d82a121 · grenade · git.iko.soy

git.iko.soy/grenade

Remove Show constraint on UpdateLayer

commitd82a121797238c93220c27615cc318e89f7d41eb authorHuw Campbell <huw.campbell@ambiata.com> dateTue 24 Jan 2017, 13:47 (10 years ago) parent148c777

8 files changed+25−16

compare with master

unifiedsplit

mafia+1−1 main/mnist.hs+2−2 src/Grenade.hs+4−3 src/Grenade/Core/Network.hs+5−3 src/Grenade/Core/Runner.hs+3−1 src/Grenade/Layers/Flatten.hs+1−1 src/Grenade/Recurrent/Core/Network.hs+6−5 src/Grenade/Recurrent/Core/Runner.hs+3

mafia+1−1

@@ -120,4 +120,4 @@ case "$MODE" in

120120upgrade) shift; run_upgrade "$@" ;;

121121*) exec_mafia "$@"

122122esac

123−# Version: 3044e63eb472fb9e16926d4ab2ca9dd9e255829c

123+# Version: 360716306a06db842ec022a7b9f161d2208483f0

main/mnist.hs+2−2

@@ -33,8 +33,8 @@ import Grenade.Utils.OneHot

3333

3434-- With the mnist data from Kaggle normalised to doubles between 0 and 1, learning rate of 0.01 and 15 iterations,

3535-- this network should get down to about a 1.3% error rate.

36−type MNIST = Network '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, FlattenLayer, Relu, FullyConnected 256 80, Logit, FullyConnected 80 10, Logit]

37− '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D1 256, 'D1 256, 'D1 80, 'D1 80, 'D1 10, 'D1 10]

36+type MNIST = Network '[ Convolution 1 10 5 5 1 1, Pooling 2 2 2 2, Relu, Convolution 10 16 5 5 1 1, Pooling 2 2 2 2, Relu, FlattenLayer, FullyConnected 256 80, Logit, FullyConnected 80 10, Logit]

37+ '[ 'D2 28 28, 'D3 24 24 10, 'D3 12 12 10, 'D3 12 12 10, 'D3 8 8 16, 'D3 4 4 16, 'D3 4 4 16, 'D1 256, 'D1 80, 'D1 80, 'D1 10, 'D1 10]

3838

3939randomMnist :: MonadRandom m => m MNIST

4040randomMnist = randomNetwork

src/Grenade.hs+4−3

@@ -13,6 +13,7 @@ import Grenade.Layers.Flatten as X

1313import Grenade.Layers.Fuse as X

1414import Grenade.Layers.FullyConnected as X

1515import Grenade.Layers.Logit as X

16−import Grenade.Layers.Convolution as X

17−import Grenade.Layers.Relu as X

18−import Grenade.Layers.Tanh as X

16+import Grenade.Layers.Convolution as X

17+import Grenade.Layers.Relu as X

18+import Grenade.Layers.Tanh as X

19+import Grenade.Layers.Softmax as X

src/Grenade/Core/Network.hs+5−3

@@ -42,7 +42,7 @@ data LearningParameters = LearningParameters {

4242

4343-- | Class for updating a layer. All layers implement this, and it is

4444-- shape independent.

45−class Show x => UpdateLayer x where

45+class UpdateLayer x where

4646 {-# MINIMAL runUpdate, createRandom #-}

4747 -- | The type for the gradient for this layer.

4848 -- Unit if there isn't a gradient to pass back.

@@ -86,9 +86,11 @@ data Network :: [*] -> [Shape] -> * where

8686 (:~>) :: (SingI i, SingI h, Layer x i h) => !x -> !(Network xs (h ': hs)) -> Network (x ': xs) (i ': h ': hs)

8787infixr 5 :~>

8888

89−instance Show (Network l h) where

89+instance Show (Network '[] '[i]) where

9090 show NNil = "NNil"

91− show (i :~> o) = show i ++ "\n:~>\n" ++ show o

91+instance (Show x, Show (Network xs rs)) => Show (Network (x ': xs) (i ': rs)) where

92+ show (x :~> xs) = show x ++ "\n~>\n" ++ show xs

93+

9294

9395-- | Gradients of a network.

9496-- Parameterised on the layers of a Network.

src/Grenade/Core/Runner.hs+3−1

@@ -14,6 +14,9 @@ Stability : experimental

1414This module defines simple back propagation and training functions

1515for a network.

1616-}

17+

18+-- GHC 7.10 doesn't think that go is complete

19+{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}

1720module Grenade.Core.Runner (

1821 train

1922 , backPropagate

@@ -48,7 +51,6 @@ backPropagate network input target =

4851 (n', dWs') = go y n

4952 -- calculate the gradient for this layer to pass down,

5053 (layer', dWs) = runBackwards layer tape dWs'

51−

5254 in (layer' :/> n', dWs)

5355

5456 -- Bouncing the derivatives back down.

src/Grenade/Layers/Flatten.hs+1−1

@@ -31,7 +31,7 @@ instance UpdateLayer FlattenLayer where

3131 runUpdate _ _ _ = FlattenLayer

3232 createRandom = return FlattenLayer

3333

34−instance (KnownNat a, KnownNat x, KnownNat y, a ~ (x * z)) => Layer FlattenLayer ('D2 x y) ('D1 a) where

34+instance (KnownNat a, KnownNat x, KnownNat y, a ~ (x * y)) => Layer FlattenLayer ('D2 x y) ('D1 a) where

3535 type Tape FlattenLayer ('D2 x y) ('D1 a) = ()

3636 runForwards _ (S2D y) = ((), fromJust' . fromStorable . flatten . extract $ y)

3737 runBackwards _ _ (S1D y) = ((), fromJust' . fromStorable . extract $ y)

src/Grenade/Recurrent/Core/Network.hs+6−5

@@ -59,11 +59,12 @@ data RecurrentNetwork :: [*] -> [Shape] -> * where

5959infixr 5 :~~>

6060infixr 5 :~@>

6161

62−instance Show (RecurrentNetwork l h) where

63− show RNil = "RNil"

64− show (i :~~> o) = show i ++ "\n:~~>\n" ++ show o

65− show (i :~@> o) = show i ++ "\n:~@>\n" ++ show o

66−

62+instance Show (RecurrentNetwork '[] '[i]) where

63+ show RNil = "NNil"

64+instance (Show x, Show (RecurrentNetwork xs rs)) => Show (RecurrentNetwork (FeedForward x ': xs) (i ': rs)) where

65+ show (x :~~> xs) = show x ++ "\n~~>\n" ++ show xs

66+instance (Show x, Show (RecurrentNetwork xs rs)) => Show (RecurrentNetwork (Recurrent x ': xs) (i ': rs)) where

67+ show (x :~@> xs) = show x ++ "\n~~>\n" ++ show xs

6768

6869-- | Recurrent inputs (sideways shapes on an imaginary unrolled graph)

6970-- Parameterised on the layers of a Network.

src/Grenade/Recurrent/Core/Runner.hs+3

@@ -7,6 +7,9 @@

77{-# LANGUAGE FlexibleContexts #-}

88{-# LANGUAGE RankNTypes #-}

99{-# LANGUAGE RecordWildCards #-}

10+

11+-- GHC 7.10 doesn't think that go is complete

12+{-# OPTIONS_GHC -fno-warn-incomplete-patterns #-}

1013module Grenade.Recurrent.Core.Runner (

1114 trainRecurrent

1215 , runRecurrent