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Tests
This commit is contained in:
Huw Campbell
parent
b090b5f073
commit
670f2d952f
@ -40,7 +40,6 @@ library
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Grenade.Core.Shape
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Grenade.Layers.Crop
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Grenade.Layers.Convolution
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Grenade.Layers.Convolution.Internal
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Grenade.Layers.Dropout
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Grenade.Layers.FullyConnected
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Grenade.Layers.Flatten
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@ -51,6 +50,9 @@ library
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Grenade.Layers.Pad
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Grenade.Layers.Pooling
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Grenade.Layers.Internal.Convolution
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Grenade.Layers.Internal.Pooling
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executable feedforward
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ghc-options: -Wall -threaded -O2
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@ -31,7 +31,7 @@ import Numeric.LinearAlgebra.Static hiding ((|||), build, toRows)
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import Grenade.Core.Network
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import Grenade.Core.Shape
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import Grenade.Core.Vector
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import Grenade.Layers.Convolution.Internal
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import Grenade.Layers.Internal.Convolution
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-- | A convolution layer for a neural network.
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-- This uses the im2col convolution trick popularised by Caffe, which essentially turns the
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@ -149,15 +149,13 @@ instance ( KnownNat kernelRows
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runForwards (Convolution kernel _) (S2D' input) =
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let ex = extract input
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ek = extract kernel
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ix = fromIntegral $ natVal (Proxy :: Proxy inputRows)
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iy = fromIntegral $ natVal (Proxy :: Proxy inputCols)
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kx = fromIntegral $ natVal (Proxy :: Proxy kernelRows)
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ky = fromIntegral $ natVal (Proxy :: Proxy kernelCols)
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sx = fromIntegral $ natVal (Proxy :: Proxy strideRows)
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sy = fromIntegral $ natVal (Proxy :: Proxy strideCols)
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ox = fromIntegral $ natVal (Proxy :: Proxy outputRows)
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oy = fromIntegral $ natVal (Proxy :: Proxy outputCols)
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c = im2colUnsafe kx ky sx sy ix iy ex
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c = im2colUnsafe kx ky sx sy ex
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mt = c LA.<> ek
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r = col2vidUnsafe 1 1 1 1 ox oy mt
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rs = fmap (fromJust . create) r
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@ -173,14 +171,13 @@ instance ( KnownNat kernelRows
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sy = fromIntegral $ natVal (Proxy :: Proxy strideCols)
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ox = fromIntegral $ natVal (Proxy :: Proxy outputRows)
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oy = fromIntegral $ natVal (Proxy :: Proxy outputCols)
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fl = fromIntegral $ natVal (Proxy :: Proxy filters)
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c = im2colUnsafe kx ky sx sy ix iy ex
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c = im2colUnsafe kx ky sx sy ex
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eo = vecToList $ fmap extract dEdy
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ek = extract kernel
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vs = vid2colUnsafe fl 1 1 1 1 ox oy eo
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vs = vid2colUnsafe 1 1 1 1 ox oy eo
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kN = fromJust . create $ tr c LA.<> vs
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dW = vs LA.<> tr ek
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@ -216,8 +213,8 @@ instance ( KnownNat kernelRows
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sy = fromIntegral $ natVal (Proxy :: Proxy strideCols)
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ox = fromIntegral $ natVal (Proxy :: Proxy outputRows)
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oy = fromIntegral $ natVal (Proxy :: Proxy outputCols)
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ch = fromIntegral $ natVal (Proxy :: Proxy channels)
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c = vid2colUnsafe ch kx ky sx sy ix iy ex
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c = vid2colUnsafe kx ky sx sy ix iy ex
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mt = c LA.<> ek
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r = col2vidUnsafe 1 1 1 1 ox oy mt
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rs = fmap (fromJust . create) r
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@ -232,14 +229,13 @@ instance ( KnownNat kernelRows
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sy = fromIntegral $ natVal (Proxy :: Proxy strideCols)
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ox = fromIntegral $ natVal (Proxy :: Proxy outputRows)
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oy = fromIntegral $ natVal (Proxy :: Proxy outputCols)
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ch = fromIntegral $ natVal (Proxy :: Proxy channels)
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fl = fromIntegral $ natVal (Proxy :: Proxy filters)
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c = vid2colUnsafe ch kx ky sx sy ix iy ex
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c = vid2colUnsafe kx ky sx sy ix iy ex
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eo = vecToList $ fmap extract dEdy
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ek = extract kernel
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vs = vid2colUnsafe fl 1 1 1 1 ox oy eo
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vs = vid2colUnsafe 1 1 1 1 ox oy eo
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kN = fromJust . create $ tr c LA.<> vs
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@ -1,4 +1,4 @@
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module Grenade.Layers.Convolution.Internal (
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module Grenade.Layers.Internal.Convolution (
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im2col
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-- , im2colUnsafe
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, vid2col
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@ -72,7 +72,7 @@ fittingStart width kernel steps =
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| left + kernel == width
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= [left]
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| otherwise
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= error "Kernel and step do not fit in matrix."
