49a4280 · grenade · git.iko.soy

git.iko.soy/grenade

GHC 8.4 compatibility

- `-XNoStarIsType` is new in GHC 8.6 - can't use `-XCPP` to conditionally enable `LANGUAGE` pragmas (implicit module declaration) - use a conditional in the .cabal file, but this is active for all modules - need to replace all `*` with `Type` and `import Data.Kind (Type)` (works in 8.4)

commit49a4280a91640ebf698e2c3dfd8768a63fd4f5b4 authorClaude Heiland-Allen <claude@mathr.co.uk> dateFri 14 Dec 2018, 18:00 (8 years ago) parent0bc6bd5

17 files changed+40−30

compare with master

unifiedsplit

grenade.cabal+2

@@ -58,6 +58,8 @@ library

5858 if impl(ghc < 8.0)

5959 ghc-options: -fno-warn-incomplete-patterns

6060

61+ if impl(ghc >= 8.6)

62+ default-extensions: NoStarIsType

6163

6264 exposed-modules:

6365 Grenade

src/Grenade/Core/Layer.hs+4−2

@@ -41,6 +41,8 @@ import Control.Monad.Random ( MonadRandom )

4141

4242import Data.List ( foldl' )

4343

44+import Data.Kind (Type)

45+

4446import Grenade.Core.Shape

4547import Grenade.Core.LearningParameters

4648

@@ -50,7 +52,7 @@ import Grenade.Core.LearningParameters

5052class UpdateLayer x where

5153 -- | The type for the gradient for this layer.

5254 -- Unit if there isn't a gradient to pass back.

53− type Gradient x :: *

55+ type Gradient x :: Type

5456

5557 -- | Update a layer with its gradient and learning parameters

5658 runUpdate :: LearningParameters -> x -> Gradient x -> x

@@ -72,7 +74,7 @@ class UpdateLayer x => Layer x (i :: Shape) (o :: Shape) where

7274 -- | The Wengert tape for this layer. Includes all that is required

7375 -- to generate the back propagated gradients efficiently. As a

7476 -- default, `S i` is fine.

75− type Tape x i o :: *

77+ type Tape x i o :: Type

7678

7779 -- | Used in training and scoring. Take the input from the previous

7880 -- layer, and give the output from this layer.

src/Grenade/Core/Network.hs+6−4

@@ -36,6 +36,8 @@ import Data.Singletons

3636import Data.Singletons.Prelude

3737import Data.Serialize

3838

39+import Data.Kind (Type)

40+

3941import Grenade.Core.Layer

4042import Grenade.Core.LearningParameters

4143import Grenade.Core.Shape

@@ -48,7 +50,7 @@ import Grenade.Core.Shape

4850--

4951-- Can be considered to be a heterogeneous list of layers which are able to

5052-- transform the data shapes of the network.

51−data Network :: [*] -> [Shape] -> * where

53+data Network :: [Type] -> [Shape] -> Type where

5254 NNil :: SingI i

5355 => Network '[] '[i]

5456

@@ -66,7 +68,7 @@ instance (Show x, Show (Network xs rs)) => Show (Network (x ': xs) (i ': rs)) wh

6668-- | Gradient of a network.

6769--

6870-- Parameterised on the layers of the network.

69−data Gradients :: [*] -> * where

71+data Gradients :: [Type] -> Type where

7072 GNil :: Gradients '[]

7173

7274 (:/>) :: UpdateLayer x

@@ -77,7 +79,7 @@ data Gradients :: [*] -> * where

7779-- | Wegnert Tape of a network.

7880--

7981-- Parameterised on the layers and shapes of the network.

80−data Tapes :: [*] -> [Shape] -> * where

82+data Tapes :: [Type] -> [Shape] -> Type where

8183 TNil :: SingI i

8284 => Tapes '[] '[i]

8385

@@ -152,7 +154,7 @@ applyUpdate _ NNil GNil

152154

153155-- | A network can easily be created by hand with (:~>), but an easy way to

154156-- initialise a random network is with the randomNetwork.

