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Remove Typeable, fix tests

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This commit is contained in:
Huw Campbell 2016-12-02 19:14:37 +11:00
parent 114dab4103
commit cd4598bee8
3 changed files with 21 additions and 18 deletions
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5
src/Grenade/Core/Network.hs
View File

@ -16,7 +16,6 @@ module Grenade.Core.Network (
, LearningParameters (..)
) where
import Data.Typeable
import Grenade.Core.Shape
data LearningParameters = LearningParameters {
@ -51,10 +50,10 @@ class UpdateLayer m x => Layer (m :: * -> *) x (i :: Shape) (o :: Shape) where
-- Could be considered to be a heterogeneous list of layers which are able to
-- transform the data shapes of the network.
data Network :: (* -> *) -> [Shape] -> * where
O :: (Typeable x, Show x, Layer m x i o, KnownShape o, KnownShape i)
O :: (Show x, Layer m x i o, KnownShape o, KnownShape i)
=> !x
-> Network m '[i, o]
(:~>) :: (Typeable x, Show x, Layer m x i h, KnownShape h, KnownShape i)
(:~>) :: (Show x, Layer m x i h, KnownShape h, KnownShape i)
=> !x
-> !(Network m (h ': hs))
-> Network m (i ': h ': hs)

1
src/Grenade/Layers/Convolution.hs
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@ -14,6 +14,7 @@
module Grenade.Layers.Convolution (
Convolution (..)
, Convolution' (..)
, randomConvolution
, im2col
, vid2col

33
test/Test/Grenade/Layers/Convolution.hs
View File

@ -93,11 +93,12 @@ prop_simple_conv_forwards = once $
, 0.0, 0.0, 0.0, 0.0
, 0.0, 0.0, 0.0, 0.0
, 0.0, 0.0, 0.0, 0.0 ] :: HStatic.L 4 4)
--expectedKernel = (HStatic.matrix
-- [ 0.0, 0.0, 0.0, -2.0
-- ,-2.0, 1.0, 1.0, -5.0
-- ,-3.0, -1.0, 1.0, -5.0
-- ,-5.0, 0.0, 0.0, -7.0 ] :: HStatic.L 4 4)
expectedGradient = (HStatic.matrix
[ 1.0, 0.0, 0.0, 2.0
, 2.0, 0.0, 0.0, 5.0
, 3.0, 0.0, 0.0, 4.0
, 4.0, 0.0, 0.0, 6.0 ] :: HStatic.L 4 4)
convLayer = Convolution myKernel zeroKernel :: Convolution 1 4 2 2 1 1
@ -128,12 +129,13 @@ prop_simple_conv_forwards = once $
expectBack = (HStatic.matrix
[ 1.0, 0.0, 0.0
, 0.0, -2.0,-1.0] :: HStatic.L 2 3)
(nc, inX) = runIdentity $ runBackards 1 convLayer input grad :: ( Convolution 1 4 2 2 1 1 , S' ('D2 2 3))
(nc, inX) = runIdentity $ runBackards convLayer input grad
in case (out, inX, nc) of
(S3D' out' , S2D' inX', Convolution _ _)
(S3D' out' , S2D' inX', Convolution' backGrad)
-> ((HStatic.extract <$> expect) === (HStatic.extract <$> vecToList out'))
.&&. ((HStatic.extract expectBack) === (HStatic.extract inX'))
.&&. ((HStatic.extract expectedGradient) === (HStatic.extract backGrad))
-- Temporarily disabled, as l2 adjustment puts in off 5%
-- .&&. HStatic.extract expectedKernel === HStatic.extract kernel'
@ -203,11 +205,12 @@ prop_single_conv_forwards = once $
, 0.0, 0.0, 0.0, 0.0
, 0.0, 0.0, 0.0, 0.0
, 0.0, 0.0, 0.0, 0.0 ] :: HStatic.L 4 4)
--expectedKernel = (HStatic.matrix
-- [ 0.0, 0.0, 0.0, -2.0
-- ,-2.0, 1.0, 1.0, -5.0
-- ,-3.0, -1.0, 1.0, -5.0
-- ,-5.0, 0.0, 0.0, -7.0 ] :: HStatic.L 4 4)
expectedGradient = (HStatic.matrix
[ 1.0, 0.0, 0.0, 2.0
, 2.0, 0.0, 0.0, 5.0
, 3.0, 0.0, 0.0, 4.0
, 4.0, 0.0, 0.0, 6.0 ] :: HStatic.L 4 4)
convLayer = Convolution myKernel zeroKernel :: Convolution 1 4 2 2 1 1
@ -238,13 +241,13 @@ prop_single_conv_forwards = once $
expectBack = (HStatic.matrix
[ 1.0, 0.0, 0.0
, 0.0, -2.0,-1.0] :: HStatic.L 2 3)
(nc, inX) = runIdentity $ runBackards 1 convLayer input grad :: ( Convolution 1 4 2 2 1 1 , S' ('D3 2 3 1))
(nc, inX) = runIdentity $ runBackards convLayer input grad
in case (out, inX, nc) of
(S3D' out' , S3D' inX', Convolution _ _)
(S3D' out' , S3D' inX', Convolution' backGrad)
-> ((HStatic.extract <$> expect) === (HStatic.extract <$> vecToList out'))
.&&. ([HStatic.extract expectBack] === (HStatic.extract <$> vecToList inX'))
-- .&&. HStatic.extract expectedKernel === HStatic.extract kernel'
.&&. ((HStatic.extract expectedGradient) === (HStatic.extract backGrad))
return []
tests :: IO Bool