d :: forall (w :: Nat) (h :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat h, KnownNat w, All KnownNat shape) => Bool -> Tensor device dtype shape -> Tensor device dtype (Upsample2d shape h w)

+ Torch.Typed.Functional: upsample_nearest2d :: forall (w :: Nat) (h :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat h, KnownNat w, All KnownNat shape) => Tensor device dtype shape -> Tensor device dtype (Upsample2d shape h w)

+ Torch.Typed.Functional: vecStack :: forall (dim :: Nat) (n :: Nat) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownNat n) => Vector n (Tensor device dtype shape) -> Tensor device dtype (Insert dim n shape)

+ Torch.Typed.Functional: zerosLike :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Lens: class HasField (field :: Symbol) (shape :: Shape)

+ Torch.Typed.Lens: class HasName (name :: Type -> Type) (shape :: Shape)

+ Torch.Typed.Lens: field :: forall (device :: (DeviceType, Nat)) (dtype :: DType). HasField field shape => Lens' (NamedTensor device dtype shape) (NamedTensor device dtype (DropField field shape))

+ Torch.Typed.Lens: fieldId :: FieldId field a => Proxy a -> Maybe Int

+ Torch.Typed.Lens: name :: forall (device :: (DeviceType, Nat)) (dtype :: DType). HasName name shape => Traversal' (NamedTensor device dtype shape) (NamedTensor device dtype (DropName name shape))

+ Torch.Typed.NN: forward :: HasForward f a b => f -> a -> b

+ Torch.Typed.NN: forwardStoch :: HasForward f a b => f -> a -> IO b

+ Torch.Typed.NN.Convolution: [Conv1d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[outputChannelSize, inputChannelSize, kernelSize] -> Parameter device dtype '[outputChannelSize] -> Conv1d inputChannelSize outputChannelSize kernelSize dtype device

+ Torch.Typed.NN.Convolution: [Conv2d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[outputChannelSize, inputChannelSize, kernelSize0, kernelSize1] -> Parameter device dtype '[outputChannelSize] -> Conv2d inputChannelSize outputChannelSize kernelSize0 kernelSize1 dtype device

+ Torch.Typed.NN.Convolution: [Conv3d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (kernelSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[outputChannelSize, inputChannelSize, kernelSize0, kernelSize1, kernelSize2] -> Parameter device dtype '[outputChannelSize] -> Conv3d inputChannelSize outputChannelSize kernelSize0 kernelSize1 kernelSize2 dtype device

+ Torch.Typed.NN.Convolution: [ConvTranspose1d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[inputChannelSize, outputChannelSize, kernelSize] -> Parameter device dtype '[outputChannelSize] -> ConvTranspose1d inputChannelSize outputChannelSize kernelSize dtype device

+ Torch.Typed.NN.Convolution: [ConvTranspose2d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[inputChannelSize, outputChannelSize, kernelSize0, kernelSize1] -> Parameter device dtype '[outputChannelSize] -> ConvTranspose2d inputChannelSize outputChannelSize kernelSize0 kernelSize1 dtype device

+ Torch.Typed.NN.Convolution: [ConvTranspose3d] :: forall (inputChannelSize :: Nat) (outputChannelSize :: Nat) (kernelSize0 :: Nat) (kernelSize1 :: Nat) (kernelSize2 :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[inputChannelSize, outputChannelSize, kernelSize0, kernelSize1, kernelSize2] -> Parameter device dtype '[outputChannelSize] -> ConvTranspose3d inputChannelSize outputChannelSize kernelSize0 kernelSize1 kernelSize2 dtype device

+ Torch.Typed.NN.Convolution: conv1dForward :: forall (stride :: Nat) (padding :: Nat) {kernelSize :: Nat} {inputSize :: Nat} {batchSize :: Nat} {outputChannelSize :: Nat} {inputChannelSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize (inputSize + (2 * padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize + (2 * padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 stride) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType stride) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize) :: Constraint), Assert (OrdCond (CmpNat (kernelSize - 1) (inputSize + (2 * padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize + (2 * padding))) :: Constraint), KnownNat batchSize, KnownNat inputSize, KnownNat kernelSize, KnownNat outputChannelSize, KnownNat inputChannelSize, KnownNat padding, KnownNat stride) => Conv1d inputChannelSize outputChannelSize kernelSize w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize + (2 * padding)) - kernelSize) stride + 1]

+ Torch.Typed.NN.Convolution: conv2dForward :: forall (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) {kernelSize1 :: Nat} {inputSize1 :: Nat} {kernelSize0 :: Nat} {inputSize0 :: Nat} {inputChannelSize :: Nat} {outputChannelSize :: Nat} {batchSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize1 (inputSize1 + (2 * Snd padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize1) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize0 (inputSize0 + (2 * Fst padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize0) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Snd stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Snd stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Fst stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Fst stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize0) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize0) :: Constraint), Assert (OrdCond (CmpNat (kernelSize0 - 1) (inputSize0 + (2 * Fst padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize0 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize1) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize1) :: Constraint), Assert (OrdCond (CmpNat (kernelSize1 - 1) (inputSize1 + (2 * Snd padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize1 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd padding))) :: Constraint), KnownNat inputChannelSize, KnownNat outputChannelSize, KnownNat kernelSize0, KnownNat kernelSize1, KnownNat inputSize0, KnownNat inputSize1, KnownNat batchSize, KnownNat (Fst stride), KnownNat (Fst padding), KnownNat (Snd stride), KnownNat (Snd padding)) => Conv2d inputChannelSize outputChannelSize kernelSize0 kernelSize1 w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize0, inputSize1] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize0 + (2 * Fst padding)) - kernelSize0) (Fst stride) + 1, Div ((inputSize1 + (2 * Snd padding)) - kernelSize1) (Snd stride) + 1]

