Safe Haskell	None
Language	Haskell2010

Torch.Models.Vision.LeNet

Synopsis

type Flattened ker = (16 * ker) * ker
data LeNet ch ker = LeNet {
- _conv1 :: !(Conv2d ch 6 '(ker, ker))
- _conv2 :: !(Conv2d 6 16 '(ker, ker))
- _fc1 :: !(Linear (Flattened ker) 120)
- _fc2 :: !(Linear 120 84)
- _fc3 :: !(Linear 84 10)
}
conv1 :: Lens' (LeNet ch ker) (Conv2d ch 6 '(ker, ker))
conv2 :: Lens' (LeNet ch ker) (Conv2d 6 16 '(ker, ker))
fc1 :: forall ch ker. Lens' (LeNet ch ker) (Linear (Flattened ker) 120)
fc2 :: Lens' (LeNet ch ker) (Linear 120 84)
fc3 :: Lens' (LeNet ch ker) (Linear 84 10)
newLeNet :: All KnownDim '[ch, ker, Flattened ker, ker * ker] => Generator -> IO (LeNet ch ker)
update :: (KnownDim ch, KnownDim kW, KnownDim ((16 * kW) * kW)) => LeNet ch kW -> HsReal -> LeNet ch kW -> LeNet ch kW
update_ :: (KnownDim i, KnownDim kW, KnownDim ((16 * kW) * kW)) => LeNet i kW -> HsReal -> LeNet i kW -> IO ()
lenet :: (If (Case_6989586621679794375 (Mod (((h1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h1 - ker) + 1) - 2) 2) ~ h2) ((1 + Div (((h1 - ker) + 1) - 2) 2) ~ h2), If (Case_6989586621679794375 (Mod (((w1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w1 - ker) + 1) - 2) 2) ~ w2) ((1 + Div (((w1 - ker) + 1) - 2) 2) ~ w2), If (Case_6989586621679794375 (Mod (((h2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h2 - ker) + 1) - 2) 2) ~ moh) ((1 + Div (((h2 - ker) + 1) - 2) 2) ~ moh), If (Case_6989586621679794375 (Mod (((w2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w2 - ker) + 1) - 2) 2) ~ mow) ((1 + Div (((w2 - ker) + 1) - 2) 2) ~ mow), Reifies s W, KnownDim ((16 * ker) * ker), KnownDim ch, KnownDim ker, KnownDim ((h2 - ker) + 1), KnownDim (((h2 - ker) + 1) * ((w2 - ker) + 1)), KnownDim ((6 * ker) * ker), KnownDim ((ker * ker) * 6), KnownDim w2, KnownDim h2, KnownDim ((w1 - ker) + 1), KnownDim w1, KnownDim ((ker * ker) * ch), KnownDim ((ch * ker) * ker), KnownDim (((h1 - ker) + 1) * ((w1 - ker) + 1)), KnownDim h1, KnownDim ((h1 - ker) + 1), KnownDim ((w2 - ker) + 1), KnownDim moh, KnownDim mow, KnownDim ((16 * moh) * mow), Case_6989586621679794339 h1 ker (CmpNat h1 ker) ~# False, Case_6989586621679794339 h2 ker (CmpNat h2 ker) ~# False, Case_6989586621679794339 w1 ker (CmpNat w1 ker) ~# False, Case_6989586621679794375 ((w1 - ker) + 1) 0 (CmpNat ((w1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h2 - ker) + 1) 0 (CmpNat ((h2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ker 0 (CmpNat ker 0) ~# True, Case_6989586621679794375 ((w2 - ker) + 1) 0 (CmpNat ((w2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h1 - ker) + 1) 0 (CmpNat ((h1 - ker) + 1) 0) ~# True, Case_6989586621679794339 w2 ker (CmpNat w2 ker) ~# False, ((16 * moh) * mow) ~# ((16 * ker) * ker)) => Double -> BVar s (LeNet ch ker) -> BVar s (Tensor (ch ': (h1 ': (w1 ': ([] :: [Nat]))))) -> BVar s (Tensor (10 ': ([] :: [Nat])))
