Add GLEU

src/GEval/BLEU.hs

@@ -1,9 +1,12 @@
 module GEval.BLEU
-       (precisionCount, bleuStep)
+       (precisionCount, bleuStep, gleuStep)
        where
 
+import GEval.Common
+import GEval.PrecisionRecall
+
 import qualified Data.MultiSet as MS
-import Data.List (minimumBy, zip, zip3, zip4)
+import Data.List (minimumBy, maximumBy, zip, zip3, zip4)
 
 bleuStep :: Ord a => [[a]] -> [a] -> (Int, Int, Int, Int,  Int,  Int, Int, Int, Int)
 bleuStep refs trans = (prec1, prec2, prec3, prec4,  closestLen, len1, len2, len3, len4)
@@ -21,18 +24,13 @@ bleuStep refs trans = (prec1, prec2, prec3, prec4,  closestLen, len1, len2, len3
         len2 = max 0 (len1 - 1)
         len3 = max 0 (len1 - 2)
         len4 = max 0 (len1 - 3)
-        bigrams [] = []
-        bigrams [_] = []
-        bigrams u = zip u $ tail u
-        trigrams [] = []
-        trigrams [_] = []
-        trigrams [_, _] = []
-        trigrams u = zip3 u (tail u) (tail $ tail u)
-        tetragrams [] = []
-        tetragrams [_] = []
-        tetragrams [_, _] = []
-        tetragrams [_, _, _] = []
-        tetragrams u = zip4 u (tail u) (tail $ tail u) (tail $ tail $ tail u)
+
+gleuStep :: Ord a => [[a]] -> [a] -> (Int, Int)
+gleuStep refs trans = maximumBy (\(g1, t1) (g2, t2) -> (g1 /. t1) `compare` (g2 /. t2)) $ map getBetterCounts refs
+  where getBetterCounts ref = let (matched, expected, got) = getCounts (==) (upToTetragrams ref, transNgrams)
+                                  total = max expected got
+                              in (matched, total)
+        transNgrams = upToTetragrams trans
 
 precisionCount :: Ord a => [[a]] -> [a] -> Int
 precisionCount refs = sum . map (lookFor refs) . MS.toOccurList . MS.fromList
@@ -40,3 +38,30 @@ precisionCount refs = sum . map (lookFor refs) . MS.toOccurList . MS.fromList
         findE e freq m = min freq (MS.occur e m)
         minimumOrZero [] = 0
         minimumOrZero l = minimum l
+
+data Ngram a = Unigram a | Bigram (a, a) | Trigram (a, a, a) | Tetragram (a, a, a, a)
+               deriving (Eq, Show)
+
+upToTetragrams :: [a] -> [Ngram a]
+upToTetragrams l = (map Unigram l)
+                   ++ (map Bigram $ bigrams l)
+                   ++ (map Trigram $ trigrams l)
+                   ++ (map Tetragram $ tetragrams l)
+
+bigrams :: [a] -> [(a, a)]
+bigrams [] = []
+bigrams [_] = []
+bigrams u = zip u $ tail u
+
+trigrams :: [a] -> [(a, a, a)]
+trigrams [] = []
+trigrams [_] = []
+trigrams [_, _] = []
+trigrams u = zip3 u (tail u) (tail $ tail u)
+
+tetragrams :: [a] -> [(a, a, a, a)]
+tetragrams [] = []
+tetragrams [_] = []
+tetragrams [_, _] = []
+tetragrams [_, _, _] = []
+tetragrams u = zip4 u (tail u) (tail $ tail u) (tail $ tail $ tail u)

src/GEval/Core.hs

@@ -97,7 +97,7 @@ defaultLogLossHashedSize :: Word32
 defaultLogLossHashedSize = 10
 
