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tensorflow-haskell/tensorflow-ops/tests/GradientTest.hs

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-- 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 OverloadedStrings #-}
{-# LANGUAGE NoMonomorphismRestriction #-}
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{-# LANGUAGE ScopedTypeVariables #-}
import Data.Int (Int32)
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import Data.List (sort)
import Data.ProtoLens.TextFormat (showMessage)
import Google.Test (googleTest)
import Lens.Family2 ((^..))
import Test.Framework (Test)
import Test.Framework.Providers.HUnit (testCase)
import Test.HUnit ((@=?))
import qualified Data.Vector as V
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import qualified TensorFlow.Core as TF
import qualified TensorFlow.GenOps.Core as TF (max)
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import qualified TensorFlow.Gradient as TF
import qualified TensorFlow.Ops as TF
import Proto.Tensorflow.Core.Framework.Graph (node)
import Proto.Tensorflow.Core.Framework.NodeDef (op)
testGradientSimple :: Test
testGradientSimple = testCase "testGradientSimple" $ do
let grads = do
x <- TF.render $ TF.scalar (3 :: Float)
b <- TF.render $ TF.scalar (4 :: Float)
let y = x `TF.mul` x `TF.add` b
TF.gradients y [x, b]
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-- Assert that the gradients are right.
[dx, db] <- TF.runSession $ grads >>= TF.run
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6 @=? TF.unScalar dx
1 @=? TF.unScalar db
-- Assert that the graph has the expected ops.
let graphDef = TF.asGraphDef grads
putStrLn $ showMessage graphDef
let ops = graphDef ^.. node . traverse . op
expected = [ "Const"
, "Mul"
, "Const"
, "Add"
-- Default output gradient of y.
, "Shape"
, "Const"
, "Fill"
-- Add gradient.
, "Shape"
, "Shape"
, "BroadcastGradientArgs"
, "Sum"
, "Sum"
, "Reshape"
, "Reshape"
-- Mul gradient.
, "Shape"
-- This Op gets dedup'd because the inputs are the same.
-- TODO(fmayle): The same would happen to the Mul and Sum ops
-- below if the gradient function didn't multiply one as
-- 'dz * y' and the other as 'x * dz'. We could change the
-- order, but I'm going to keep it the same as the python
-- version for now.
--
-- , "Shape"
, "BroadcastGradientArgs"
, "Mul"
, "Mul"
, "Sum"
, "Sum"
, "Reshape"
, "Reshape"
-- AddN to combine x's output gradients.
, "AddN"
]
sort expected @=? sort ops
testGradientDisconnected :: Test
testGradientDisconnected = testCase "testGradientDisconnected" $ do
let grads = do
x <- TF.render $ TF.scalar (3 :: Float)
b <- TF.render $ TF.scalar (4 :: Float)
TF.gradients x [x, b]
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-- Assert that the gradients are right.
[dx, db] <- TF.runSession $ grads >>= TF.run
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1 @=? TF.unScalar dx
0 @=? TF.unScalar db
-- Assert that the graph has the expected ops.
let graphDef = TF.asGraphDef grads
putStrLn $ showMessage graphDef
let ops = graphDef ^.. node . traverse . op
expected = [ "Const"
, "Const"
-- Default output gradient of x.
, "Shape"
, "Const"
, "Fill"
-- Default output gradient of b.
, "ZerosLike"
]
sort expected @=? sort ops
-- Test that identical "stateful" ops work with createGraph.
testCreateGraphStateful :: Test
testCreateGraphStateful = testCase "testCreateGraphStateful" $ do
[dx, dy] <- TF.runSession $ do
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let shape = TF.constant (TF.Shape [1]) [1]
x :: TF.Tensor TF.Value Float <- TF.truncatedNormal shape
y :: TF.Tensor TF.Value Float <- TF.truncatedNormal shape
TF.gradients (TF.expr x + TF.expr y * 3) [x, y] >>= TF.run
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-- If this test fails, it will likely be caused by an exception within
-- `TF.gradients`. These asserts are extra.
1 @=? TF.unScalar dx
3 @=? TF.unScalar dy
-- Test that name scopes work with createGraph.
testCreateGraphNameScopes :: Test
testCreateGraphNameScopes = testCase "testCreateGraphNameScopes" $ do
[dx] <- TF.runSession $ do
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let shape = TF.constant (TF.Shape [1]) [1]
x :: TF.Tensor TF.Value Float <-
TF.withNameScope "foo" (TF.truncatedNormal shape)
TF.gradients x [x] >>= TF.run
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-- If this test fails, it will likely be caused by an exception within
-- `TF.gradients`. This assert is extra.
1 @=? TF.unScalar dx
-- Test that createGraph can handle graphs with diamond shapes.
testDiamond :: Test
testDiamond = testCase "testDiamond" $ do
[dx] <- TF.runSession $ do
x <- TF.render $ TF.vector [1]
let y = x `TF.mul` x
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z = y*y
TF.gradients z [x] >>= TF.run
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(4 :: Float) @=? TF.unScalar dx
testMaxGradient :: Test
testMaxGradient = testCase "testMaxGradient" $ do
[dx] <- TF.runSession $ do
x <- TF.render $ TF.vector [1, 2, 3, 0, 1 :: Float]
let y = TF.max x (0 :: TF.Tensor TF.Build Int32)
TF.gradients y [x] >>= TF.run
V.fromList [0, 0, 1, 0, 0 :: Float] @=? dx
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main :: IO ()
main = googleTest [ testGradientSimple
, testGradientDisconnected
, testCreateGraphStateful
, testCreateGraphNameScopes
, testDiamond
, testMaxGradient
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]