lenetLayer :: forall inp h w ker ow oh s out mow moh step pad. Reifies s W => All KnownDim '[inp, out, ker, (ker * ker) * inp] => pad ~ 0 => step ~ 1 => SpatialConvolutionC inp h w ker ker step step pad pad oh ow => SpatialDilationC oh ow 2 2 2 2 pad pad mow moh 1 1 True => Double -> BVar s (Conv2d inp out '(ker, ker)) -> BVar s (Tensor '[inp, h, w]) -> BVar s (Tensor '[out, moh, mow])
lenetBatch :: (If (Case_6989586621679794375 (Mod (((h1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h1 - ker) + 1) - 2) 2) ~ h2) ((1 + Div (((h1 - ker) + 1) - 2) 2) ~ h2), If (Case_6989586621679794375 (Mod (((w1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w1 - ker) + 1) - 2) 2) ~ w2) ((1 + Div (((w1 - ker) + 1) - 2) 2) ~ w2), If (Case_6989586621679794375 (Mod (((h2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h2 - ker) + 1) - 2) 2) ~ moh) ((1 + Div (((h2 - ker) + 1) - 2) 2) ~ moh), If (Case_6989586621679794375 (Mod (((w2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w2 - ker) + 1) - 2) 2) ~ mow) ((1 + Div (((w2 - ker) + 1) - 2) 2) ~ mow), Reifies s W, KnownDim ((16 * ker) * ker), KnownDim ch, KnownDim ker, KnownDim ((h2 - ker) + 1), KnownDim (((h2 - ker) + 1) * ((w2 - ker) + 1)), KnownDim ((6 * ker) * ker), KnownDim ((ker * ker) * 6), KnownDim w2, KnownDim h2, KnownDim ((w1 - ker) + 1), KnownDim w1, KnownDim b, KnownDim ((ker * ker) * ch), KnownDim ((ch * ker) * ker), KnownDim (((h1 - ker) + 1) * ((w1 - ker) + 1)), KnownDim h1, KnownDim ((h1 - ker) + 1), KnownDim ((w2 - ker) + 1), KnownDim moh, KnownDim mow, KnownDim ((16 * moh) * mow), Case_6989586621679794339 h1 ker (CmpNat h1 ker) ~# False, Case_6989586621679794339 w1 ker (CmpNat w1 ker) ~# False, Case_6989586621679794339 h2 ker (CmpNat h2 ker) ~# False, (((b * 16) * moh) * mow) ~# (b * ((16 * moh) * mow)), Case_6989586621679794375 ((h2 - ker) + 1) 0 (CmpNat ((h2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((w1 - ker) + 1) 0 (CmpNat ((w1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h1 - ker) + 1) 0 (CmpNat ((h1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((w2 - ker) + 1) 0 (CmpNat ((w2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ker 0 (CmpNat ker 0) ~# True, Case_6989586621679794339 w2 ker (CmpNat w2 ker) ~# False, ((16 * moh) * mow) ~# ((16 * ker) * ker)) => Double -> BVar s (LeNet ch ker) -> BVar s (Tensor (b ': (ch ': (h1 ': (w1 ': ([] :: [Nat])))))) -> BVar s (Tensor (b ': (10 ': ([] :: [Nat]))))
lenetLayerBatch :: forall inp h w ker ow oh s out mow moh step pad batch. Reifies s W => All KnownDim '[batch, inp, out, ker, (ker * ker) * inp] => pad ~ 0 => step ~ 1 => SpatialConvolutionC inp h w ker ker step step pad pad oh ow => SpatialDilationC oh ow 2 2 2 2 pad pad mow moh 1 1 True => Double -> BVar s (Conv2d inp out '(ker, ker)) -> BVar s (Tensor '[batch, inp, h, w]) -> BVar s (Tensor '[batch, out, moh, mow])

