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tensorflow-haskell/tensorflow-ops/tests/BuildTest.hs
Judah Jacobson c99a23b6a7 Add versions of each op that take optional params as an extra arg. (#84)
Each op `foo :: ...` now has a corresponding `foo' :: OpParams -> ...`
which lets you set optional attributes.  `OpParams` is currently a type alias for
`OpDef -> OpDef`.  In the future we should consider more type safety, e.g.,
using type-level strings and OverloadedLabels for optional attributes.

I used it to replace a few manual `buildOp`s in our code with the codegenerated
ops, now that it's easier to set attributes.  I also removed `tensorAttr` and
`named` since it's now possible to set those op attributes directly.

Although this clutters up the API a bit, I think it's simpler than using type
classes to implement optional arguments (as in, for example, `Text.Printf`) --
especially in terms of type inference with the rest of the library.
2017-03-20 18:16:38 -07:00

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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 OverloadedStrings #-}
{-# LANGUAGE OverloadedLists #-}
{-# LANGUAGE ScopedTypeVariables #-}
module Main where
import Control.Monad.IO.Class (liftIO)
import Lens.Family2 ((^.), (.~))
import Data.List (sort)
import Proto.Tensorflow.Core.Framework.Graph
( node )
import Proto.Tensorflow.Core.Framework.NodeDef
( NodeDef
, device
, name
, op )
import TensorFlow.Build
( Build
, BuildT
, asGraphDef
, evalBuildT
, flushNodeBuffer
, render
, withDevice
, colocateWith
, withNameScope
, opName
)
import TensorFlow.Types (unScalar)
import TensorFlow.Ops
( add
, assign
, constant
, initializedVariable
, variable
, variable'
)
import TensorFlow.Output (Device(..))
import TensorFlow.Tensor (Tensor, Value, Ref)
import TensorFlow.Session
( run
, runSession
, run_
)
import Test.Framework (Test)
import Test.Framework.Providers.HUnit (testCase)
import Test.HUnit ((@=?))
import Google.Test (googleTest)
import qualified Data.Vector as V
-- | Test 'opName' behavior.
testOpName :: Test
testOpName = testCase "testOpName" $ do
let graph = variable' (opName .~ "foo") []
>>= render :: Build (Tensor Ref Float)
nodeDef :: NodeDef
nodeDef = head $ asGraphDef graph ^. node
"Variable" @=? (nodeDef ^. op)
"foo" @=? (nodeDef ^. name)
-- | Test that "run" will render and extend any pure ops that haven't already
-- been rendered.
testPureRender :: Test
testPureRender = testCase "testPureRender" $ runSession $ do
result <- run $ 2 `add` 2
liftIO $ 4 @=? (unScalar result :: Float)
-- | Test that "run" assigns any previously accumulated initializers.
testInitializedVariable :: Test
testInitializedVariable =
testCase "testInitializedVariable" $ runSession $ do
(formula, reset) <- do
v <- initializedVariable 42
r <- assign v 24
return (1 `add` v, r)
result <- run formula
liftIO $ 43 @=? (unScalar result :: Float)
run_ reset -- Updates v to a different value
rerunResult <- run formula
liftIO $ 25 @=? (unScalar rerunResult :: Float)
testInitializedVariableShape :: Test
testInitializedVariableShape =
testCase "testInitializedVariableShape" $ runSession $ do
vector <- initializedVariable (constant [1] [42 :: Float])
result <- run vector
liftIO $ [42] @=? (result :: V.Vector Float)
-- | Test nameScoped behavior.
testNameScoped :: Test
testNameScoped = testCase "testNameScoped" $ do
let graph = withNameScope "foo" $ variable [] :: Build (Tensor Ref Float)
nodeDef :: NodeDef
[nodeDef] = asGraphDef graph ^. node
"foo/Variable_0" @=? (nodeDef ^. name) -- TODO: Check prefix.
"Variable" @=? (nodeDef ^. op)
-- | Test combined opName and nameScoped behavior.
testNamedAndScoped :: Test
testNamedAndScoped = testCase "testNamedAndScoped" $ do
let graph :: Build (Tensor Ref Float)
graph = withNameScope "foo1" (variable' (opName .~ "bar1") [])
>>= render
nodeDef :: NodeDef
nodeDef = head $ asGraphDef graph ^. node
"Variable" @=? (nodeDef ^. op)
"foo1/bar1" @=? (nodeDef ^. name)
-- | Flush the node buffer and sort the nodes by name (for more stable tests).
flushed :: Ord a => (NodeDef -> a) -> BuildT IO [a]
flushed field = sort . map field <$> flushNodeBuffer
-- | Test the interaction of rendering, CSE and scoping.
testRenderDedup :: Test
testRenderDedup = testCase "testRenderDedup" $ evalBuildT $ do
renderNodes
names <- flushed (^. name)
liftIO $ ["Const_1", "Variable_0", "Variable_2"] @=? names
-- Render the nodes in a different scope, which should cause them
-- to be distinct from the previous ones.
withNameScope "foo" renderNodes
scopedNames <- flushed (^. name)
liftIO $ ["foo/Const_4", "foo/Variable_3", "foo/Variable_5"] @=? scopedNames
where
renderNodes = do
-- A stateful op and a pure op.
_ :: Tensor Ref Float <- variable []
_ :: Tensor Value Float <- render 3
-- Another stateful op, and a pure op which should be
-- deduped with the previous one.
_ :: Tensor Ref Float <- variable []
_ :: Tensor Value Float <- render 3
return ()
-- | Test the interaction of rendering, CSE and scoping.
testDeviceColocation :: Test
testDeviceColocation = testCase "testDeviceColocation" $ evalBuildT $ do
renderNodes
devices <- flushed (\x -> (x ^. name, x ^. device))
liftIO $ [ ("Add_2","dev0")
, ("Const_1","dev0")
, ("Variable_0","dev0")] @=? devices
where
renderNodes = do
-- A stateful op and a pure op.
var :: Tensor Ref Float <- withDevice (Just $ Device "dev0") $ variable []
-- Uses render to cause the expression be added to the graph.
_ <- colocateWith var $ render $ 3 `add` var
return ()
main :: IO ()
main = googleTest [ testInitializedVariable
, testInitializedVariableShape
, testDeviceColocation
, testOpName
, testNameScoped
, testNamedAndScoped
, testPureRender
, testRenderDedup
]