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= [] -- error "Kernel and step do not fit in matrix."
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in go 0
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col2imFit :: [(Int,Int)] -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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@ -119,14 +119,9 @@ col2imFit starts krows kcols drows dcols m =
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-- }
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-- }
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-- let starts = fittingStart (cols m) (krows * kcols) (krows * kcols)
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-- r = rows m
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-- mats = fmap (\s -> subMatrix (0,s) (r, krows * kcols) m) starts
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-- in parMap rseq (col2imUnsafe krows kcols srows scols drows dcols) mats
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col2imUnsafe :: Int -> Int -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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col2imUnsafe kernelRows kernelColumns strideRows strideColumns destinationRows destinationCols columnMatrix = U.runSTMatrix $ do
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let columnMatrixRows = rows columnMatrix
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dataIm <- U.newMatrix 0 destinationRows destinationCols
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@ -134,15 +129,15 @@ col2imUnsafe kernelRows kernelColumns strideRows strideColumns destinationRows d
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offsetR <- newSTRef 0
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offsetC <- newSTRef 0
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forM_ [0 .. columnMatrixRows - 1] $ \ir -> do
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inputColumn <- newSTRef 0
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forM_ [0 .. columnMatrixRows - 1] $ \inputRow -> do
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inputColumnRef <- newSTRef 0
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forM_ [0 .. kernelRows -1] $ \kr ->
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forM_ [0 .. kernelColumns -1] $ \kc -> do
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ic <- readSTRef inputColumn
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offsetR' <- readSTRef offsetR
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offsetC' <- readSTRef offsetC
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U.modifyMatrix dataIm (kr + offsetR') (kc + offsetC') (+ atIndex columnMatrix (ir,ic))
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modifySTRef inputColumn (+1)
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inputColumn <- readSTRef inputColumnRef
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offsetR' <- readSTRef offsetR
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offsetC' <- readSTRef offsetC
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U.modifyMatrix dataIm (kr + offsetR') (kc + offsetC') (+ U.atM' columnMatrix inputRow inputColumn)
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modifySTRef inputColumnRef (+1)
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offsetC' <- readSTRef offsetC
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if offsetC' + kernelColumns < destinationCols
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@ -158,12 +153,12 @@ col2vidUnsafe kernelRows kernelColumns strideRows strideColumns destinationRows
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dataIms <- traverse (\_ -> U.newMatrix 0 destinationRows destinationCols) [0 .. filters-1]
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offsetR <- newSTRef 0
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offsetC <- newSTRef 0
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offsetM <- newSTRef 0
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forM_ dataIms $ \dataIm -> do
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offsetM' <- readSTRef offsetM
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offsetR <- newSTRef 0
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offsetC <- newSTRef 0
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offsetM' <- readSTRef offsetM
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forM_ [0 .. columnMatrixRows - 1] $ \ir -> do
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inputColumn <- newSTRef 0
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forM_ [0 .. kernelRows -1] $ \kr ->
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@ -171,7 +166,7 @@ col2vidUnsafe kernelRows kernelColumns strideRows strideColumns destinationRows
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ic <- readSTRef inputColumn
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offsetR' <- readSTRef offsetR
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offsetC' <- readSTRef offsetC
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U.modifyMatrix dataIm (kr + offsetR') (kc + offsetC') (+ atIndex columnMatrix (ir, ic + offsetM'))
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U.modifyMatrix dataIm (kr + offsetR') (kc + offsetC') (+ U.atM' columnMatrix ir (ic + offsetM'))
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modifySTRef inputColumn (+1)
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offsetC' <- readSTRef offsetC
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@ -179,60 +174,55 @@ col2vidUnsafe kernelRows kernelColumns strideRows strideColumns destinationRows
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then modifySTRef offsetC (+ strideColumns)
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else writeSTRef offsetC 0 >> modifySTRef offsetR (+ strideRows)
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writeSTRef offsetR 0
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writeSTRef offsetC 0
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modifySTRef offsetM (+ (kernelRows * kernelColumns))
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traverse U.freezeMatrix dataIms
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traverse U.unsafeFreezeMatrix dataIms
