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tensorflow-haskell/tensorflow-ops/tests/OpsTest.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 OverloadedLists #-}
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{-# LANGUAGE OverloadedStrings #-}
module Main where
import Control.Monad.IO.Class (liftIO)
import Data.Int (Int32, Int64)
import Test.Framework (defaultMain, Test)
import Lens.Family2 ((.~))
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import System.IO.Temp (withSystemTempDirectory)
import Test.Framework.Providers.HUnit (testCase)
import Test.HUnit ((@=?))
import qualified Data.ByteString.Char8 as B8
import qualified Data.Vector as V
import qualified TensorFlow.Build as TF
import qualified TensorFlow.Nodes 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
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-- | Test that one can easily determine number of elements in the tensor.
testSize :: Test
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testSize = testCase "testSize" $ do
x <- eval $ TF.size (TF.constant (TF.Shape [2, 3]) [0..5 :: Float])
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TF.Scalar (2 * 3 :: Int32) @=? x
eval :: TF.Fetchable t a => t -> IO a
eval = TF.runSession . TF.run
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-- | Confirms that the original example from Python code works.
testReducedShape :: Test
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testReducedShape = testCase "testReducedShape" $ do
x <- eval $ TF.reducedShape (TF.vector [2, 3, 5, 7 :: Int64])
(TF.vector [1, 2 :: Int32])
V.fromList [2, 1, 1, 7 :: Int32] @=? x
testSaveRestore :: Test
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testSaveRestore = testCase "testSaveRestore" $
withSystemTempDirectory "" $ \dirPath -> do
let path = B8.pack $ dirPath ++ "/checkpoint"
var :: TF.MonadBuild m => m (TF.Tensor TF.Ref Float)
var = TF.zeroInitializedVariable' (TF.opName .~ "a")
(TF.Shape [])
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TF.runSession $ do
v <- var
TF.assign v 134 >>= TF.run_
TF.save path [v] >>= TF.run_
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result <- TF.runSession $ do
v <- var
TF.restore path v >>= TF.run_
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TF.run v
liftIO $ TF.Scalar 134 @=? result
-- | Test that 'placeholder' is not CSE'd.
testPlaceholderCse :: Test
testPlaceholderCse = testCase "testPlaceholderCse" $ TF.runSession $ do
p1 <- TF.placeholder []
p2 <- TF.placeholder []
let enc :: Float -> TF.TensorData Float
enc n = TF.encodeTensorData [] (V.fromList [n])
result <- TF.runWithFeeds [TF.feed p1 (enc 2), TF.feed p2 (enc 3)]
$ p1 `TF.add` p2
liftIO $ result @=? TF.Scalar 5
-- | Test that regular tensors can also be used for feeds, as long as they each
-- have a different name.
testScalarFeedCse :: Test
testScalarFeedCse = testCase "testScalarFeedCse" $ TF.runSession $ do
p1 <- TF.render $ TF.scalar' (TF.opName .~ "A") 0
-- The second op is identical to the first other than its name; make sure
-- we don't aggressively CSE them together and prevent feeding them
-- separately.
p2 <- TF.render $ TF.scalar' (TF.opName .~ "B") 0
let enc :: Float -> TF.TensorData Float
enc n = TF.encodeTensorData [] (V.fromList [n])
result <- TF.runWithFeeds [TF.feed p1 (enc 2), TF.feed p2 (enc 3)]
$ p1 `TF.add` p2
liftIO $ result @=? TF.Scalar 5
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-- | See https://github.com/tensorflow/haskell/issues/92.
-- Even though we're not explicitly evaluating `f0` until the end,
-- it should hold the earlier value of the variable.
testRereadRef :: Test
testRereadRef = testCase "testReRunAssign" $ TF.runSession $ do
w <- TF.initializedVariable 0
f0 <- TF.run w
TF.run_ =<< TF.assign w (TF.scalar (0.1 :: Float))
f1 <- TF.run w
liftIO $ (0.0, 0.1) @=? (TF.unScalar f0, TF.unScalar f1)
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main :: IO ()
main = defaultMain
[ testSaveRestore
, testSize
, testReducedShape
, testPlaceholderCse
, testScalarFeedCse
, testRereadRef
]