155−class CreatableNetwork (xs :: [*]) (ss :: [Shape]) where

157+class CreatableNetwork (xs :: [Type]) (ss :: [Shape]) where

156158 -- | Create a network with randomly initialised weights.

157159 --

158160 -- Calls to this function will not compile if the type of the neural

src/Grenade/Core/Shape.hs−1

@@ -8,7 +8,6 @@

88{-# LANGUAGE FlexibleContexts #-}

99{-# LANGUAGE ScopedTypeVariables #-}

1010{-# LANGUAGE RankNTypes #-}

11−{-# LANGUAGE NoStarIsType #-}

1211{-# LANGUAGE UndecidableInstances #-}

1312{-|

1413Module : Grenade.Core.Shape

src/Grenade/Layers/Concat.hs−1

@@ -8,7 +8,6 @@

88{-# LANGUAGE FlexibleInstances #-}

99{-# LANGUAGE ScopedTypeVariables #-}

1010{-# LANGUAGE StandaloneDeriving #-}

11−{-# LANGUAGE NoStarIsType #-}

1211{-# LANGUAGE UndecidableInstances #-}

1312{-|

1413Module : Grenade.Layers.Concat

src/Grenade/Layers/Convolution.hs−1

@@ -8,7 +8,6 @@

88{-# LANGUAGE MultiParamTypeClasses #-}

99{-# LANGUAGE FlexibleInstances #-}

1010{-# LANGUAGE FlexibleContexts #-}

11−{-# LANGUAGE NoStarIsType #-}

1211{-# LANGUAGE UndecidableInstances #-}

1312{-|

1413Module : Grenade.Layers.Convolution

src/Grenade/Layers/Crop.hs−1

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

66{-# LANGUAGE TypeFamilies #-}

77{-# LANGUAGE FlexibleContexts #-}

88{-# LANGUAGE MultiParamTypeClasses #-}

9−{-# LANGUAGE NoStarIsType #-}

109{-# LANGUAGE UndecidableInstances #-}

1110{-|

1211Module : Grenade.Layers.Crop

src/Grenade/Layers/Deconvolution.hs−1

@@ -8,7 +8,6 @@

88{-# LANGUAGE MultiParamTypeClasses #-}

99{-# LANGUAGE FlexibleInstances #-}

1010{-# LANGUAGE FlexibleContexts #-}

11−{-# LANGUAGE NoStarIsType #-}

1211{-# LANGUAGE UndecidableInstances #-}

1312{-|

1413Module : Grenade.Layers.Deconvolution

src/Grenade/Layers/Merge.hs+3−1

@@ -23,13 +23,15 @@ import Data.Serialize

2323

2424import Data.Singletons

2525

26+import Data.Kind (Type)

27+

2628import Grenade.Core

2729

2830-- | A Merging layer.

2931--

3032-- Similar to Concat layer, except sums the activations instead of creating a larger

3133-- shape.

32−data Merge :: * -> * -> * where

34+data Merge :: Type -> Type -> Type where

3335 Merge :: x -> y -> Merge x y

3436

3537instance (Show x, Show y) => Show (Merge x y) where

src/Grenade/Layers/Pad.hs−1

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

66{-# LANGUAGE TypeFamilies #-}

77{-# LANGUAGE MultiParamTypeClasses #-}

88{-# LANGUAGE FlexibleContexts #-}

9−{-# LANGUAGE NoStarIsType #-}

109{-# LANGUAGE UndecidableInstances #-}

1110{-|

1211Module : Grenade.Core.Pad

src/Grenade/Layers/Pooling.hs−1

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

77{-# LANGUAGE TypeFamilies #-}

88{-# LANGUAGE MultiParamTypeClasses #-}

99{-# LANGUAGE FlexibleContexts #-}

10−{-# LANGUAGE NoStarIsType #-}

1110{-# LANGUAGE UndecidableInstances #-}

1211{-|

1312Module : Grenade.Core.Pooling

src/Grenade/Layers/Reshape.hs−1

@@ -3,7 +3,6 @@

33{-# LANGUAGE TypeFamilies #-}

44{-# LANGUAGE MultiParamTypeClasses #-}

55{-# LANGUAGE FlexibleContexts #-}

6−{-# LANGUAGE NoStarIsType #-}

76{-# LANGUAGE UndecidableInstances #-}

87{-|

98Module : Grenade.Layers.Reshape

src/Grenade/Recurrent/Core/Layer.hs+4−2

@@ -8,6 +8,8 @@ module Grenade.Recurrent.Core.Layer (

88 , RecurrentUpdateLayer (..)

