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f170df9d13
In addition, you can now fetch TensorData directly. This might be useful in
scenarios where you feed the result of a computation back in, like RNN.
Before:
benchmarking feedFetch/4 byte
time 83.31 μs (81.88 μs .. 84.75 μs)
0.997 R² (0.994 R² .. 0.998 R²)
mean 87.32 μs (86.06 μs .. 88.83 μs)
std dev 4.580 μs (3.698 μs .. 5.567 μs)
variance introduced by outliers: 55% (severely inflated)
benchmarking feedFetch/4 KiB
time 114.9 μs (111.5 μs .. 118.2 μs)
0.996 R² (0.994 R² .. 0.998 R²)
mean 117.3 μs (116.2 μs .. 118.6 μs)
std dev 3.877 μs (3.058 μs .. 5.565 μs)
variance introduced by outliers: 31% (moderately inflated)
benchmarking feedFetch/4 MiB
time 109.0 ms (107.9 ms .. 110.7 ms)
1.000 R² (0.999 R² .. 1.000 R²)
mean 108.6 ms (108.2 ms .. 109.2 ms)
std dev 740.2 μs (353.2 μs .. 1.186 ms)
After:
benchmarking feedFetch/4 byte
time 82.92 μs (80.55 μs .. 85.24 μs)
0.996 R² (0.993 R² .. 0.998 R²)
mean 83.58 μs (82.34 μs .. 84.89 μs)
std dev 4.327 μs (3.664 μs .. 5.375 μs)
variance introduced by outliers: 54% (severely inflated)
benchmarking feedFetch/4 KiB
time 85.69 μs (83.81 μs .. 87.30 μs)
0.997 R² (0.996 R² .. 0.999 R²)
mean 86.99 μs (86.11 μs .. 88.15 μs)
std dev 3.608 μs (2.854 μs .. 5.273 μs)
variance introduced by outliers: 43% (moderately inflated)
benchmarking feedFetch/4 MiB
time 1.582 ms (1.509 ms .. 1.677 ms)
0.970 R² (0.936 R² .. 0.993 R²)
mean 1.645 ms (1.554 ms .. 1.981 ms)
std dev 490.6 μs (138.9 μs .. 1.067 ms)
variance introduced by outliers: 97% (severely inflated)
67 lines
2.7 KiB
Haskell
67 lines
2.7 KiB
Haskell
-- Copyright 2016 TensorFlow authors.
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--
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-- Licensed under the Apache License, Version 2.0 (the "License");
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-- you may not use this file except in compliance with the License.
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-- You may obtain a copy of the License at
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--
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-- http://www.apache.org/licenses/LICENSE-2.0
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--
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-- Unless required by applicable law or agreed to in writing, software
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-- distributed under the License is distributed on an "AS IS" BASIS,
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-- WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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-- See the License for the specific language governing permissions and
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-- limitations under the License.
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{-# LANGUAGE FlexibleContexts #-}
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{-# LANGUAGE ScopedTypeVariables #-}
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import Data.Int (Int32, Int64)
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import Data.List (genericLength)
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import Google.Test (googleTest)
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import Test.Framework.Providers.QuickCheck2 (testProperty)
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import Test.HUnit ((@=?))
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import Test.QuickCheck (Arbitrary(..), Property, choose, vectorOf)
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import Test.QuickCheck.Monadic (monadicIO, run)
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import qualified Data.Vector as V
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import qualified TensorFlow.GenOps.Core as CoreOps
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import qualified TensorFlow.Ops as TF
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import qualified TensorFlow.Session as TF
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import qualified TensorFlow.Tensor as TF
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import qualified TensorFlow.Types as TF
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-- DynamicSplit is undone with DynamicStitch to get the original input
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-- back.
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testDynamicPartitionStitchInverse :: forall a.
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(TF.TensorDataType V.Vector a, Show a, Eq a) => StitchExample a -> Property
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testDynamicPartitionStitchInverse (StitchExample numParts values partitions) =
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let splitParts :: [TF.Tensor TF.Value a] =
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CoreOps.dynamicPartition numParts (TF.vector values) partTensor
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partTensor = TF.vector partitions
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restitchIndices = CoreOps.dynamicPartition numParts
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(TF.vector [0..genericLength values-1])
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partTensor
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-- drop (numParts - 2) from both args to expose b/27343984
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restitch = CoreOps.dynamicStitch restitchIndices splitParts
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in monadicIO $ run $ do
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fromIntegral numParts @=? length splitParts
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valuesOut <- TF.runSession $ TF.buildAnd TF.run $ return restitch
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V.fromList values @=? valuesOut
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data StitchExample a = StitchExample Int64 [a] [Int32]
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deriving Show
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instance Arbitrary a => Arbitrary (StitchExample a) where
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arbitrary = do
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-- Limits the size of the vector.
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size <- choose (1, 100)
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values <- vectorOf size arbitrary
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numParts <- choose (2, 15)
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partitions <- vectorOf size (choose (0, fromIntegral numParts - 1))
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return $ StitchExample numParts values partitions
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main :: IO ()
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main = googleTest
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[ testProperty "DynamicPartitionStitchInverse"
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(testDynamicPartitionStitchInverse :: StitchExample Int64 -> Property)
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]
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