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Fixed matMul gradients for transposed arguments
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51014a015c
commit
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4 changed files with 100 additions and 24 deletions
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@ -551,13 +551,13 @@ opGrad "MatMul" nodeDef [toT -> x, toT -> y] [dz] =
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, Just $ matMul' (transAttrs True False) x dz]
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(False, True) ->
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[ Just $ matMul dz y
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, Just $ matMul' (transAttrs True False) x dz]
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, Just $ matMul' (transAttrs True False) dz x]
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(True, False) ->
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[ Just $ matMul' (transAttrs False True) dz y
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[ Just $ matMul' (transAttrs False True) y dz
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, Just $ matMul x dz]
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(True, True) ->
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[ Just $ matMul' (transAttrs True True) dz y
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, Just $ matMul' (transAttrs True True) x dz]
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[ Just $ matMul' (transAttrs True True) y dz
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, Just $ matMul' (transAttrs True True) dz x]
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opGrad "Transpose" _ [_, toT -> p] [dz] =
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[ Just $ CoreOps.transpose dz
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@ -318,21 +318,15 @@ scalarize t = CoreOps.reshape t (vector scalarShape)
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-- | Sum a tensor down to a scalar
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-- Seee `TensorFlow.GenOps.Core.sum`
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reduceSum
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:: ( TensorType a
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, OneOf '[ Double, Float, Int32, Int64
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, Complex Float, Complex Double] a
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)
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=> Tensor v a -> Tensor Build a
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reduceSum :: (OneOf '[ Double, Float, Int32, Int64
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, Complex Float, Complex Double] a) =>
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Tensor v a -> Tensor Build a
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reduceSum x = CoreOps.sum x allAxes
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where allAxes = CoreOps.range 0 (CoreOps.rank x :: Tensor Build Int32) 1
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reduceSum'
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:: ( TensorType a
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, OneOf '[ Double, Float, Int32, Int64
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, Complex Float, Complex Double] a
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)
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=> OpParams -> Tensor v a -> Tensor Build a
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reduceSum' :: (OneOf '[ Double, Float, Int32, Int64
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, Complex Float, Complex Double] a) =>
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OpParams -> Tensor v a -> Tensor Build a
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reduceSum' params x = CoreOps.sum' params x allAxes
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where allAxes = CoreOps.range 0 (CoreOps.rank x :: Tensor Build Int32) 1
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@ -200,6 +200,7 @@ Test-Suite GradientTest
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, tensorflow-proto
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, test-framework
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, test-framework-hunit
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, transformers
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, vector
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Test-Suite MiscTest
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@ -15,21 +15,26 @@
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{-# LANGUAGE OverloadedStrings #-}
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{-# LANGUAGE NoMonomorphismRestriction #-}
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{-# LANGUAGE ScopedTypeVariables #-}
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{-# LANGUAGE FlexibleContexts #-}
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import Data.Int (Int32)
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import Data.Int (Int32, Int64)
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import Data.List (sort)
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import Data.ProtoLens.TextFormat (showMessage)
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import Google.Test (googleTest)
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import Lens.Family2 ((^..))
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import Lens.Family2 ((^..), (.~))
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import Test.Framework (Test)
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import Test.Framework.Providers.HUnit (testCase)
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import Test.HUnit ((@=?))