+ Torch.Typed.NN.Convolution: conv3dForward :: forall (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) {kernelSize0 :: Nat} {inputSize0 :: Nat} {kernelSize2 :: Nat} {inputSize2 :: Nat} {kernelSize1 :: Nat} {inputSize1 :: Nat} {batchSize :: Nat} {outputChannelSize :: Nat} {inputChannelSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize0 (inputSize0 + (2 * Fst3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize0) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize2 (inputSize2 + (2 * Trd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize2) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize2 + (2 * Trd3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize1 (inputSize1 + (2 * Snd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize1) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Snd3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Snd3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Trd3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Trd3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Fst3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Fst3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize0) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize0) :: Constraint), Assert (OrdCond (CmpNat (kernelSize0 - 1) (inputSize0 + (2 * Fst3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize0 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst3 padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize1) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize1) :: Constraint), Assert (OrdCond (CmpNat (kernelSize1 - 1) (inputSize1 + (2 * Snd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize1 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd3 padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize2) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize2) :: Constraint), Assert (OrdCond (CmpNat (kernelSize2 - 1) (inputSize2 + (2 * Trd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize2 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize2 + (2 * Trd3 padding))) :: Constraint), KnownNat batchSize, KnownNat inputSize2, KnownNat inputSize1, KnownNat inputSize0, KnownNat kernelSize2, KnownNat kernelSize1, KnownNat kernelSize0, KnownNat outputChannelSize, KnownNat inputChannelSize, KnownNat (Trd3 padding), KnownNat (Trd3 stride), KnownNat (Snd3 padding), KnownNat (Snd3 stride), KnownNat (Fst3 padding), KnownNat (Fst3 stride)) => Conv3d inputChannelSize outputChannelSize kernelSize0 kernelSize1 kernelSize2 w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize0, inputSize1, inputSize2] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize0 + (2 * Fst3 padding)) - kernelSize0) (Fst3 stride) + 1, Div ((inputSize1 + (2 * Snd3 padding)) - kernelSize1) (Snd3 stride) + 1, Div ((inputSize2 + (2 * Trd3 padding)) - kernelSize2) (Trd3 stride) + 1]

+ Torch.Typed.NN.Convolution: convTranspose1dForward :: forall (stride :: Nat) (padding :: Nat) {kernelSize :: Nat} {inputSize :: Nat} {batchSize :: Nat} {outputChannelSize :: Nat} {inputChannelSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize (inputSize + (2 * padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize + (2 * padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 stride) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType stride) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize) :: Constraint), Assert (OrdCond (CmpNat (kernelSize - 1) (inputSize + (2 * padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize + (2 * padding))) :: Constraint), KnownNat batchSize, KnownNat inputSize, KnownNat kernelSize, KnownNat outputChannelSize, KnownNat inputChannelSize, KnownNat padding, KnownNat stride) => ConvTranspose1d inputChannelSize outputChannelSize kernelSize w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize + (2 * padding)) - kernelSize) stride + 1]

+ Torch.Typed.NN.Convolution: convTranspose2dForward :: forall (stride :: (Nat, Nat)) (padding :: (Nat, Nat)) {kernelSize1 :: Nat} {inputSize1 :: Nat} {kernelSize0 :: Nat} {inputSize0 :: Nat} {inputChannelSize :: Nat} {outputChannelSize :: Nat} {batchSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize1 (inputSize1 + (2 * Snd padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize1) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize0 (inputSize0 + (2 * Fst padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize0) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Snd stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Snd stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Fst stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Fst stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize0) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize0) :: Constraint), Assert (OrdCond (CmpNat (kernelSize0 - 1) (inputSize0 + (2 * Fst padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize0 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize1) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize1) :: Constraint), Assert (OrdCond (CmpNat (kernelSize1 - 1) (inputSize1 + (2 * Snd padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize1 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd padding))) :: Constraint), KnownNat inputChannelSize, KnownNat outputChannelSize, KnownNat kernelSize0, KnownNat kernelSize1, KnownNat inputSize0, KnownNat inputSize1, KnownNat batchSize, KnownNat (Fst stride), KnownNat (Fst padding), KnownNat (Snd stride), KnownNat (Snd padding)) => ConvTranspose2d inputChannelSize outputChannelSize kernelSize0 kernelSize1 w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize0, inputSize1] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize0 + (2 * Fst padding)) - kernelSize0) (Fst stride) + 1, Div ((inputSize1 + (2 * Snd padding)) - kernelSize1) (Snd stride) + 1]

+ Torch.Typed.NN.Convolution: convTranspose3dForward :: forall (stride :: (Nat, Nat, Nat)) (padding :: (Nat, Nat, Nat)) {kernelSize0 :: Nat} {inputSize0 :: Nat} {kernelSize2 :: Nat} {inputSize2 :: Nat} {kernelSize1 :: Nat} {inputSize1 :: Nat} {batchSize :: Nat} {outputChannelSize :: Nat} {inputChannelSize :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)}. (Assert (OrdCond (CmpNat kernelSize0 (inputSize0 + (2 * Fst3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize0) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize2 (inputSize2 + (2 * Trd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize2) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize2 + (2 * Trd3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat kernelSize1 (inputSize1 + (2 * Snd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType kernelSize1) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd3 padding))) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Snd3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Snd3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Trd3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Trd3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 (Fst3 stride)) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType (Fst3 stride)) :: Constraint) ~ (), Assert (OrdCond (CmpNat 1 kernelSize0) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize0) :: Constraint), Assert (OrdCond (CmpNat (kernelSize0 - 1) (inputSize0 + (2 * Fst3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize0 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize0 + (2 * Fst3 padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize1) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize1) :: Constraint), Assert (OrdCond (CmpNat (kernelSize1 - 1) (inputSize1 + (2 * Snd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize1 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize1 + (2 * Snd3 padding))) :: Constraint), Assert (OrdCond (CmpNat 1 kernelSize2) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType 1) ':<>: 'Text " <= ") ':<>: 'ShowType kernelSize2) :: Constraint), Assert (OrdCond (CmpNat (kernelSize2 - 1) (inputSize2 + (2 * Trd3 padding))) 'True 'True 'False) (TypeError ((('Text "Cannot satisfy: " ':<>: 'ShowType (kernelSize2 - 1)) ':<>: 'Text " <= ") ':<>: 'ShowType (inputSize2 + (2 * Trd3 padding))) :: Constraint), KnownNat batchSize, KnownNat inputSize2, KnownNat inputSize1, KnownNat inputSize0, KnownNat kernelSize2, KnownNat kernelSize1, KnownNat kernelSize0, KnownNat outputChannelSize, KnownNat inputChannelSize, KnownNat (Trd3 padding), KnownNat (Trd3 stride), KnownNat (Snd3 padding), KnownNat (Snd3 stride), KnownNat (Fst3 padding), KnownNat (Fst3 stride)) => ConvTranspose3d inputChannelSize outputChannelSize kernelSize0 kernelSize1 kernelSize2 w1 w2 -> Tensor w2 w1 '[batchSize, inputChannelSize, inputSize0, inputSize1, inputSize2] -> Tensor w2 w1 '[batchSize, outputChannelSize, Div ((inputSize0 + (2 * Fst3 padding)) - kernelSize0) (Fst3 stride) + 1, Div ((inputSize1 + (2 * Snd3 padding)) - kernelSize1) (Snd3 stride) + 1, Div ((inputSize2 + (2 * Trd3 padding)) - kernelSize2) (Trd3 stride) + 1]