99 ) where

1010

11+import Data.Kind (Type)

12+

1113import Grenade.Core

1214

1315-- | Class for a recurrent layer.

@@ -15,11 +17,11 @@ import Grenade.Core

1517-- of an extra recurrent data shape.

1618class UpdateLayer x => RecurrentUpdateLayer x where

1719 -- | Shape of data that is passed between each subsequent run of the layer

18− type RecurrentShape x :: *

20+ type RecurrentShape x :: Type

1921

2022class (RecurrentUpdateLayer x, Num (RecurrentShape x)) => RecurrentLayer x (i :: Shape) (o :: Shape) where

2123 -- | Wengert Tape

22− type RecTape x i o :: *

24+ type RecTape x i o :: Type

2325 -- | Used in training and scoring. Take the input from the previous

2426 -- layer, and give the output from this layer.

2527 runRecurrentForwards :: x -> RecurrentShape x -> S i -> (RecTape x i o, RecurrentShape x, S o)

src/Grenade/Recurrent/Core/Network.hs+10−8

@@ -32,18 +32,20 @@ import Data.Singletons ( SingI )

3232import Data.Singletons.Prelude ( Head, Last )

3333import Data.Serialize

3434

35+import Data.Kind (Type)

36+

3537import Grenade.Core

3638import Grenade.Recurrent.Core.Layer

3739

3840-- | Witness type to say indicate we're building up with a normal feed

3941-- forward layer.

40−data FeedForward :: * -> *

42+data FeedForward :: Type -> Type

4143-- | Witness type to say indicate we're building up with a recurrent layer.

42−data Recurrent :: * -> *

44+data Recurrent :: Type -> Type

4345

4446-- | Type of a recurrent neural network.

4547--

46−-- The [*] type specifies the types of the layers.

48+-- The [Type] type specifies the types of the layers.

4749--

4850-- The [Shape] type specifies the shapes of data passed between the layers.

4951--

@@ -52,7 +54,7 @@ data Recurrent :: * -> *

5254--

5355-- Often, to make the definitions more concise, one will use a type alias

5456-- for these empty data types.

55−data RecurrentNetwork :: [*] -> [Shape] -> * where

57+data RecurrentNetwork :: [Type] -> [Shape] -> Type where

5658 RNil :: SingI i

5759 => RecurrentNetwork '[] '[i]

5860

@@ -71,7 +73,7 @@ infixr 5 :~@>

7173-- | Gradient of a network.

7274--

7375-- Parameterised on the layers of the network.

74−data RecurrentGradient :: [*] -> * where

76+data RecurrentGradient :: [Type] -> Type where

7577 RGNil :: RecurrentGradient '[]

7678

7779 (://>) :: UpdateLayer x

@@ -81,7 +83,7 @@ data RecurrentGradient :: [*] -> * where

8183

8284-- | Recurrent inputs (sideways shapes on an imaginary unrolled graph)

8385-- Parameterised on the layers of a Network.

84−data RecurrentInputs :: [*] -> * where

86+data RecurrentInputs :: [Type] -> Type where

8587 RINil :: RecurrentInputs '[]

8688

8789 (:~~+>) :: (UpdateLayer x, Fractional (RecurrentInputs xs))

@@ -95,7 +97,7 @@ data RecurrentInputs :: [*] -> * where

9597--

9698-- We index on the time step length as well, to ensure

9799-- that that all Tape lengths are the same.