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vid2colUnsafe :: Int -> Int -> Int -> Int -> Int -> Int -> Int -> [Matrix Double] -> Matrix Double
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vid2colUnsafe channels kernelRows kernelColumns striderows stridecols vidrows vidcols dataVid = U.runSTMatrix $ do
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vid2colUnsafe :: Int -> Int -> Int -> Int -> Int -> Int -> [Matrix Double] -> Matrix Double
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vid2colUnsafe kernelRows kernelColumns striderows stridecols vidrows vidcols dataVid = U.runSTMatrix $ do
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let starts = fittingStarts vidrows kernelRows striderows vidcols kernelColumns stridecols
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matWidth = kernelRows * kernelColumns
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destinationRows = 1 + (vidrows - kernelRows) `div` striderows
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destinationCols = 1 + (vidcols - kernelColumns) `div` stridecols
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destinationSize = destinationRows * destinationCols
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kernelSize = kernelRows * kernelColumns
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numberOfPatches = length starts
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channels = length dataVid
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dataCol <- U.newMatrix 0 destinationSize (channels * matWidth)
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dataCol <- U.newMatrix 0 numberOfPatches (channels * kernelSize)
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offsetC <- newSTRef 0
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forM_ dataVid $ \dataIm -> do
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inputRow <- newSTRef 0
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inputRowRef <- newSTRef 0
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offsetC' <- readSTRef offsetC
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forM_ starts $ \(startRow, startCol) -> do
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inputColumn <- newSTRef 0
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inputRow' <- readSTRef inputRow
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inputColumnRef <- newSTRef 0
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inputRow <- readSTRef inputRowRef
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forM_ [0 .. kernelRows -1] $ \kr ->
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forM_ [0 .. kernelColumns -1] $ \kc -> do
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inputColumn' <- readSTRef inputColumn
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U.modifyMatrix dataCol inputRow' (inputColumn' + offsetC') (+ atIndex dataIm (kr + startRow, kc + startCol))
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modifySTRef inputColumn (+1)
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modifySTRef inputRow (+1)
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inputColumn <- readSTRef inputColumnRef
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U.modifyMatrix dataCol inputRow (inputColumn + offsetC') (+ U.atM' dataIm (kr + startRow) (kc + startCol))
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modifySTRef inputColumnRef (+1)
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modifySTRef inputRowRef (+1)
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modifySTRef offsetC (+ matWidth)
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modifySTRef offsetC (+ kernelSize)
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return dataCol
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im2colUnsafe :: Int -> Int -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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im2colUnsafe kernelRows kernelColumns striderows stridecols vidrows vidcols dataIm = U.runSTMatrix $ do
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let starts = fittingStarts vidrows kernelRows striderows vidcols kernelColumns stridecols
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matWidth = kernelRows * kernelColumns
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destinationRows = 1 + (vidrows - kernelRows) `div` striderows
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destinationCols = 1 + (vidcols - kernelColumns) `div` stridecols
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destinationSize = destinationRows * destinationCols
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im2colUnsafe :: Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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im2colUnsafe kernelRows kernelColumns striderows stridecols dataIm = U.runSTMatrix $ do
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let starts = fittingStarts (rows dataIm) kernelRows striderows (cols dataIm) kernelColumns stridecols
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kernelSize = kernelRows * kernelColumns
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numberOfPatches = length starts
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dataCol <- U.newMatrix 0 destinationSize matWidth
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dataCol <- U.newMatrix 0 numberOfPatches kernelSize
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inputRow <- newSTRef 0
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inputRowRef <- newSTRef 0
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forM_ starts $ \(startRow, startCol) -> do
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inputColumn <- newSTRef 0
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inputRow' <- readSTRef inputRow
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inputColumnRef <- newSTRef 0
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inputRow <- readSTRef inputRowRef
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forM_ [0 .. kernelRows -1] $ \kr ->
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forM_ [0 .. kernelColumns -1] $ \kc -> do
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inputColumn' <- readSTRef inputColumn