Documentation

type Flattened ker = (16 * ker) * ker Source #

data LeNet ch ker Source #

Constructors

LeNet
Fields _conv1 :: !(Conv2d ch 6 '(ker, ker)) _conv2 :: !(Conv2d 6 16 '(ker, ker)) _fc1 :: !(Linear (Flattened ker) 120) _fc2 :: !(Linear 120 84) _fc3 :: !(Linear 84 10)

Instances

(KnownDim (Flattened ker), KnownDim ch, KnownDim ker) => Show (LeNet ch ker) Source #
Instance details Defined in Torch.Models.Vision.LeNet Methods showsPrec :: Int -> LeNet ch ker -> ShowS # show :: LeNet ch ker -> String # showList :: [LeNet ch ker] -> ShowS #
Generic (LeNet ch ker) Source #
Instance details Defined in Torch.Models.Vision.LeNet Associated Types type Rep (LeNet ch ker) :: Type -> Type # Methods from :: LeNet ch ker -> Rep (LeNet ch ker) x # to :: Rep (LeNet ch ker) x -> LeNet ch ker #
(KnownDim (Flattened ker), KnownDim ch, KnownDim ker) => Backprop (LeNet ch ker) Source #
Instance details Defined in Torch.Models.Vision.LeNet Methods zero :: LeNet ch ker -> LeNet ch ker add :: LeNet ch ker -> LeNet ch ker -> LeNet ch ker one :: LeNet ch ker -> LeNet ch ker
type Rep (LeNet ch ker) Source #
Instance details Defined in Torch.Models.Vision.LeNet type Rep (LeNet ch ker) = D1 (MetaData "LeNet" "Torch.Models.Vision.LeNet" "hasktorch-zoo-0.0.1.0-inplace" False) (C1 (MetaCons "LeNet" PrefixI True) ((S1 (MetaSel (Just "_conv1") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Conv2d ch 6 ((,) ker ker))) :: S1 (MetaSel (Just "_conv2") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Conv2d 6 16 ((,) ker ker)))) :: (S1 (MetaSel (Just "_fc1") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Linear (Flattened ker) 120)) :: (S1 (MetaSel (Just "_fc2") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Linear 120 84)) :: S1 (MetaSel (Just "_fc3") NoSourceUnpackedness SourceStrict DecidedStrict) (Rec0 (Linear 84 10))))))

conv1 :: Lens' (LeNet ch ker) (Conv2d ch 6 '(ker, ker)) Source #

conv2 :: Lens' (LeNet ch ker) (Conv2d 6 16 '(ker, ker)) Source #

fc1 :: forall ch ker. Lens' (LeNet ch ker) (Linear (Flattened ker) 120) Source #

fc2 :: Lens' (LeNet ch ker) (Linear 120 84) Source #

fc3 :: Lens' (LeNet ch ker) (Linear 84 10) Source #

newLeNet :: All KnownDim '[ch, ker, Flattened ker, ker * ker] => Generator -> IO (LeNet ch ker) Source #

update :: (KnownDim ch, KnownDim kW, KnownDim ((16 * kW) * kW)) => LeNet ch kW -> HsReal -> LeNet ch kW -> LeNet ch kW Source #

update a LeNet network

update_ :: (KnownDim i, KnownDim kW, KnownDim ((16 * kW) * kW)) => LeNet i kW -> HsReal -> LeNet i kW -> IO () Source #

update a LeNet network inplace

lenet :: (If (Case_6989586621679794375 (Mod (((h1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h1 - ker) + 1) - 2) 2) ~ h2) ((1 + Div (((h1 - ker) + 1) - 2) 2) ~ h2), If (Case_6989586621679794375 (Mod (((w1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w1 - ker) + 1) - 2) 2) ~ w2) ((1 + Div (((w1 - ker) + 1) - 2) 2) ~ w2), If (Case_6989586621679794375 (Mod (((h2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h2 - ker) + 1) - 2) 2) ~ moh) ((1 + Div (((h2 - ker) + 1) - 2) 2) ~ moh), If (Case_6989586621679794375 (Mod (((w2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w2 - ker) + 1) - 2) 2) ~ mow) ((1 + Div (((w2 - ker) + 1) - 2) 2) ~ mow), Reifies s W, KnownDim ((16 * ker) * ker), KnownDim ch, KnownDim ker, KnownDim ((h2 - ker) + 1), KnownDim (((h2 - ker) + 1) * ((w2 - ker) + 1)), KnownDim ((6 * ker) * ker), KnownDim ((ker * ker) * 6), KnownDim w2, KnownDim h2, KnownDim ((w1 - ker) + 1), KnownDim w1, KnownDim ((ker * ker) * ch), KnownDim ((ch * ker) * ker), KnownDim (((h1 - ker) + 1) * ((w1 - ker) + 1)), KnownDim h1, KnownDim ((h1 - ker) + 1), KnownDim ((w2 - ker) + 1), KnownDim moh, KnownDim mow, KnownDim ((16 * moh) * mow), Case_6989586621679794339 h1 ker (CmpNat h1 ker) ~# False, Case_6989586621679794339 h2 ker (CmpNat h2 ker) ~# False, Case_6989586621679794339 w1 ker (CmpNat w1 ker) ~# False, Case_6989586621679794375 ((w1 - ker) + 1) 0 (CmpNat ((w1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h2 - ker) + 1) 0 (CmpNat ((h2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ker 0 (CmpNat ker 0) ~# True, Case_6989586621679794375 ((w2 - ker) + 1) 0 (CmpNat ((w2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h1 - ker) + 1) 0 (CmpNat ((h1 - ker) + 1) 0) ~# True, Case_6989586621679794339 w2 ker (CmpNat w2 ker) ~# False, ((16 * moh) * mow) ~# ((16 * ker) * ker)) => Double -> BVar s (LeNet ch ker) -> BVar s (Tensor (ch ': (h1 ': (w1 ': ([] :: [Nat]))))) -> BVar s (Tensor (10 ': ([] :: [Nat]))) Source #