98−data RecurrentTape :: [*] -> [Shape] -> * where

100+data RecurrentTape :: [Type] -> [Shape] -> Type where

99101 TRNil :: SingI i

100102 => RecurrentTape '[] '[i]

101103

@@ -204,7 +206,7 @@ instance (Show x, Show (RecurrentNetwork xs rs)) => Show (RecurrentNetwork (Recu

204206

205207-- | A network can easily be created by hand with (:~~>) and (:~@>), but an easy way to initialise a random

206208-- recurrent network and a set of random inputs for it is with the randomRecurrent.

207−class CreatableRecurrent (xs :: [*]) (ss :: [Shape]) where

209+class CreatableRecurrent (xs :: [Type]) (ss :: [Shape]) where

208210 -- | Create a network of the types requested

209211 randomRecurrent :: MonadRandom m => m (RecurrentNetwork xs ss)

210212

src/Grenade/Recurrent/Layers/BasicRecurrent.hs+4−2

@@ -18,6 +18,8 @@ import Control.Monad.Random ( MonadRandom, getRandom )

1818

1919import Data.Singletons.TypeLits

2020

21+import Data.Kind (Type)

22+

2123import Numeric.LinearAlgebra.Static

2224

2325import GHC.TypeLits

@@ -27,7 +29,7 @@ import Grenade.Recurrent.Core

2729

2830data BasicRecurrent :: Nat -- Input layer size

2931 -> Nat -- Output layer size

30− -> * where

32+ -> Type where

3133 BasicRecurrent :: ( KnownNat input

3234 , KnownNat output

3335 , KnownNat matrixCols

@@ -40,7 +42,7 @@ data BasicRecurrent :: Nat -- Input layer size

4042

4143data BasicRecurrent' :: Nat -- Input layer size

4244 -> Nat -- Output layer size

43− -> * where

45+ -> Type where

4446 BasicRecurrent' :: ( KnownNat input

4547 , KnownNat output

4648 , KnownNat matrixCols

src/Grenade/Recurrent/Layers/ConcatRecurrent.hs+3−1

@@ -27,6 +27,8 @@ import Data.Serialize

2727import Data.Singletons

2828import GHC.TypeLits

2929

30+import Data.Kind (Type)

31+

3032import Grenade.Core

3133import Grenade.Recurrent.Core

3234

@@ -45,7 +47,7 @@ import Numeric.LinearAlgebra.Static ( (#), split, R )

4547--

4648-- 3D images become 3D images with more channels. The sizes must be the same, one can use Pad

4749-- and Crop layers to ensure this is the case.

48−data ConcatRecurrent :: Shape -> * -> Shape -> * -> * where

50+data ConcatRecurrent :: Shape -> Type -> Shape -> Type -> Type where

4951 ConcatRecLeft :: x -> y -> ConcatRecurrent m (Recurrent x) n (FeedForward y)

5052 ConcatRecRight :: x -> y -> ConcatRecurrent m (FeedForward x) n (Recurrent y)

5153 ConcatRecBoth :: x -> y -> ConcatRecurrent m (Recurrent x) n (Recurrent y)

src/Grenade/Recurrent/Layers/LSTM.hs+4−2

@@ -23,6 +23,8 @@ import Data.Proxy

2323import Data.Serialize

2424import Data.Singletons.TypeLits

2525

26+import Data.Kind (Type)

27+

2628import qualified Numeric.LinearAlgebra as LA

2729import Numeric.LinearAlgebra.Static

2830

@@ -36,14 +38,14 @@ import Grenade.Layers.Internal.Update

3638-- This is a Peephole formulation, so the recurrent shape is

3739-- just the cell state, the previous output is not held or used

3840-- at all.

39−data LSTM :: Nat -> Nat -> * where

41+data LSTM :: Nat -> Nat -> Type where

4042 LSTM :: ( KnownNat input

4143 , KnownNat output

4244 ) => !(LSTMWeights input output) -- Weights

4345 -> !(LSTMWeights input output) -- Momentums

4446 -> LSTM input output

4547

46−data LSTMWeights :: Nat -> Nat -> * where

48+data LSTMWeights :: Nat -> Nat -> Type where

4749 LSTMWeights :: ( KnownNat input

4850 , KnownNat output

4951 ) => {