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U.modifyMatrix dataCol inputRow' inputColumn' (+ atIndex dataIm (kr + startRow, kc + startCol))
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modifySTRef inputColumn (+1)
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modifySTRef inputRow (+1)
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inputColumn <- readSTRef inputColumnRef
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U.modifyMatrix dataCol inputRow inputColumn (+ U.atM' dataIm (kr + startRow) (kc + startCol))
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modifySTRef inputColumnRef (+1)
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modifySTRef inputRowRef (+1)
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return dataCol
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48
src/Grenade/Layers/Internal/Pooling.hs
Normal file
48
src/Grenade/Layers/Internal/Pooling.hs
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@ -0,0 +1,48 @@
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module Grenade.Layers.Internal.Pooling (
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poolForward
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, poolBackward
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, poolForwardList
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, poolBackwardList
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) where
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import Numeric.LinearAlgebra hiding ( uniformSample, konst )
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import qualified Numeric.LinearAlgebra as LA
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import Grenade.Layers.Internal.Convolution
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poolForward :: Int -> Int -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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poolForward nrows ncols srows scols outputRows outputCols m =
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let starts = fittingStarts (rows m) nrows srows (cols m) ncols scols
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in poolForwardFit starts nrows ncols outputRows outputCols m
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poolForwardList :: Functor f => Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> f (Matrix Double) -> f (Matrix Double)
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poolForwardList nrows ncols srows scols inRows inCols outputRows outputCols ms =
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let starts = fittingStarts inRows nrows srows inCols ncols scols
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in poolForwardFit starts nrows ncols outputRows outputCols <$> ms
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poolForwardFit :: [(Int,Int)] -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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poolForwardFit starts nrows ncols _ outputCols m =
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let els = fmap (\start -> maxElement $ subMatrix start (nrows, ncols) m) starts
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in LA.matrix outputCols els
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poolBackward :: Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double -> Matrix Double
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poolBackward krows kcols srows scols inputMatrix gradientMatrix =
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let inRows = rows inputMatrix
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inCols = cols inputMatrix
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starts = fittingStarts inRows krows srows inCols kcols scols
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in poolBackwardFit starts krows kcols inputMatrix gradientMatrix
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poolBackwardList :: Functor f => Int -> Int -> Int -> Int -> Int -> Int -> f (Matrix Double, Matrix Double) -> f (Matrix Double)
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poolBackwardList krows kcols srows scols inRows inCols inputMatrices =
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let starts = fittingStarts inRows krows srows inCols kcols scols
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in uncurry (poolBackwardFit starts krows kcols) <$> inputMatrices
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poolBackwardFit :: [(Int,Int)] -> Int -> Int -> Matrix Double -> Matrix Double -> Matrix Double
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poolBackwardFit starts krows kcols inputMatrix gradientMatrix =
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let inRows = rows inputMatrix
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inCols = cols inputMatrix
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inds = fmap (\start -> maxIndex $ subMatrix start (krows, kcols) inputMatrix) starts
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grads = toList $ flatten gradientMatrix
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grads' = zip3 starts grads inds
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accums = fmap (\((stx',sty'),grad,(inx, iny)) -> ((stx' + inx, sty' + iny), grad)) grads'
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in accum (LA.konst 0 (inRows, inCols)) (+) accums
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@ -24,10 +24,8 @@ import GHC.TypeLits
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import Grenade.Core.Network
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import Grenade.Core.Shape
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import Grenade.Core.Vector
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import Grenade.Layers.Convolution.Internal
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import Grenade.Layers.Internal.Pooling
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import Numeric.LinearAlgebra hiding (uniformSample)
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import qualified Numeric.LinearAlgebra as LA
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import Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRows)
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-- | A pooling layer for a neural network.
