1
0
Fork 0
mirror of https://github.com/tensorflow/haskell.git synced 2024-11-23 11:29:43 +01:00
tensorflow-haskell/tensorflow-nn/tests/NNTest.hs
Greg Steuck 9f2f4e2877 Fixed CI and added indicator. (#15)
* Sorted test names.

* Don't require a terminal to run tests.

Should resolve "the input device is not a TTY" problem with Jenkins.

* Added build indicator to README.md.

* Fixed up URL.
2016-10-28 18:08:32 -07:00

119 lines
4.1 KiB
Haskell

-- Copyright 2016 TensorFlow authors.
--
-- Licensed under the Apache License, Version 2.0 (the "License");
-- you may not use this file except in compliance with the License.
-- You may obtain a copy of the License at
--
-- http://www.apache.org/licenses/LICENSE-2.0
--
-- Unless required by applicable law or agreed to in writing, software
-- distributed under the License is distributed on an "AS IS" BASIS,
-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-- See the License for the specific language governing permissions and
-- limitations under the License.
{-# LANGUAGE OverloadedLists #-}
{-# LANGUAGE OverloadedStrings #-}
{-# LANGUAGE NoMonomorphismRestriction #-}
{-# LANGUAGE FlexibleInstances #-}
{-# LANGUAGE FlexibleContexts #-}
module Main where
import Data.Maybe (fromMaybe)
import Google.Test (googleTest)
import Test.Framework.Providers.HUnit (testCase)
import Test.HUnit ((@?))
import Test.HUnit.Lang (Assertion(..))
import qualified Data.Vector as V
import qualified TensorFlow.Build as TF
import qualified TensorFlow.Gradient as TF
import qualified TensorFlow.NN as TF
import qualified TensorFlow.Ops as TF
import qualified TensorFlow.Session as TF
import qualified TensorFlow.Tensor as TF
import qualified TensorFlow.Types as TF
-- | These tests are ported from:
--
-- <tensorflow>/tensorflow/python/ops/nn_xent_tests.py
--
-- This is the implementation we use to check the implementation we
-- wrote in `TensorFlow.NN.sigmoidCrossEntropyWithLogits`.
--
sigmoidXentWithLogits :: Floating a => Ord a => [a] -> [a] -> [a]
sigmoidXentWithLogits logits' targets' =
let sig = map (\x -> 1 / (1 + exp (-x))) logits'
eps = 0.0001
pred = map (\p -> min (max p eps) (1 - eps)) sig
xent y z = (-z) * (log y) - (1 - z) * log (1 - y)
in zipWith xent pred targets'
data Inputs = Inputs {
logits :: [Float]
, targets :: [Float]
}
defInputs :: Inputs
defInputs = Inputs {
logits = [-100, -2, -2, 0, 2, 2, 2, 100]
, targets = [ 0, 0, 1, 0, 0, 1, 0.5, 1]
}
assertAllClose :: V.Vector Float -> V.Vector Float -> Assertion
assertAllClose xs ys = all (<= tol) (V.zipWith absDiff xs ys) @?
("Difference > tolerance: \nxs: " ++ show xs ++ "\nys: " ++ show ys
++ "\ntolerance: " ++ show tol)
where
absDiff x y = abs (x - y)
tol = 0.001 :: Float
testLogisticOutput = testCase "testLogisticOutput" $ do
let inputs = defInputs
vLogits = TF.vector $ logits inputs
vTargets = TF.vector $ targets inputs
tfLoss = TF.sigmoidCrossEntropyWithLogits vLogits vTargets
ourLoss = V.fromList $ sigmoidXentWithLogits (logits inputs) (targets inputs)
r <- run tfLoss
assertAllClose r ourLoss
testLogisticOutputMultipleDim =
testCase "testLogisticOutputMultipleDim" $ do
let inputs = defInputs
shape = [2, 2, 2]
vLogits = TF.constant shape (logits inputs)
vTargets = TF.constant shape (targets inputs)
tfLoss = TF.sigmoidCrossEntropyWithLogits vLogits vTargets
ourLoss = V.fromList $ sigmoidXentWithLogits (logits inputs) (targets inputs)
r <- run tfLoss
assertAllClose r ourLoss
testGradientAtZero = testCase "testGradientAtZero" $ do
let inputs = defInputs { logits = [0, 0], targets = [0, 1] }
vLogits = TF.vector $ logits inputs
vTargets = TF.vector $ targets inputs
tfLoss = TF.sigmoidCrossEntropyWithLogits vLogits vTargets
r <- run $ do
l <- tfLoss
TF.gradients l [vLogits]
assertAllClose (head r) (V.fromList [0.5, -0.5])
run = TF.runSession . TF.buildAnd TF.run
main :: IO ()
main = googleTest [ testGradientAtZero
, testLogisticOutput
, testLogisticOutputMultipleDim
]