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import Test.HUnit ((@=?), assertEqual)
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import qualified Data.Vector as V
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import Control.Monad.IO.Class (liftIO)
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import qualified TensorFlow.Core as TF
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import qualified TensorFlow.GenOps.Core as TF (max, tile)
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import qualified TensorFlow.Gradient as TF
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import qualified TensorFlow.Ops as TF
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import qualified TensorFlow.Output as TF
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import qualified TensorFlow.Types as TF
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import Proto.Tensorflow.Core.Framework.Graph (node)
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import Proto.Tensorflow.Core.Framework.NodeDef (op)
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@ -207,15 +212,85 @@ testTile2DGrad = testCase "testTileGrad2D" $ do
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let y = TF.tile x multiples
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[dx] <- TF.gradients y [x]
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shapeDX <- TF.run $ TF.shape dx
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shapeX <- TF.run $ TF.shape x
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dxv <- TF.run dx
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return (dxv, shapeDX, shapeX)
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TF.run (dx, TF.shape dx, TF.shape x)
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shapeX @=? (shapeDX :: V.Vector Int32)
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V.fromList [6, 6, 6, 6, 6, 6::Float] @=? (dx :: V.Vector Float)
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matMulGradient :: Test
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matMulGradient = testCase "matMulGradients" $ do
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let dfBuild = do
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x <- TF.render $ TF.zeros $ TF.Shape [3, 1 :: Int64]
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w <- TF.zeroInitializedVariable $ TF.Shape [1, 2 :: Int64]
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let f = x `TF.matMul` w :: TF.Tensor TF.Build Float
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dfs <- TF.gradients f [x]
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return (x, dfs)
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(xShape, dxShape) <- TF.runSession $ do
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(x, [dx]) <- TF.build dfBuild
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TF.run (TF.shape x, TF.shape dx)
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assertEqual "Shape of gradient must match shape of input" xShape (dxShape :: V.Vector Int32)
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-- test that gradient of matMul can be taken gradient of
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matMulGradGrad :: Test
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matMulGradGrad = testCase "matMulGradGrad" $ do
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let width = 2 :: Int64
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batch = 4 :: Int64
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let tower = do
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x <- TF.render $ TF.zeros $ TF.Shape [batch, 1]
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w <- TF.zeroInitializedVariable $ TF.Shape [1, width]
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let f = x `TF.matMul` w
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[dfdx] <- TF.gradients f [x]
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let f'x = TF.reduceSum dfdx
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[dfdw] <- TF.gradients f'x [w] -- take gradient again (this time over w)
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return [TF.value w, dfdw]
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TF.runSession $ do
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[w, dfdw] <- TF.build tower
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(wShape, dfdwShape) <- TF.run (TF.shape w, TF.shape dfdw)
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liftIO $ assertEqual "Shape of gradient must match input" wShape (dfdwShape :: V.Vector Int32)
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let step = w `TF.add` dfdw
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w0 <- TF.run step
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liftIO $ ((V.fromList [4, 4 :: Float]) @=? w0)
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-- test that gradient of matMul deals correctly with transpose_a and transpose_b
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matMulTransposeGradient :: (Bool, Bool) -> Test
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matMulTransposeGradient txw = testCase ("matMulTransposeGradients " ++ (show txw)) $ do
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let (transposeX, transposeW) = txw
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let dfBuild = do
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let xShape = TF.Shape [3, 1 :: Int64]
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let xZeros = TF.zeros xShape
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x <- TF.render $ if transposeX then TF.matTranspose xZeros else xZeros
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variable <- TF.zeroInitializedVariable $ TF.Shape [1, 2 :: Int64]
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let wv = if transposeW then TF.matTranspose variable else TF.expr variable
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let f = TF.matMul' (transAttrs transposeX transposeW) x wv :: TF.Tensor TF.Build Float
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w <- TF.render wv
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ds <- TF.gradients f [x, w]
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return (x, w, ds)
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TF.runSession $ do
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(x, w, [dx, dw]) <- TF.build dfBuild
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xShape <- TF.run $ TF.shape x
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dxShape <- TF.run $ TF.shape dx
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liftIO $ assertEqual "xShape must match dxShape" xShape (dxShape :: V.Vector Int32)
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wShape <- TF.run $ TF.shape w
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dwShape <- TF.run $ TF.shape dw
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liftIO $ assertEqual "wShape must match dwShape" wShape (dwShape :: V.Vector Int32)
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transAttrs :: (TF.Attribute a,
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TF.Attribute b) =>
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a -> b -> TF.OpDef -> TF.OpDef
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transAttrs a b =
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(TF.opAttr "transpose_a" .~ a) . (TF.opAttr "transpose_b" .~ b)
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main :: IO ()
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main = googleTest [ testGradientSimple
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, testGradientDisconnected
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@ -228,4 +303,10 @@ main = googleTest [ testGradientSimple
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, testFillGrad
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, testTileGrad
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, testTile2DGrad
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, matMulGradient
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, matMulGradGrad
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, matMulTransposeGradient (False, False)
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, matMulTransposeGradient (False, True)
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, matMulTransposeGradient (True, False)
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, matMulTransposeGradient (True, True)
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]
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