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@ -37,16 +35,12 @@ import Numeric.LinearAlgebra.Static as LAS hiding ((|||), build, toRow
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-- The kernel size dictates which input and output sizes will "fit". Fitting the equation:
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-- `out = (in - kernel) / stride + 1` for both dimensions.
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--
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data Pooling :: Nat
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-> Nat
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-> Nat
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-> Nat -> * where
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data Pooling :: Nat -> Nat -> Nat -> Nat -> * where
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Pooling :: Pooling kernelRows kernelColumns strideRows strideColumns
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instance Show (Pooling k k' s s') where
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show Pooling = "Pooling"
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instance UpdateLayer (Pooling kernelRows kernelColumns strideRows strideColumns) where
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type Gradient (Pooling kr kc sr sc) = ()
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runUpdate _ Pooling _ = Pooling
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@ -123,40 +117,3 @@ instance ( KnownNat kernelRows
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ez = vectorZip (,) ex eo
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vs = poolBackwardList kx ky sx sy ix iy ez
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in ((), S3D' . fmap (fromJust . create) $ vs)
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poolForward :: Int -> Int -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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poolForward nrows ncols srows scols outputRows outputCols m =
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let starts = fittingStarts (rows m) nrows srows (cols m) ncols scols
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in poolForwardFit starts nrows ncols outputRows outputCols m
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poolForwardList :: Functor f => Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> f (Matrix Double) -> f (Matrix Double)
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poolForwardList nrows ncols srows scols inRows inCols outputRows outputCols ms =
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let starts = fittingStarts inRows nrows srows inCols ncols scols
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in poolForwardFit starts nrows ncols outputRows outputCols <$> ms
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poolForwardFit :: [(Int,Int)] -> Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double
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poolForwardFit starts nrows ncols _ outputCols m =
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let els = fmap (\start -> maxElement $ subMatrix start (nrows, ncols) m) starts
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in LA.matrix outputCols els
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poolBackward :: Int -> Int -> Int -> Int -> Matrix Double -> Matrix Double -> Matrix Double
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poolBackward krows kcols srows scols inputMatrix gradientMatrix =
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let inRows = (rows inputMatrix)
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inCols = (cols inputMatrix)
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starts = fittingStarts inRows krows srows inCols kcols scols
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in poolBackwardFit starts krows kcols inputMatrix gradientMatrix
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poolBackwardList :: Functor f => Int -> Int -> Int -> Int -> Int -> Int -> f (Matrix Double, Matrix Double) -> f (Matrix Double)
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poolBackwardList krows kcols srows scols inRows inCols inputMatrices =