+ Torch.Typed.NN.DataParallel: class HasGradConcurrently (device' :: k) (devices :: k1) (parameters :: [k2]) (losses :: [k3]) (gradients :: [k4]) | device' devices parameters losses -> gradients

+ Torch.Typed.NN.DataParallel: class ReduceGradients (device' :: (DeviceType, Nat)) (devices :: [(DeviceType, Nat)]) (xxs :: [k]) (ys :: [k1]) | device' devices xxs -> ys

+ Torch.Typed.NN.DataParallel: forwardConcurrently :: forall {k} (models :: [k]) (inputs :: [k]) (outputs :: [k]). HZipWithM Concurrently ForwardConcurrentlyF models inputs outputs => HList models -> HList inputs -> Concurrently (HList outputs)

+ Torch.Typed.NN.DataParallel: forwardConcurrently' :: forall {k} (devices' :: [(DeviceType, Nat)]) (device' :: k) (device :: (DeviceType, Nat)) model input output (models :: [Type]) (inputs :: [Type]) (outputs :: [Type]). ('Just device ~ GetDevice model, 'Just device ~ GetDevice input, HasScatter devices' device input inputs, HasReplicate devices' device model models, HZipWithM Concurrently ForwardConcurrentlyF models inputs outputs, HasGather device' devices' outputs output) => model -> input -> IO output

+ Torch.Typed.NN.DataParallel: forwardConcurrentlyStoch :: forall {k} (models :: [k]) (inputs :: [k]) (outputs :: [k]). HZipWithM Concurrently ForwardConcurrentlyF models inputs outputs => HList models -> HList inputs -> Concurrently (HList outputs)

+ Torch.Typed.NN.DataParallel: forwardConcurrentlyStoch' :: forall {k} (devices' :: [(DeviceType, Nat)]) (device' :: k) (device :: (DeviceType, Nat)) model input output (models :: [Type]) (inputs :: [Type]) (outputs :: [Type]). ('Just device ~ GetDevice model, 'Just device ~ GetDevice input, HasScatter devices' device input inputs, HasReplicate devices' device model models, HZipWithM Concurrently ForwardConcurrentlyF models inputs outputs, HasGather device' devices' outputs output) => model -> input -> IO output

+ Torch.Typed.NN.Dropout: dropoutForward :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Dropout -> Bool -> Tensor device dtype shape -> IO (Tensor device dtype shape)

+ Torch.Typed.NN.Linear: [Linear] :: forall (inputFeatures :: Nat) (outputFeatures :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[outputFeatures, inputFeatures] -> Parameter device dtype '[outputFeatures] -> Linear inputFeatures outputFeatures dtype device

+ Torch.Typed.NN.Linear: linearForward :: forall {inputFeatures :: Nat} {outputFeatures :: Nat} {w1 :: DType} {w2 :: (DeviceType, Nat)} {shape :: [Nat]}. Linear inputFeatures outputFeatures w1 w2 -> Tensor w2 w1 shape -> Tensor w2 w1 (CheckBroadcast (CheckMatMul shape '[inputFeatures, outputFeatures] (ComputeMatMul (ReverseImpl shape ('[] :: [Nat])) '[outputFeatures, inputFeatures])) (CheckMatMul shape '[inputFeatures, outputFeatures] (ComputeMatMul (ReverseImpl shape ('[] :: [Nat])) '[outputFeatures, inputFeatures])) (ComputeBroadcast (ReverseImpl (CheckMatMul shape '[inputFeatures, outputFeatures] (ComputeMatMul (ReverseImpl shape ('[] :: [Nat])) '[outputFeatures, inputFeatures])) ('[] :: [Nat])) (ReverseImpl (CheckMatMul shape '[inputFeatures, outputFeatures] (ComputeMatMul (ReverseImpl shape ('[] :: [Nat])) '[outputFeatures, inputFeatures])) ('[] :: [Nat]))))

+ Torch.Typed.NN.Normalization: [LayerNormSpec] :: forall (normalizedShape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Double -> LayerNormSpec normalizedShape dtype device

+ Torch.Typed.NN.Normalization: [LayerNorm] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (normalizedShape :: [Nat]). Parameter device dtype normalizedShape -> Parameter device dtype normalizedShape -> Double -> LayerNorm normalizedShape dtype device

+ Torch.Typed.NN.Normalization: layerNormForward :: forall (normalizedShape :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (IsSuffixOf normalizedShape shape, KnownShape normalizedShape) => LayerNorm normalizedShape dtype device -> Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.NN.Recurrent.Cell.GRU: gruCellForward :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => GRUCell inputDim hiddenDim dtype device -> Tensor device dtype '[batchSize, hiddenDim] -> Tensor device dtype '[batchSize, inputDim] -> Tensor device dtype '[batchSize, hiddenDim]

+ Torch.Typed.NN.Recurrent.Cell.GRU: gruCellScan :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => GRUCell inputDim hiddenDim dtype device -> Tensor device dtype '[batchSize, hiddenDim] -> [Tensor device dtype '[batchSize, inputDim]] -> [Tensor device dtype '[batchSize, hiddenDim]]

+ Torch.Typed.NN.Recurrent.Cell.GRU: gruFold :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => GRUCell inputDim hiddenDim dtype device -> Tensor device dtype '[batchSize, hiddenDim] -> [Tensor device dtype '[batchSize, inputDim]] -> Tensor device dtype '[batchSize, hiddenDim]

+ Torch.Typed.NN.Recurrent.Cell.LSTM: lstmCellFold :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => LSTMCell inputDim hiddenDim dtype device -> (Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim]) -> [Tensor device dtype '[batchSize, inputDim]] -> (Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim])

+ Torch.Typed.NN.Recurrent.Cell.LSTM: lstmCellForward :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => LSTMCell inputDim hiddenDim dtype device -> (Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim]) -> Tensor device dtype '[batchSize, inputDim] -> (Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim])

+ Torch.Typed.NN.Recurrent.Cell.LSTM: lstmCellScan :: forall (inputDim :: Nat) (hiddenDim :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDType dtype, KnownNat inputDim, KnownNat hiddenDim, KnownNat batchSize) => LSTMCell inputDim hiddenDim dtype device -> (Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim]) -> [Tensor device dtype '[batchSize, inputDim]] -> [(Tensor device dtype '[batchSize, hiddenDim], Tensor device dtype '[batchSize, hiddenDim])]