 -- | evaluation metric
-data Metric = RMSE | MSE | BLEU | Accuracy | ClippEU | FMeasure Double | NMI
+data Metric = RMSE | MSE | BLEU | GLEU | Accuracy | ClippEU | FMeasure Double | NMI
               | LogLossHashed Word32 | CharMatch | MAP | LogLoss | Likelihood
               | BIOF1 | BIOF1Labels | LikelihoodHashed Word32 | MAE | MultiLabelFMeasure Double
               | MultiLabelLogLoss | MultiLabelLikelihood
@@ -107,6 +107,7 @@ instance Show Metric where
   show RMSE = "RMSE"
   show MSE  = "MSE"
   show BLEU = "BLEU"
+  show GLEU = "GLEU"
   show Accuracy = "Accuracy"
   show ClippEU = "ClippEU"
   show (FMeasure beta) = "F" ++ (show beta)
@@ -138,6 +139,7 @@ instance Read Metric where
   readsPrec _ ('R':'M':'S':'E':theRest) = [(RMSE, theRest)]
   readsPrec _ ('M':'S':'E':theRest) = [(MSE, theRest)]
   readsPrec _ ('B':'L':'E':'U':theRest) = [(BLEU, theRest)]
+  readsPrec _ ('G':'L':'E':'U':theRest) = [(GLEU, theRest)]
   readsPrec _ ('A':'c':'c':'u':'r':'a':'c':'y':theRest) = [(Accuracy, theRest)]
   readsPrec _ ('C':'l':'i':'p':'p':'E':'U':theRest) = [(ClippEU, theRest)]
   readsPrec _ ('N':'M':'I':theRest) = [(NMI, theRest)]
@@ -172,6 +174,7 @@ getMetricOrdering :: Metric -> MetricOrdering
 getMetricOrdering RMSE     = TheLowerTheBetter
 getMetricOrdering MSE      = TheLowerTheBetter
 getMetricOrdering BLEU     = TheHigherTheBetter
+getMetricOrdering GLEU     = TheHigherTheBetter
 getMetricOrdering Accuracy = TheHigherTheBetter
 getMetricOrdering ClippEU  = TheHigherTheBetter
 getMetricOrdering (FMeasure _) = TheHigherTheBetter
@@ -516,6 +519,12 @@ gevalCore' BLEU _ = gevalCoreWithoutInput (Right . Prelude.map Prelude.words . D
           | c == 0 && r > 0 = 0.0
           | otherwise = exp (1.0 - (r /. c))
 
+gevalCore' GLEU _ = gevalCoreWithoutInput (Right . Prelude.map Prelude.words . DLS.splitOn "\t" . unpack) (Right . Prelude.words . unpack) gleuCombine gleuAgg gleuFinal
+  where gleuFinal (m, t) = m /. t
+        gleuCombine (refs, sen) = gleuStep refs sen
+        gleuAgg = CC.foldl gleuFuse (0, 0)
+        gleuFuse (a1, a2) (b1, b2) = (a1+b1, a2+b2)
+
 gevalCore' Accuracy _ = gevalCoreWithoutInput (Right . strip) (Right . strip) hitOrMiss averageC id
                       where hitOrMiss (exp, got) =
                               -- first try to parse what we got as a probability distribution

src/GEval/CreateChallenge.hs

@@ -52,6 +52,7 @@ createFile filePath contents = do
   writeFile filePath contents
 
 readmeMDContents :: Metric -> String -> String
+readmeMDContents GLEU testName = readmeMDContents BLEU testName
 readmeMDContents BLEU testName = [i|
 GEval sample machine translation challenge
 ==========================================
@@ -313,6 +314,7 @@ configContents metrics precision testName = unwords (Prelude.map (\metric -> ("-
           precisionOpt (Just p) = " --precision " ++ (show p)
 
 trainContents :: Metric -> String
+trainContents GLEU = trainContents BLEU
 trainContents BLEU = [hereLit|alussa loi jumala taivaan ja maan	he mea hanga na te atua i te timatanga te rangi me te whenua
 ja maa oli autio ja tyhjä , ja pimeys oli syvyyden päällä	a kahore he ahua o te whenua , i takoto kau ; he pouri ano a runga i te mata o te hohonu
 ja jumalan henki liikkui vetten päällä	na ka whakapaho te wairua o te atua i runga i te kare o nga wai
@@ -384,6 +386,7 @@ trainContents _ = [hereLit|0.06	0.39	0	0.206
 |]
 