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let starts = fittingStarts inRows krows srows inCols kcols scols
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in (uncurry $ poolBackwardFit starts krows kcols) <$> inputMatrices
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poolBackwardFit :: [(Int,Int)] -> Int -> Int -> Matrix Double -> Matrix Double -> Matrix Double
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poolBackwardFit starts krows kcols inputMatrix gradientMatrix =
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let inRows = (rows inputMatrix)
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inCols = (cols inputMatrix)
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inds = fmap (\start -> maxIndex $ subMatrix start (krows, kcols) inputMatrix) starts
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grads = toList $ flatten gradientMatrix
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grads' = zip3 starts grads inds
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accums = fmap (\((stx',sty'),grad,(inx, iny)) -> ((stx' + inx, sty' + iny), grad)) grads'
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in accum (LA.konst 0 (inRows, inCols)) (+) accums
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@ -8,7 +8,7 @@ import Grenade.Core.Shape
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import Grenade.Core.Vector as Grenade
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import Grenade.Core.Network
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import Grenade.Layers.Convolution
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import Grenade.Layers.Convolution.Internal
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import Grenade.Layers.Internal.Convolution
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import Numeric.LinearAlgebra hiding (uniformSample, konst, (===))
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import qualified Numeric.LinearAlgebra.Static as HStatic
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@ -51,7 +51,7 @@ prop_im2col_other = once $
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expected = (2><6)
|
||||
[ 1.0, 2.0, 5.0, 6.0 , 9.0, 10.0
|
||||
, 3.0, 4.0, 7.0, 8.0 , 11.0 ,12.0 ]
|
||||
out = im2col 3 2 1 2 input
|
||||
out = im2colUnsafe 3 2 1 2 input
|
||||
in expected === out
|
||||
|
||||
-- If there's no overlap (stride is the same size as the kernel)
|
||||
@ -71,7 +71,7 @@ prop_im2colunsafe_sym_on_same_stride = once $
|
||||
[ 1.0, 2.0, 3.0, 4.0
|
||||
, 5.0, 6.0, 7.0, 8.0
|
||||
, 9.0, 10.0, 11.0, 12.0 ]
|
||||
out = col2imUnsafe 3 2 3 2 3 4 . im2colUnsafe 3 2 3 2 3 4 $ input
|
||||
out = col2imUnsafe 3 2 3 2 3 4 . im2colUnsafe 3 2 3 2 $ input
|
||||
in input === out
|
||||
|
||||
|
||||
@ -86,7 +86,7 @@ prop_im2col_col2im_additive = once $
|
||||
[ 1.0, 2.0, 2.0, 1.0
|
||||
, 2.0, 4.0, 4.0, 2.0
|
||||
, 1.0, 2.0, 2.0, 1.0 ]
|
||||
out = col2im 2 2 1 1 3 4 . im2col 2 2 1 1 $ input
|
||||
out = col2imUnsafe 2 2 1 1 3 4 . im2colUnsafe 2 2 1 1 $ input
|
||||
in expected === out
|
||||
|
||||
prop_simple_conv_forwards = once $
|
||||
@ -166,7 +166,7 @@ prop_vid2col_no_stride = once $
|
||||
, 5.0, 6.0, 9.0, 10.0 , 25.0, 26.0, 29.0, 30.0
|
||||
, 6.0, 7.0, 10.0, 11.0 , 26.0, 27.0, 30.0, 31.0
|
||||
, 7.0, 8.0, 11.0, 12.0 , 27.0, 28.0, 31.0, 32.0 ]
|
||||
out = vid2col 2 2 1 1 3 4 input
|
||||
out = vid2colUnsafe 2 2 1 1 3 4 input
|
||||
in expected === out
|
||||
|
||||
prop_vid2col_stride = once $
|
||||
@ -183,7 +183,7 @@ prop_vid2col_stride = once $
|
||||
, 3.0, 4.0, 7.0, 8.0 , 23.0, 24.0, 27.0, 28.0
|
||||
, 5.0, 6.0, 9.0, 10.0 , 25.0, 26.0, 29.0, 30.0
|
||||
, 7.0, 8.0, 11.0, 12.0 , 27.0, 28.0, 31.0, 32.0 ]
|
||||
out = vid2col 2 2 1 2 3 4 input
|
||||
out = vid2colUnsafe 2 2 1 2 3 4 input
|
||||
in expected === out
|
||||
|
||||
|
||||
@ -208,7 +208,7 @@ prop_vid2col_invert_unsafe = once $
|
||||
[ 21.0, 22.0, 23.0, 24.0
|
||||
, 25.0, 26.0, 27.0, 28.0
|
||||
, 29.0, 30.0, 31.0, 32.0 ] ]
|
||||
out = col2vidUnsafe 3 2 3 2 3 4 . vid2colUnsafe 2 3 2 3 2 3 4 $ input
|
||||
out = col2vidUnsafe 3 2 3 2 3 4 . vid2colUnsafe 3 2 3 2 3 4 $ input
|
||||
in input === out
|
||||
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user