+ Torch.Typed.NN.Recurrent.GRU: [GRUBidirectionalLayer] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (inputSize :: Nat). 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

+ Torch.Typed.NN.Recurrent.GRU: [GRULayer1] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRULayer inputSize hiddenSize directionality dtype device -> GRULayerStack inputSize hiddenSize 1 directionality dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRULayerK] :: forall (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) (inputSize :: Nat) (numLayers1 :: Natural). GRULayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device -> GRULayerStack inputSize hiddenSize numLayers1 directionality dtype device -> GRULayerStack inputSize hiddenSize (numLayers1 + 1) directionality dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRUUnidirectionalLayer] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (inputSize :: Nat). 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

+ Torch.Typed.NN.Recurrent.GRU: [GRUWithConstInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRUSpec inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRUWithConstInit] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRU inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> GRUWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRUWithLearnedInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRUSpec inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRUWithLearnedInit] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRU inputSize hiddenSize numLayers directionality dtype device -> Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> GRUWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRUWithZerosInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). GRUSpec inputSize hiddenSize numLayers directionality dtype device -> GRUWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.GRU: [GRU] :: forall (numLayers :: Nat) (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). 1 <= numLayers => GRULayerStack inputSize hiddenSize numLayers directionality dtype device -> Dropout -> GRU inputSize hiddenSize numLayers directionality dtype device

+ Torch.Typed.NN.Recurrent.GRU: class GRULayerStackParameterized (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) where {

+ Torch.Typed.NN.Recurrent.GRU: class GRULayerStackRandomizable (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat))

+ Torch.Typed.NN.Recurrent.GRU: gruForward :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hcShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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 :: [Type]), 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)

+ Torch.Typed.NN.Recurrent.GRU: gruForwardWithDropout :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hcShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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 :: [Type]), 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)

+ Torch.Typed.NN.Recurrent.GRU: gruForwardWithoutDropout :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hcShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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 :: [Type]), 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)

+ Torch.Typed.NN.Recurrent.GRU: type GRULayerStackParameters (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) :: [Type];

+ Torch.Typed.NN.Recurrent.GRU: xavierUniformGRU :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (featureSize :: Nat). (KnownDType dtype, KnownNat hiddenSize, KnownNat featureSize, KnownDevice device, RandDTypeIsValid device dtype) => IO (Tensor device dtype '[3 * hiddenSize, featureSize])

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMBidirectionalLayer] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (inputSize :: Nat). Parameter device dtype (LSTMWIShape hiddenSize inputSize) -> Parameter device dtype (LSTMWHShape hiddenSize inputSize) -> Parameter device dtype (LSTMBIShape hiddenSize inputSize) -> Parameter device dtype (LSTMBHShape hiddenSize inputSize) -> Parameter device dtype (LSTMWIShape hiddenSize inputSize) -> Parameter device dtype (LSTMWHShape hiddenSize inputSize) -> Parameter device dtype (LSTMBIShape hiddenSize inputSize) -> Parameter device dtype (LSTMBHShape hiddenSize inputSize) -> LSTMLayer inputSize hiddenSize 'Bidirectional dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMLayer1] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTMLayer inputSize hiddenSize directionality dtype device -> LSTMLayerStack inputSize hiddenSize 1 directionality dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMLayerK] :: forall (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) (inputSize :: Nat) (numLayers1 :: Natural). LSTMLayer (hiddenSize * NumberOfDirections directionality) hiddenSize directionality dtype device -> LSTMLayerStack inputSize hiddenSize numLayers1 directionality dtype device -> LSTMLayerStack inputSize hiddenSize (numLayers1 + 1) directionality dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMUnidirectionalLayer] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (inputSize :: Nat). Parameter device dtype (LSTMWIShape hiddenSize inputSize) -> Parameter device dtype (LSTMWHShape hiddenSize inputSize) -> Parameter device dtype (LSTMBIShape hiddenSize inputSize) -> Parameter device dtype (LSTMBHShape hiddenSize inputSize) -> LSTMLayer inputSize hiddenSize 'Unidirectional dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMWithConstInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTMSpec inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> LSTMWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMWithConstInit] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTM inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> LSTMWithInit inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMWithLearnedInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTMSpec inputSize hiddenSize numLayers directionality dtype device -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> Tensor device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> LSTMWithInitSpec inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMWithLearnedInit] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTM inputSize hiddenSize numLayers directionality dtype device -> Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> Parameter device dtype '[numLayers * NumberOfDirections directionality, hiddenSize] -> LSTMWithInit inputSize hiddenSize numLayers directionality 'LearnedInitialization dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTMWithZerosInitSpec] :: forall (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). LSTMSpec inputSize hiddenSize numLayers directionality dtype device -> LSTMWithInitSpec inputSize hiddenSize numLayers directionality 'ConstantInitialization dtype device

+ Torch.Typed.NN.Recurrent.LSTM: [LSTM] :: forall (numLayers :: Nat) (inputSize :: Nat) (hiddenSize :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)). 1 <= numLayers => LSTMLayerStack inputSize hiddenSize numLayers directionality dtype device -> Dropout -> LSTM inputSize hiddenSize numLayers directionality dtype device

+ Torch.Typed.NN.Recurrent.LSTM: class LSTMLayerStackParameterized (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) where {

+ Torch.Typed.NN.Recurrent.LSTM: class LSTMLayerStackRandomizable (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat))

+ Torch.Typed.NN.Recurrent.LSTM: lstmForward :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hxShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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, hxShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (LSTM inputSize hiddenSize numLayers directionality dtype device), Parameterized (LSTM inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ (LSTMR inputSize hiddenSize numLayers directionality dtype device :: [Type]), Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => Bool -> LSTMWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hxShape, Tensor device dtype hxShape)

+ Torch.Typed.NN.Recurrent.LSTM: lstmForwardWithDropout :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hxShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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, hxShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (LSTM inputSize hiddenSize numLayers directionality dtype device), Parameterized (LSTM inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ (LSTMR inputSize hiddenSize numLayers directionality dtype device :: [Type]), Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => LSTMWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hxShape, Tensor device dtype hxShape)

