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tensorflow-haskell/tensorflow-ops/tests/MatrixTest.hs
Judah Jacobson ff5f1cccf4 Increase the number of iterations for MatrixTest. (#107)
The number of iterations was reduced from 1000 to 300 during review, but that
turned out to be too low and the test now fails about 20% of the time.
After changing it back to 1000, the test succeeded at 50 out of 50 runs.
2017-05-09 09:54:09 -07:00

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1.7 KiB
Haskell

{-# LANGUAGE FlexibleContexts #-}
{-# LANGUAGE OverloadedLists #-}
import Control.Monad.IO.Class (liftIO)
import Control.Monad (replicateM_, zipWithM)
import qualified TensorFlow.GenOps.Core as TF (square, rank)
import qualified TensorFlow.Core as TF
import qualified TensorFlow.Gradient as TF
import qualified TensorFlow.Ops as TF
import qualified Data.Vector as V
import Test.Framework (Test)
import Test.Framework.Providers.HUnit (testCase)
import TensorFlow.Test (assertAllClose)
import Google.Test (googleTest)
randomParam :: TF.Shape -> TF.Session (TF.Tensor TF.Value Float)
randomParam (TF.Shape shape) = TF.truncatedNormal (TF.vector shape)
reduceMean :: TF.Tensor v Float -> TF.Tensor TF.Build Float
reduceMean xs = TF.mean xs (TF.range 0 (TF.rank xs) 1)
fitMatrix :: Test
fitMatrix = testCase "fitMatrix" $ TF.runSession $ do
u <- TF.initializedVariable =<< randomParam [2, 1]
v <- TF.initializedVariable =<< randomParam [1, 2]
let ones = [1, 1, 1, 1] :: [Float]
matx = TF.constant [2, 2] ones
diff = matx `TF.sub` (u `TF.matMul` v)
loss = reduceMean $ TF.square diff
trainStep <- gradientDescent 0.01 loss [u, v]
replicateM_ 1000 (TF.run trainStep)
(u',v') <- TF.run (u, v)
-- ones = u * v
liftIO $ assertAllClose (V.fromList ones) ((*) <$> u' <*> v')
gradientDescent :: Float
-> TF.Tensor TF.Build Float
-> [TF.Tensor TF.Ref Float]
-> TF.Session TF.ControlNode
gradientDescent alpha loss params = do
let applyGrad param grad =
TF.assign param (param `TF.sub` (TF.scalar alpha `TF.mul` grad))
TF.group =<< zipWithM applyGrad params =<< TF.gradients loss params
main :: IO ()
main = googleTest [ fitMatrix ]