Updated machines and added regression machine timer

UD_any/data/Makefile

@@ -9,7 +9,7 @@ TEST_FILES=$(shell find . -type f -name '*test*.conllu')
 THRESHOLD=10
 FPLM_FILENAME=fplm
 
-all: tokenizer.ts segmenter.ts texts all_no_test.conllu transitions pretrain
+all: writescore_TIME.ts tokenizer.ts segmenter.ts texts all_no_test.conllu transitions pretrain
 	rm -f all_no_test.conllu
 
 all_no_test.conllu:
@@ -40,6 +40,9 @@ segmenter.ts:
 	echo "EOS b.0" > $@
 	echo "NOTEOS b.0" >> $@
 	sed -i -e 's/^/<segmenter> /' $@
+
+writescore_TIME.ts:
+	echo "WRITESCORE b.0 TIME" > $@
  
 transitions: all_no_test.conllu
 	./getTransitionSets.py $<
@@ -48,7 +51,7 @@ texts:
 	./getRawText.py $(CONLL2TXT) $(TRAIN_FILES) $(DEV_FILES) $(TEST_FILES)
 
 pretrain:
-	for col in FORM UPOS FEATS DEPREL LETTERS ; do \
+	for col in FORM UPOS LEMMA FEATS DEPREL LETTERS ; do \
 	./pretrainEmbeddings.sh $(TRAIN_FILES) $$col 64 $$col.w2v 2> pretrain_log.err || ( cat pretrain_log.err && exit 1 ) ; \
 	done
 

UD_any/templates/lemmatizer/machine.rm

@@ -4,18 +4,18 @@ Classifier : lemmatizer
 	Transitions : {lemmatizer_rules,data/lemmatizer_rules.ts, lemmatizer_case,data/lemmatizer_case.ts}
 	LossMultiplier : {}
 	Network type : Modular
-	Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{lower:FORM} LSTM{1 1 0 1} In{64} Out{64}
-	Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64}
-	Context : Buffer{-2 -1 0} Stack{} Columns{LEMMA} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{ID} NbElem{1} Buffer{-1 0 1 1} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{prefix3:FORM} NbElem{3} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{suffix3:FORM} NbElem{3} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{EOS} NbElem{1} Buffer{-1 0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
+	Context : Targets{b.-2 b.-1 b.0 b.1 b.2} Columns{lower:FORM UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{UPOS,data/UPOS.w2v FORM,data/FORM.w2v}
+	Context : Targets{b.-2 b.-1 b.0 b.1 b.2} Columns{ID EOS} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+	Context : Targets{b.-2 b.-1 b.0} Columns{LEMMA} LSTM{1 1 0 1} In{64} Out{64} w2v{LEMMA,data/LEMMA.w2v}
+	Focused : Column{prefix3:FORM} NbElem{3} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+	Focused : Column{suffix3:FORM} NbElem{3} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
 	UppercaseRate : Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} Out{32}
-	InputDropout : 0.5
-	MLP : {4096 0.3}
+	InputDropout : 0.3
+	MLP : {1600 0.3 1600 0.3}
 	End
-  Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
+  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
 }
 Predictions : LEMMA
 Strategy

UD_any/templates/morpho/machine.rm

@@ -4,16 +4,17 @@ Classifier : morpho
 	Transitions : {morpho,data/morpho_parts.ts}
 	LossMultiplier : {}
 	Network type : Modular
-	Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM UPOS} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{ID} NbElem{1} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{FORM} NbElem{13} Buffer{-1 0 1 2} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{FEATS} NbElem{13} Buffer{-2 -1 0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	Focused : Column{EOS} NbElem{1} Buffer{-1 0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	History : NbElem{10} LSTM{1 1 0 1} In{64} Out{64}
-	InputDropout : 0.5
-	MLP : {2048 0.3 2048 0.3}
+  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
+  Context : Targets{b.-2 b.-1 b.0 b.1 b.2} Columns{EOS ID UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
+  Focused : Column{FEATS} NbElem{13} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+	InputDropout : 0.3
+	MLP : {1600 0.3 1600 0.3}
 	End
-	Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
+  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
 }
 Predictions : FEATS
 Strategy

UD_any/templates/parser/machine.rm

@@ -4,7 +4,7 @@ Classifier : parser
   Transitions : {parser,data/parser_eager_rel_strict.ts}
   LossMultiplier : {}
   Network type : Modular
-  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
+  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
   Context : Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{UPOS FEATS EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
   Context : Targets{s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{DEPREL} LSTM{1 1 0 1} In{64} Out{64} w2v{}
   History : NbElem{10} LSTM{1 1 0 1} In{32} Out{32}
@@ -12,6 +12,8 @@ Classifier : parser
   MLP : {1600 0.3 1600 0.3}
   End
   Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
 }
 Predictions : HEAD DEPREL
 Strategy