+ Torch.Typed.NN.Recurrent.LSTM: lstmForwardWithoutDropout :: forall (shapeOrder :: RNNShapeOrder) (batchSize :: Nat) (seqLen :: Nat) (directionality :: RNNDirectionality) (initialization :: RNNInitialization) (numLayers :: Nat) (inputSize :: Nat) (outputSize :: Natural) (hiddenSize :: Nat) (inputShape :: [Nat]) (outputShape :: [Nat]) (hxShape :: [Natural]) (parameters :: [Type]) (tensorParameters :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (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, hxShape ~ '[numLayers * NumberOfDirections directionality, batchSize, hiddenSize], parameters ~ Parameters (LSTM inputSize hiddenSize numLayers directionality dtype device), Parameterized (LSTM inputSize hiddenSize numLayers directionality dtype device), tensorParameters ~ (LSTMR inputSize hiddenSize numLayers directionality dtype device :: [Type]), Castable (HList tensorParameters) [ATenTensor], HMap' ToDependent parameters tensorParameters) => LSTMWithInit inputSize hiddenSize numLayers directionality initialization dtype device -> Tensor device dtype inputShape -> (Tensor device dtype outputShape, Tensor device dtype hxShape, Tensor device dtype hxShape)

+ Torch.Typed.NN.Recurrent.LSTM: type LSTMLayerStackParameters (flag :: Bool) (inputSize :: Nat) (hiddenSize :: Nat) (numLayers :: Nat) (directionality :: RNNDirectionality) (dtype :: DType) (device :: (DeviceType, Nat)) :: [Type];

+ Torch.Typed.NN.Recurrent.LSTM: xavierUniformLSTM :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (hiddenSize :: Nat) (featureSize :: Nat). (KnownDType dtype, KnownNat hiddenSize, KnownNat featureSize, KnownDevice device, RandDTypeIsValid device dtype) => IO (Tensor device dtype '[4 * hiddenSize, featureSize])

+ Torch.Typed.NN.Sparse: [ConstEmbeddingSpec] :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[numEmbeds, embedSize] -> EmbeddingSpec paddingIdx numEmbeds embedSize 'Constant dtype device

+ Torch.Typed.NN.Sparse: [ConstEmbedding] :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[numEmbeds, embedSize] -> Embedding paddingIdx numEmbeds embedSize 'Constant dtype device

+ Torch.Typed.NN.Sparse: [LearnedEmbeddingWithCustomInitSpec] :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype '[numEmbeds, embedSize] -> EmbeddingSpec paddingIdx numEmbeds embedSize 'Learned dtype device

+ Torch.Typed.NN.Sparse: [LearnedEmbeddingWithRandomInitSpec] :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). EmbeddingSpec paddingIdx numEmbeds embedSize 'Learned dtype device

+ Torch.Typed.NN.Sparse: [LearnedEmbedding] :: forall (paddingIdx :: Maybe Nat) (numEmbeds :: Nat) (embedSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype '[numEmbeds, embedSize] -> Embedding paddingIdx numEmbeds embedSize 'Learned dtype device

+ Torch.Typed.NN.Sparse: embed :: forall (paddingIdx :: Maybe Nat) (shape :: [Nat]) (numEmbeds :: Nat) (embedSize :: Nat) (embeddingType :: EmbeddingType) (dtype :: DType) (device :: (DeviceType, Nat)) (shape' :: [Nat]). (KnownMaybeNat paddingIdx, PaddingIdxCheck paddingIdx numEmbeds, shape' ~ Reverse (embedSize ': Reverse shape)) => Embedding paddingIdx numEmbeds embedSize embeddingType dtype device -> Tensor device 'Int64 shape -> Tensor device dtype shape'

+ Torch.Typed.NN.Transformer: [MultiheadAttentionSpec] :: forall (embedDim :: Nat) (kEmbedDim :: Nat) (vEmbedDim :: Nat) (numHeads :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). DropoutSpec -> MultiheadAttentionSpec embedDim kEmbedDim vEmbedDim numHeads dtype device

+ Torch.Typed.NN.Transformer: [MultiheadAttention] :: forall (embedDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)) (kEmbedDim :: Nat) (vEmbedDim :: Nat) (numHeads :: Nat). Linear embedDim embedDim dtype device -> Linear kEmbedDim embedDim dtype device -> Linear vEmbedDim embedDim dtype device -> Linear embedDim embedDim dtype device -> Dropout -> MultiheadAttention embedDim kEmbedDim vEmbedDim numHeads dtype device

+ Torch.Typed.NN.Transformer: [TransformerLMSpec] :: forall (numAttnLayers :: Nat) (numHeads :: Nat) (ffnDim :: Nat) (paddingIdx :: Nat) (numEmbeds :: Nat) (embedDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). DropoutSpec -> TransformerLayerSpec embedDim embedDim embedDim numHeads ffnDim dtype device -> TransformerLMSpec numAttnLayers numHeads ffnDim paddingIdx numEmbeds embedDim dtype device

+ Torch.Typed.NN.Transformer: [TransformerLM] :: forall (numAttnLayers :: Nat) (numHeads :: Nat) (ffnDim :: Nat) (paddingIdx :: Nat) (numEmbeds :: Nat) (embedDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Embedding ('Just paddingIdx) numEmbeds embedDim 'Learned dtype device -> Embedding ('Nothing :: Maybe Nat) 2048 embedDim 'Constant dtype device -> Dropout -> HList (HReplicateR numAttnLayers (TransformerLayer embedDim embedDim embedDim numHeads ffnDim dtype device)) -> Linear embedDim numEmbeds dtype device -> TransformerLM numAttnLayers numHeads ffnDim paddingIdx numEmbeds embedDim dtype device

+ Torch.Typed.NN.Transformer: [TransformerLayerSpec] :: forall (embedDim :: Nat) (kEmbedDim :: Nat) (vEmbedDim :: Nat) (numHeads :: Nat) (ffnDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). MultiheadAttentionSpec embedDim kEmbedDim vEmbedDim numHeads dtype device -> DropoutSpec -> Double -> TransformerMLPSpec embedDim ffnDim dtype device -> TransformerLayerSpec embedDim kEmbedDim vEmbedDim numHeads ffnDim dtype device

+ Torch.Typed.NN.Transformer: [TransformerLayer] :: forall (embedDim :: Nat) (kEmbedDim :: Nat) (vEmbedDim :: Nat) (numHeads :: Nat) (ffnDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). MultiheadAttention embedDim kEmbedDim vEmbedDim numHeads dtype device -> Dropout -> LayerNorm '[embedDim] dtype device -> TransformerMLP embedDim ffnDim dtype device -> TransformerLayer embedDim kEmbedDim vEmbedDim numHeads ffnDim dtype device

+ Torch.Typed.NN.Transformer: [TransformerMLPSpec] :: forall (embedDim :: Nat) (ffnDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). DropoutSpec -> DropoutSpec -> Double -> TransformerMLPSpec embedDim ffnDim dtype device