lenetLayer Source #

Arguments

:: Reifies s W
=> All KnownDim '[inp, out, ker, (ker * ker) * inp]
=> pad ~ 0
=> step ~ 1
=> SpatialConvolutionC inp h w ker ker step step pad pad oh ow
=> SpatialDilationC oh ow 2 2 2 2 pad pad mow moh 1 1 True
=> Double	learning rate for convolution layer
-> BVar s (Conv2d inp out '(ker, ker))	convolutional layer
-> BVar s (Tensor '[inp, h, w])	input
-> BVar s (Tensor '[out, moh, mow])	output

lenetBatch :: (If (Case_6989586621679794375 (Mod (((h1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h1 - ker) + 1) - 2) 2) ~ h2) ((1 + Div (((h1 - ker) + 1) - 2) 2) ~ h2), If (Case_6989586621679794375 (Mod (((w1 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w1 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w1 - ker) + 1) - 2) 2) ~ w2) ((1 + Div (((w1 - ker) + 1) - 2) 2) ~ w2), If (Case_6989586621679794375 (Mod (((h2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((h2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((h2 - ker) + 1) - 2) 2) ~ moh) ((1 + Div (((h2 - ker) + 1) - 2) 2) ~ moh), If (Case_6989586621679794375 (Mod (((w2 - ker) + 1) - 2) 2) 0 (CmpNat (Mod (((w2 - ker) + 1) - 2) 2) 0)) ((2 + Div (((w2 - ker) + 1) - 2) 2) ~ mow) ((1 + Div (((w2 - ker) + 1) - 2) 2) ~ mow), Reifies s W, KnownDim ((16 * ker) * ker), KnownDim ch, KnownDim ker, KnownDim ((h2 - ker) + 1), KnownDim (((h2 - ker) + 1) * ((w2 - ker) + 1)), KnownDim ((6 * ker) * ker), KnownDim ((ker * ker) * 6), KnownDim w2, KnownDim h2, KnownDim ((w1 - ker) + 1), KnownDim w1, KnownDim b, KnownDim ((ker * ker) * ch), KnownDim ((ch * ker) * ker), KnownDim (((h1 - ker) + 1) * ((w1 - ker) + 1)), KnownDim h1, KnownDim ((h1 - ker) + 1), KnownDim ((w2 - ker) + 1), KnownDim moh, KnownDim mow, KnownDim ((16 * moh) * mow), Case_6989586621679794339 h1 ker (CmpNat h1 ker) ~# False, Case_6989586621679794339 w1 ker (CmpNat w1 ker) ~# False, Case_6989586621679794339 h2 ker (CmpNat h2 ker) ~# False, (((b * 16) * moh) * mow) ~# (b * ((16 * moh) * mow)), Case_6989586621679794375 ((h2 - ker) + 1) 0 (CmpNat ((h2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((w1 - ker) + 1) 0 (CmpNat ((w1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((h1 - ker) + 1) 0 (CmpNat ((h1 - ker) + 1) 0) ~# True, Case_6989586621679794375 ((w2 - ker) + 1) 0 (CmpNat ((w2 - ker) + 1) 0) ~# True, Case_6989586621679794375 ker 0 (CmpNat ker 0) ~# True, Case_6989586621679794339 w2 ker (CmpNat w2 ker) ~# False, ((16 * moh) * mow) ~# ((16 * ker) * ker)) => Double -> BVar s (LeNet ch ker) -> BVar s (Tensor (b ': (ch ': (h1 ': (w1 ': ([] :: [Nat])))))) -> BVar s (Tensor (b ': (10 ': ([] :: [Nat])))) Source #

lenetLayerBatch Source #

Arguments

:: Reifies s W
=> All KnownDim '[batch, inp, out, ker, (ker * ker) * inp]
=> pad ~ 0
=> step ~ 1
=> SpatialConvolutionC inp h w ker ker step step pad pad oh ow
=> SpatialDilationC oh ow 2 2 2 2 pad pad mow moh 1 1 True
=> Double	learning rate for convolution layer
-> BVar s (Conv2d inp out '(ker, ker))	convolutional layer
-> BVar s (Tensor '[batch, inp, h, w])	input
-> BVar s (Tensor '[batch, out, moh, mow])	output