UD_any/templates/parserseg/machine.rm

@@ -2,22 +2,19 @@ Name : Parser and Segmenter machine
 Classifier : parserseg
 {
 	Transitions : {parser,data/parser_eager_rel_strict.ts segmenter,data/segmenter.ts}
-  LossMultiplier : {segmenter,3.0}
+  LossMultiplier : {}
   Network type : Modular
-  StateName : Out{1024}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM} LSTM{1 1 0 1} In{64} Out{64}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{1 0} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{ID} NbElem{1} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{FORM} NbElem{13} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{FEATS} NbElem{13} Buffer{-1 0} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{EOS} NbElem{1} Buffer{-2 -1} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{DEPREL} NbElem{1} Buffer{} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  DepthLayerTree : Columns{DEPREL} Buffer{} Stack{2 1 0} LayerSizes{3} LSTM{1 1 0.0 1} In{64} Out{64}
-  History : NbElem{10} LSTM{1 1 0 1} In{64} Out{64}
-  InputDropout : 0.5
-  MLP : {2048 0.3 2048 0.3}
+  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
+  Context : Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{UPOS FEATS EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
+  Context : Targets{s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{DEPREL} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  History : NbElem{10} LSTM{1 1 0 1} In{32} Out{32}
+  InputDropout : 0.3
+  MLP : {1600 0.3 1600 0.3}
   End
-  Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
+  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
+
 }
 Predictions : HEAD DEPREL EOS
 Strategy

UD_any/templates/tagger/machine.rm

@@ -4,15 +4,17 @@ Classifier : tagger
 	Transitions : {tagger,data/tagger.ts}
 	LossMultiplier : {}
 	Network type : Modular
-  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
+  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
   Context : Targets{b.-2 b.-1 b.0 b.1 b.2} Columns{EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{b.-3 b.-2 b.-1} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{data/UPOS.w2v} 
-  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
+  Context : Targets{b.-3 b.-2 b.-1} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{UPOS,data/UPOS.w2v} 
+  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
 	InputDropout : 0.3
 	MLP : {1600 0.3 1600 0.3}
 	End
   Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
 }
 Predictions : UPOS
 Strategy

UD_any/templates/taggerparser_base/machine.rm

-Name : Tagger, Parser and Segmenter baseline Machine
-Classifier : taggerparser
-{
-	Transitions : {tagger,data/tagger.ts parser,data/parser_eager_rel_strict.ts segmenter,data/segmenter.ts}
-  LossMultiplier : {segmenter,3.0}
-  Network type : Modular
-  StateName : Out{1024}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM} LSTM{1 1 0 1} In{64} Out{64}
-  Context : Buffer{-3 -2 -1 0} Stack{1 0} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{ID} NbElem{1} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{FORM} NbElem{13} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{EOS} NbElem{1} Buffer{-1} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{DEPREL} NbElem{1} Buffer{} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  DepthLayerTree : Columns{DEPREL} Buffer{} Stack{2 1 0} LayerSizes{3} LSTM{1 1 0.0 1} In{64} Out{64}
-  History : NbElem{10} LSTM{1 1 0 1} In{64} Out{64}
-  InputDropout : 0.5
-  MLP : {2048 0.3 2048 0.3}
-  End
-  Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
-}
-Predictions : UPOS HEAD DEPREL EOS
-Strategy
-{
-	Block : End{cannotMove}
-	tagger tagger * 1
-	Block : End{cannotMove}
-	parser segmenter eager_SHIFT 0
-	parser segmenter eager_RIGHT_rel 0
-	parser parser * 0
-	segmenter parser * 1
-}

UD_any/templates/taggerparser_incr/machine.rm

-Name : Tagger, Parser and Segmenter incremental Machine
-Classifier : taggerparser
-{
-  Transitions : {tagger,data/tagger.ts parser,data/parser_eager_rel_strict.ts segmenter,data/segmenter.ts}
-  LossMultiplier : {segmenter,3.0}
-  Network type : Modular
-  StateName : Out{1024}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM} LSTM{1 1 0 1} In{64} Out{64}
-  Context : Buffer{-3 -2 -1 0} Stack{1 0} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{ID} NbElem{1} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{FORM} NbElem{13} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{EOS} NbElem{1} Buffer{-1} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{DEPREL} NbElem{1} Buffer{} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  DepthLayerTree : Columns{DEPREL} Buffer{} Stack{2 1 0} LayerSizes{3} LSTM{1 1 0.0 1} In{64} Out{64}
-  History : NbElem{10} LSTM{1 1 0 1} In{64} Out{64}
-  InputDropout : 0.5
-  MLP : {2048 0.3 2048 0.3}
-  End
-  Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
-}
-Predictions : UPOS HEAD DEPREL EOS
-Strategy
-{
-	Block : End{cannotMove}
-	tagger parser * 0
-	parser segmenter eager_SHIFT 0
-	parser segmenter eager_RIGHT_rel 0
-	parser parser * 0
-	segmenter tagger * 1
-}