+ Torch.Typed.NN.Transformer: [TransformerMLP] :: forall (embedDim :: Nat) (ffnDim :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). Linear embedDim ffnDim dtype device -> Linear ffnDim embedDim dtype device -> Dropout -> Dropout -> LayerNorm '[embedDim] dtype device -> TransformerMLP embedDim ffnDim dtype device

+ Torch.Typed.NN.Transformer: multiheadAttention :: forall (embedDim :: Natural) (kEmbedDim :: Natural) (vEmbedDim :: Natural) (numHeads :: Natural) (seqLen :: Natural) (seqLen' :: Natural) (batchSize :: Natural) (headDim :: Natural) (dtype :: DType) (device :: (DeviceType, Nat)). (1 <= numHeads, embedDim ~ (headDim * numHeads), All KnownNat '[embedDim, kEmbedDim, vEmbedDim, numHeads, seqLen, seqLen', batchSize, headDim], KnownDType dtype, StandardFloatingPointDTypeValidation device dtype, MatMulDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype, dtype ~ SumDType dtype, SumDTypeIsValid device dtype, KnownDevice device) => MultiheadAttention embedDim kEmbedDim vEmbedDim numHeads dtype device -> Bool -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen]) -> Maybe (Tensor device 'Bool '[batchSize, seqLen]) -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen, headDim]) -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen, headDim]) -> Tensor device dtype '[batchSize, seqLen', embedDim] -> Tensor device dtype '[batchSize, seqLen, kEmbedDim] -> Tensor device dtype '[batchSize, seqLen, vEmbedDim] -> IO (Tensor device dtype '[batchSize, seqLen', embedDim], Tensor device dtype '[batchSize, seqLen', seqLen])

+ Torch.Typed.NN.Transformer: sinusoidal :: forall (numEmbeds :: Nat) (embedDim :: Nat) (device :: (DeviceType, Nat)). (All KnownNat '[numEmbeds, embedDim], 1 <= numEmbeds, 1 <= Div embedDim 2, (Div embedDim 2 * 2) ~ embedDim, StandardFloatingPointDTypeValidation device 'Float, BasicArithmeticDTypeIsValid device 'Float, KnownDevice device) => Tensor device 'Float '[numEmbeds, embedDim]

+ Torch.Typed.NN.Transformer: transformerLM :: forall (numAttnLayers :: Nat) (numHeads :: Nat) (ffnDim :: Nat) (paddingIdx :: Nat) (numEmbeds :: Natural) (embedDim :: Nat) (seqLen :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (All KnownNat '[paddingIdx, embedDim, seqLen, batchSize], (paddingIdx + 1) <= numEmbeds, 1 <= seqLen, HFoldrM IO (FoldLayers batchSize seqLen dtype device) (Tensor device dtype '[batchSize, seqLen, embedDim]) (HReplicateR numAttnLayers (TransformerLayer embedDim embedDim embedDim numHeads ffnDim dtype device)) (Tensor device dtype '[batchSize, seqLen, embedDim]), BasicArithmeticDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device 'Int64, KnownDType dtype, KnownDevice device) => TransformerLM numAttnLayers numHeads ffnDim paddingIdx numEmbeds embedDim dtype device -> Bool -> Tensor device 'Int64 '[batchSize, seqLen] -> IO (Tensor device dtype '[batchSize, seqLen, numEmbeds])

+ Torch.Typed.NN.Transformer: transformerLayer :: forall (numHeads :: Nat) (ffnDim :: Nat) (embedDim :: Nat) (kEmbedDim :: Nat) (vEmbedDim :: Nat) (headDim :: Nat) (seqLen :: Nat) (seqLen' :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (1 <= numHeads, embedDim ~ (headDim * numHeads), All KnownNat '[embedDim, kEmbedDim, vEmbedDim, numHeads, seqLen, seqLen', batchSize, headDim], IsSuffixOf '[embedDim] '[batchSize, seqLen', embedDim], KnownDType dtype, dtype ~ SumDType dtype, StandardFloatingPointDTypeValidation device dtype, MatMulDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype, SumDTypeIsValid device dtype, KnownDevice device) => TransformerLayer embedDim kEmbedDim vEmbedDim numHeads ffnDim dtype device -> Bool -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen]) -> Maybe (Tensor device 'Bool '[batchSize, seqLen]) -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen, headDim]) -> Maybe (Tensor device dtype '[batchSize, seqLen', seqLen, headDim]) -> Tensor device dtype '[batchSize, seqLen', embedDim] -> Tensor device dtype '[batchSize, seqLen, kEmbedDim] -> Tensor device dtype '[batchSize, seqLen, vEmbedDim] -> IO (Tensor device dtype '[batchSize, seqLen', embedDim])

+ Torch.Typed.NN.Transformer: transformerMLP :: forall (embedDim :: Nat) (ffnDim :: Nat) (seqLen :: Nat) (batchSize :: Nat) (dtype :: DType) (device :: (DeviceType, Nat)). (BasicArithmeticDTypeIsValid device dtype, StandardFloatingPointDTypeValidation device dtype, KnownNat embedDim, IsSuffixOf '[embedDim] '[seqLen, batchSize, embedDim]) => TransformerMLP embedDim ffnDim dtype device -> Bool -> Tensor device dtype '[seqLen, batchSize, embedDim] -> IO (Tensor device dtype '[seqLen, batchSize, embedDim])

+ Torch.Typed.NamedTensor: type ToNestedList a;

+ Torch.Typed.Optim: AdamParameterUpdate :: Float -> LearningRate device dtype -> AdamParameterUpdate (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: GDMStep :: Float -> LearningRate device dtype -> GDMStep (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: GDStep :: LearningRate device dtype -> GDStep (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: adam :: forall {k} (gradients :: [Type]) (tensors :: [Type]) (momenta :: [Type]) (adamStep :: k) (dtype :: DType) (device :: (DeviceType, Nat)). (HZipWith AdamMomentum1Update momenta gradients momenta, HZipWith AdamMomentum2Update momenta gradients momenta, HMap' AdamBiasAdjustment momenta momenta, HZipWith3 (AdamParameterUpdate device dtype) tensors momenta momenta tensors) => LearningRate device dtype -> HList gradients -> HList tensors -> Adam momenta -> (HList tensors, Adam momenta)

+ Torch.Typed.Optim: class Optimizer optim (gradients :: [k]) (tensors :: [k1]) (dtype :: DType) (device :: (DeviceType, Nat))

+ Torch.Typed.Optim: data AdamParameterUpdate (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: data GDMStep (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: gd :: forall {k} (gradients :: [k]) (tensors :: [k]) (dtype :: DType) (device :: (DeviceType, Nat)). HZipWith (GDStep device dtype) tensors gradients tensors => LearningRate device dtype -> HList gradients -> HList tensors -> GD -> (HList tensors, GD)