 devInContents :: Metric -> String
+devInContents GLEU = devInContents BLEU
 devInContents BLEU = [hereLit|ja jumala sanoi : " tulkoon valkeus " , ja valkeus tuli
 ja jumala näki , että valkeus oli hyvä ; ja jumala erotti valkeuden pimeydestä
 |]
@@ -431,6 +434,7 @@ devInContents _ = [hereLit|0.72	0	0.007
 |]
 
 devExpectedContents :: Metric -> String
+devExpectedContents GLEU = devExpectedContents BLEU
 devExpectedContents BLEU = [hereLit|a ka ki te atua , kia marama : na ka marama
 a ka kite te atua i te marama , he pai : a ka wehea e te atua te marama i te pouri
 |]
@@ -478,6 +482,7 @@ devExpectedContents _ = [hereLit|0.82
 |]
 
 testInContents :: Metric -> String
+testInContents GLEU = testInContents BLEU
 testInContents BLEU = [hereLit|ja jumala kutsui valkeuden päiväksi , ja pimeyden hän kutsui yöksi
 ja tuli ehtoo , ja tuli aamu , ensimmäinen päivä
 |]
@@ -524,6 +529,7 @@ I hate
 |]
 
 testExpectedContents :: Metric -> String
+testExpectedContents GLEU = testExpectedContents BLEU
 testExpectedContents BLEU = [hereLit|na ka huaina e te atua te marama ko te awatea , a ko te pouri i huaina e ia ko te po
 a ko te ahiahi , ko te ata , he ra kotahi
 |]

src/GEval/OptionsParser.hs

@@ -169,7 +169,7 @@ metricReader = many $ option auto         -- actually `some` should be used inst
                ( long "metric"            -- --metric might be in the config.txt file...
                  <> short 'm'
                  <> metavar "METRIC"
-                 <> help "Metric to be used - RMSE, MSE, Accuracy, LogLoss, Likelihood, F-measure (specify as F1, F2, F0.25, etc.), multi-label F-measure (specify as MultiLabel-F1, MultiLabel-F2, MultiLabel-F0.25, etc.), MAP, BLEU, NMI, ClippEU, LogLossHashed, LikelihoodHashed, BIO-F1, BIO-F1-Labels or CharMatch" )
+                 <> help "Metric to be used - RMSE, MSE, Accuracy, LogLoss, Likelihood, F-measure (specify as F1, F2, F0.25, etc.), multi-label F-measure (specify as MultiLabel-F1, MultiLabel-F2, MultiLabel-F0.25, etc.), MAP, BLEU, GLEU (\"Google GLEU\" not the grammar correction metric), NMI, ClippEU, LogLossHashed, LikelihoodHashed, BIO-F1, BIO-F1-Labels or CharMatch" )
 
 altMetricReader :: Parser (Maybe Metric)
 altMetricReader = optional $ option auto

test/Spec.hs

@@ -81,6 +81,9 @@ main = hspec $ do
       runGEvalTest "bleu-empty" `shouldReturnAlmost` 0.0000
     it "with tokenization" $
       runGEvalTest "bleu-with-tokenization" `shouldReturnAlmost` 0.6501914150070065
+  describe "GLEU" $ do
+    it "simple example" $
+      runGEvalTest "gleu-simple" `shouldReturnAlmost` 0.462962962962963
   describe "Accuracy" $ do
     it "simple example" $
       runGEvalTest "accuracy-simple" `shouldReturnAlmost` 0.6

test/gleu-simple/gleu-simple-solution/test-A/out.tsv

@@ -0,0 +1,3 @@
+I can sing the rainbow in a book .
+The
+This is a sample sentence .

test/gleu-simple/gleu-simple/config.txt

@@ -0,0 +1 @@
+--metric GLEU

test/gleu-simple/gleu-simple/test-A/expected.tsv

@@ -0,0 +1,3 @@
+I can see a rainbow .
+The dog .
+This is a sample sentence .