UD_any/templates/taggerparser_incr_one/machine.rm

-Name : Tagger and Parser incremental Machine with one classifier
-Classifier : taggerparser
-{
-  Transitions : {tagger,data/tagger.ts parser,data/parser_eager_rel_strict.ts}
-  LossMultiplier : {}
-  Network type : Modular
-  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
-  Context : Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{b.-2 b.-1 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{s.0 s.1 s.2 s.0.0 b.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{DEPREL} LSTM{1 1 0 1} In{64} Out{64} w2v{}
-  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  History : NbElem{10} LSTM{1 1 0 1} In{32} Out{32}
-  InputDropout : 0.3
-  MLP : {1600 0.3 1600 0.3}
-  End
-  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
-
-}
-Predictions : UPOS HEAD DEPREL
-Strategy
-{
-	Block : End{cannotMove}
-	tagger parser * 0
-	parser tagger eager_SHIFT 1
-	parser tagger eager_RIGHT_rel 1
-	parser parser * 0
-}

UD_any/templates/taggerparser_incr_two/machine.rm

-Name : Tagger and Parser incremental Machine with two classifiers
-Classifier : tagger
-{
-	Transitions : {tagger,data/tagger.ts}
-	LossMultiplier : {}
-	Network type : Modular
-  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
-  Context : Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{}
-  Context : Targets{b.-2 b.-1 s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{s.0 s.1 s.2 b.0.0 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{DEPREL} LSTM{1 1 0 1} In{64} Out{64} w2v{}
-  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	InputDropout : 0.3
-	MLP : {1600 0.3 1600 0.3}
-	End
-  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
-}
-Classifier : parser
-{
-  Transitions : {parser,data/parser_eager_rel_strict.ts}
-  LossMultiplier : {}
-  Network type : Modular
-  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2}
-  Context : Targets{b.-2 b.-1 b.0 b.1 b.2 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{EOS ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{b.-2 b.-1 b.0 s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Context : Targets{s.0 s.1 s.2 s.0.0 s.0.-1 s.1.0 s.1.-1 s.0.1 s.0.-2 s.1.1 s.1.-2} Columns{DEPREL} LSTM{1 1 0 1} In{64} Out{64} w2v{}
-  History : NbElem{10} LSTM{1 1 0 1} In{32} Out{32}
-  InputDropout : 0.3
-  MLP : {1600 0.3 1600 0.3}
-  End
-  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
-}
-Predictions : UPOS HEAD DEPREL
-Strategy
-{
-	Block : End{cannotMove}
-	tagger parser * 0
-	parser tagger eager_SHIFT 1
-	parser tagger eager_RIGHT_rel 1
-	parser parser * 0
-}

UD_any/templates/taggerparser_seq/machine.rm

-Name : Tagger, Parser and Segmenter sequential Machine
-Classifier : taggerparser
-{
-	Transitions : {tagger,data/tagger.ts parser,data/parser_eager_rel_strict.ts segmenter,data/segmenter.ts}
-  LossMultiplier : {segmenter,3.0}
-  Network type : Modular
-  StateName : Out{1024}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{} Columns{FORM} LSTM{1 1 0 1} In{64} Out{64}
-  Context : Buffer{-3 -2 -1 0 1 2} Stack{1 0} Columns{UPOS} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{ID} NbElem{1} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{FORM} NbElem{13} Buffer{-1 0 1 2} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{EOS} NbElem{1} Buffer{-1} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{DEPREL} NbElem{1} Buffer{} Stack{2 1 0} LSTM{1 1 0 1} In{64} Out{64}
-  DepthLayerTree : Columns{DEPREL} Buffer{} Stack{2 1 0} LayerSizes{3} LSTM{1 1 0.0 1} In{64} Out{64}
-  History : NbElem{10} LSTM{1 1 0 1} In{64} Out{64}
-  InputDropout : 0.5
-  MLP : {2048 0.3 2048 0.3}
-  End
-  Optimizer : Adam {0.0003 0.9 0.999 0.00000001 0.00002 true}
-}
-Predictions : UPOS HEAD DEPREL EOS
-Strategy
-{
-	Block : End{cannotMove}
-	tagger tagger * 1
-	Block : End{cannotMove}
-	parser segmenter eager_SHIFT 0
-	parser segmenter eager_RIGHT_rel 0
-	parser parser * 0
-	segmenter parser * 1
-}