+ Torch.Typed.Optim: gdm :: forall (gradients :: [Type]) (tensors :: [Type]) (momenta :: [Type]) (gdmStep :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (HZipWith3 (GDMStep device dtype) tensors gradients momenta gdmStep, HMap' AFst gdmStep tensors, HMap' ASnd gdmStep momenta) => LearningRate device dtype -> HList gradients -> HList tensors -> GDM momenta -> (HList tensors, GDM momenta)

+ Torch.Typed.Optim: mkAdam :: forall (parameters :: [Type]) (momenta :: [Type]). HMap' ZerosLike parameters momenta => AdamIter -> Float -> Float -> HList parameters -> Adam momenta

+ Torch.Typed.Optim: mkGDM :: forall (parameters :: [Type]) (momenta :: [Type]). HMap' ZerosLike parameters momenta => Float -> HList parameters -> GDM momenta

+ Torch.Typed.Optim: newtype GDStep (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Optim: runStep :: forall model optim (parameters :: [Type]) (gradients :: [Type]) (tensors :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (Parameterized model, parameters ~ Parameters model, HasGrad (HList parameters) (HList gradients), tensors ~ gradients, HMap' ToDependent parameters tensors, Castable (HList gradients) [ATenTensor], Optimizer optim gradients tensors dtype device, HMapM' IO MakeIndependent tensors parameters) => model -> optim -> Loss device dtype -> LearningRate device dtype -> IO (model, optim)

+ Torch.Typed.Optim: runStep' :: forall model optim (parameters :: [Type]) (gradients :: [Type]) (tensors :: [Type]) (dtype :: DType) (device :: (DeviceType, Nat)). (Parameterized model, parameters ~ Parameters model, tensors ~ gradients, HMap' ToDependent parameters tensors, Optimizer optim gradients tensors dtype device, HMapM' IO MakeIndependent tensors parameters) => model -> optim -> LearningRate device dtype -> HList gradients -> IO (model, optim)

+ Torch.Typed.Optim: type AdamIter = Tensor '( 'CPU, 0) 'Int64 '[] :: [Nat]

+ Torch.Typed.Optim: type LearningRate (device :: (DeviceType, Nat)) (dtype :: DType) = Tensor device dtype '[] :: [Nat]

+ Torch.Typed.Optim: type Loss (device :: (DeviceType, Nat)) (dtype :: DType) = Tensor device dtype '[] :: [Nat]

+ Torch.Typed.Optim.CppOptim: initOptimizer :: forall model (tensors :: [Type]). (CppOptimizer option, Parameterized model, HMap' ToDependent (Parameters model) tensors, Castable (HList tensors) [ATenTensor]) => option -> model -> IO (CppOptimizerState option (Parameters model))

+ Torch.Typed.Optim.CppOptim: runStep :: forall option model (tensors :: [Type]) (dev :: (DeviceType, Nat)) (dtype :: DType). (CppOptimizer option, Parameterized model, HMap' ToDependent (Parameters model) tensors, HMap' ToParameter tensors (Parameters model), Castable (HList tensors) [ATenTensor]) => model -> CppOptimizerState option (Parameters model) -> Loss dev dtype -> IO (model, CppOptimizerState option (Parameters model))

+ Torch.Typed.Optim.CppOptim: unsafeStep :: forall model (dev :: (DeviceType, Nat)) (dtype :: DType) (lossShape :: [Nat]) (tensors :: [Type]) res. (CppOptimizer option, Parameterized model, HMap' ToDependent (Parameters model) tensors, HMap' ToParameter tensors (Parameters model), Castable (HList tensors) [ATenTensor]) => model -> CppOptimizerState option (Parameters model) -> Tensor dev dtype lossShape -> IO (model, CppOptimizerState option (Parameters model))

+ Torch.Typed.Parameter: class Parameterized f where {

+ Torch.Typed.Parameter: flattenParameters :: Parameterized f => f -> HList (Parameters f)

+ Torch.Typed.Parameter: gFlattenParameters :: GParameterized f => f a -> HList (GParameters f)

+ Torch.Typed.Parameter: gReplaceParameters :: GParameterized f => f a -> HList (GParameters f) -> f a

+ Torch.Typed.Parameter: makeIndependent :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Tensor device dtype shape -> IO (Parameter device dtype shape)

+ Torch.Typed.Parameter: parameterToDType :: forall (dtype' :: DType) (dtype :: DType) (device :: (DeviceType, Nat)) (shape :: [Nat]). KnownDType dtype' => Parameter device dtype shape -> Parameter device dtype' shape

+ Torch.Typed.Parameter: parameterToDevice :: forall (device' :: (DeviceType, Nat)) (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). KnownDevice device' => Parameter device dtype shape -> Parameter device' dtype shape

+ Torch.Typed.Parameter: replaceParameters :: Parameterized f => f -> HList (Parameters f) -> f

+ Torch.Typed.Parameter: toDependent :: forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). Parameter device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Parameter: type GParameters (f :: Type -> Type) :: [Type];

+ Torch.Typed.Parameter: type Parameters f = GParameters Rep f;

+ Torch.Typed.Parameter: untypeParam :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Parameter device dtype shape -> Parameter

+ Torch.Typed.Serialize: load :: forall (tensors :: [Type]). Castable (HList tensors) [ATenTensor] => FilePath -> IO (HList tensors)

+ Torch.Typed.Serialize: save :: forall (tensors :: [Type]). Castable (HList tensors) [ATenTensor] => HList tensors -> FilePath -> IO ()

+ Torch.Typed.Tensor: (/=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: (<.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: (<=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: (==.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: (>.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: (>=.) :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: UnknownShapeTensor :: Tensor device dtype shape -> UnknownShapeTensor (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Tensor: [FromTensor] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: Shape) (shape1 :: [Nat]). shape1 ~ ToNats shape => Tensor device dtype shape1 -> NamedTensor device dtype shape

+ Torch.Typed.Tensor: [UnsafeMkTensor] :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor -> Tensor device dtype shape

+ Torch.Typed.Tensor: add :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed.Tensor: data UnknownShapeTensor (device :: (DeviceType, Nat)) (dtype :: DType)

+ Torch.Typed.Tensor: device :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> Device

+ Torch.Typed.Tensor: dim :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> Int

+ Torch.Typed.Tensor: div :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed.Tensor: dtype :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> DType

+ Torch.Typed.Tensor: eq :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: fromUnnamed :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). (Unnamed t, IsUnnamed t device dtype shape) => Tensor device dtype shape -> t

+ Torch.Typed.Tensor: ge :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: getFiniteI :: forall (n :: Nat). Finite n -> Int

+ Torch.Typed.Tensor: gt :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: le :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: lt :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: matmul :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (shape'' ~ MatMul shape shape', MatMulDTypeIsValid device dtype) => Tensor device dtype shape -> Tensor device dtype shape' -> Tensor device dtype shape''

+ Torch.Typed.Tensor: mul :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed.Tensor: ne :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (device :: (DeviceType, Nat)). (shape'' ~ Broadcast shape shape', ComparisonDTypeIsValid device dtype, ComparisonDTypeIsValid device dtype') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device 'Bool shape''

+ Torch.Typed.Tensor: reshape :: forall (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownShape shape', Numel shape ~ Numel shape') => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Tensor: select :: forall (dim :: Nat) (idx :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, KnownNat idx, InRange shape dim idx, shape' ~ Remove shape dim) => Tensor device dtype shape -> Tensor device dtype shape'

+ Torch.Typed.Tensor: selectIdx :: forall (dim :: Nat) (n :: Nat) (shape' :: [Nat]) (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownNat dim, n ~ Index shape dim, shape' ~ Remove shape dim) => Tensor device dtype shape -> Finite n -> Tensor device dtype shape'

+ Torch.Typed.Tensor: shape :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t. (TensorOptions shape dtype device, IsUnnamed t device dtype shape) => t -> [Int]

+ Torch.Typed.Tensor: sub :: forall (shape'' :: [Nat]) (shape :: [Nat]) (shape' :: [Nat]) (dtype :: DType) (dtype' :: DType) (dtype'' :: DType) (device :: (DeviceType, Nat)). (dtype'' ~ DTypePromotion dtype dtype', shape'' ~ Broadcast shape shape', BasicArithmeticDTypeIsValid device dtype, BasicArithmeticDTypeIsValid device dtype', BasicArithmeticDTypeIsValid device dtype'') => Tensor device dtype shape -> Tensor device dtype' shape' -> Tensor device dtype'' shape''

+ Torch.Typed.Tensor: toBool :: forall (device :: (DeviceType, Nat)). Tensor device 'Bool ('[] :: [Nat]) -> Bool

+ Torch.Typed.Tensor: toCPU :: forall (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> CPUTensor dtype shape

+ Torch.Typed.Tensor: toCUDA :: forall {k} (device' :: k) (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> CUDATensor 0 dtype shape

+ Torch.Typed.Tensor: toDType :: forall (dtype' :: DType) (dtype :: DType) (device :: (DeviceType, Nat)) (shape :: [Nat]) t t'. (KnownDType dtype', IsUnnamed t device dtype shape, Unnamed t', t' ~ ReplaceDType'' t dtype') => t -> t'

+ Torch.Typed.Tensor: toDense :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Tensor: toDevice :: forall (device' :: (DeviceType, Nat)) (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]) t t'. (KnownDevice device', IsUnnamed t device dtype shape, Unnamed t', t' ~ ReplaceDevice'' t device') => t -> t'

+ Torch.Typed.Tensor: toDouble :: forall (device :: (DeviceType, Nat)). Tensor device 'Double ('[] :: [Nat]) -> Double

+ Torch.Typed.Tensor: toFloat :: forall (device :: (DeviceType, Nat)). Tensor device 'Float ('[] :: [Nat]) -> Float

+ Torch.Typed.Tensor: toInt :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Int

+ Torch.Typed.Tensor: toMPS :: forall {k} (device' :: k) (device :: (DeviceType, Nat)) (shape :: [Nat]) (dtype :: DType). Tensor device dtype shape -> MPSTensor 0 dtype shape

+ Torch.Typed.Tensor: toSparse :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype shape -> Tensor device dtype shape

+ Torch.Typed.Tensor: toUnnamed :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). (Unnamed t, IsUnnamed t device dtype shape) => t -> Tensor device dtype shape

+ Torch.Typed.Tensor: type Broadcast (shape :: [Nat]) (shape' :: [Nat]) = CheckBroadcast shape shape' ComputeBroadcast Reverse shape Reverse shape'

+ Torch.Typed.Tensor: type CUDATensor (deviceIndex :: Nat) = Tensor '( 'CUDA, deviceIndex)

+ Torch.Typed.Tensor: type MPSTensor (deviceIndex :: k) = Tensor '( 'MPS, 0)

+ Torch.Typed.Tensor: type MatMul (shape :: [Nat]) (shape' :: [Nat]) = CheckMatMul shape shape' ComputeMatMul Reverse shape Reverse shape'

+ Torch.Typed.Tensor: withTensor :: Tensor -> (forall (shape :: [Nat]) (dtype :: DType) (device :: (DeviceType, Nat)). (KnownDevice device, KnownDType dtype, KnownShape shape) => Tensor device dtype shape -> r) -> r

+ Torch.Typed.Tensor: withTensorShape :: forall (device :: (DeviceType, Nat)) (dtype :: DType) r. (KnownDevice device, KnownDType dtype) => Tensor -> (forall (shape :: [Nat]). KnownShape shape => Tensor device dtype shape -> r) -> r

+ Torch.Typed.VLTensor: VLTensor :: Tensor device dtype (n ': shape) -> VLTensor (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat])

+ Torch.Typed.VLTensor: fromVLTensor :: forall (n :: Nat) (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). (KnownNat n, TensorOptions shape dtype device, KnownShape shape) => VLTensor device dtype shape -> Maybe (Tensor device dtype (n ': shape))

+ Torch.Typed.VLTensor: pack :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). [Tensor device dtype shape] -> VLTensor device dtype shape

+ Torch.Typed.VLTensor: selectIndexes :: forall (n :: Nat) (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). Tensor device dtype (n ': shape) -> Tensor device 'Bool '[n] -> VLTensor device dtype shape

+ Torch.Typed.VLTensor: unpack :: forall (device :: (DeviceType, Nat)) (dtype :: DType) (shape :: [Nat]). VLTensor device dtype shape -> [Tensor device dtype shape]

+ Torch.Typed.Vision: getImages :: forall (n :: Nat). KnownNat n => MnistData -> [Int] -> CPUTensor 'Float '[n, DataDim]

+ Torch.Typed.Vision: getImages' :: forall (n :: Nat). KnownNat n => MnistData -> [Int] -> CPUTensor 'Float '[n, DataDim]

+ Torch.Typed.Vision: getLabels :: forall (n :: Nat). KnownNat n => MnistData -> [Int] -> CPUTensor 'Int64 '[n]

+ Torch.Vision: writeImage :: Pixel p => Int -> Int -> Int -> p -> Tensor -> IO (Image p)