UD_any/templates/timer/machine.rm

+Name : Timer Machine
+Classifier : timer
+{
+	Transitions : {timer,data/writescore_TIME.ts}
+	LossMultiplier : {}
+	Network type : Modular
+  Contextual : Window{-10 10} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
+  Context : Targets{b.-2 b.-1 b.0 b.1 b.2} Columns{EOS ID UPOS} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+	InputDropout : 0.3
+	MLP : {1600 0.3 1600 0.3}
+	End
+  Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : regression
+  Loss : mse
+}
+Predictions : TIME
+Strategy
+{
+	Block : End{cannotMove}
+	timer timer * 1
+}

UD_any/templates/tokenizer/machine.rm

@@ -4,16 +4,18 @@ Classifier : tokenizer
 	Transitions : {tokenizer,data/tokenizer.ts}
   LossMultiplier : {}
   Network type : Modular
-  Contextual : Window{-10 0} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
-  Context : Targets{b.-2 b.-1 b.0} Columns{ID} LSTM{1 1 0 1} In{64} Out{64} w2v{} 
-  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64}
-	RawInput : Left{5} Right{10} LSTM{1 1 0.0 1} In{32} Out{32}
+  Contextual : Window{-10 0} Columns{FORM} LSTM{1 1 0 1} In{64} Out{128} w2v{FORM,data/FORM.w2v} Targets{b.-2 b.-1 b.0 b.1 b.2}
+  Context : Targets{b.-2 b.-1 b.0} Columns{ID} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  Focused : Column{prefix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+  Focused : Column{suffix3:FORM} NbElem{3} Buffer{0} Stack{} LSTM{1 1 0 1} In{64} Out{64} w2v{}
+	RawInput : Left{5} Right{10} LSTM{1 1 0.0 1} In{32} Out{32} w2v{}
   History : NbElem{10} LSTM{1 1 0 1} In{32} Out{32}
 	InputDropout : 0.3
 	MLP : {1600 0.3 1600 0.3}
 	End
   Optimizer : Adagrad {0.01 0.000001 0 0.0000000001}
+  Type : classification
+  Loss : crossentropy
 }
 Splitwords : data/splitwords.ts
 Predictions : ID FORM EOS

scripts/conll18_ud_eval.py

@@ -111,6 +111,19 @@ metric2colname = {
   "Lemmas" : "LEMMA",
 }
 
+defaultColumns = {
+"ID",
+"FORM",
+"UPOS",
+"XPOS",
+"LEMMA",
+"FEATS",
+"HEAD",
+"DEPREL",
+"DEPS",
+"MISC",
+}
+
 # Content and functional relations
 CONTENT_DEPRELS = {
   "nsubj", "obj", "iobj", "csubj", "ccomp", "xcomp", "obl", "vocative",
@@ -129,6 +142,16 @@ UNIVERSAL_FEATURES = {
   "Tense", "Aspect", "Voice", "Evident", "Polarity", "Person", "Polite"
 }
 
+################################################################################
+def is_float(value) :
+  if not isinstance(value, str) :
+    return False
+  try:
+    float(value)
+    return '.' in value
+  except ValueError:
+    return False
+################################################################################
 
 ################################################################################
 def filter_columns(columns) :
@@ -400,10 +423,15 @@ def evaluate(gold_ud, system_ud) :
     errors = []
     for words in alignment.matched_words :
       if filter_fn is None or filter_fn(words.gold_word) :
-        if key_fn(words.gold_word, gold_aligned_gold) == key_fn(words.system_word, gold_aligned_system) :
-          correct += 1
+        goldItem = key_fn(words.gold_word, gold_aligned_gold)
+        systemItem = key_fn(words.system_word, gold_aligned_system)
+        if (not isinstance(systemItem, str) or '.' not in systemItem or not is_float(systemItem)) or  (not isinstance(goldItem, str) or '.' not in goldItem or not is_float(goldItem)) :
+          if goldItem == systemItem :
+            correct += 1
+          else :
+            errors.append(words)
         else :
-          errors.append(words)
+          correct -= abs(float(goldItem) - float(systemItem))
 
     return [Score(gold, system, correct, aligned), errors]
 
@@ -532,6 +560,10 @@ def evaluate(gold_ud, system_ud) :
   if "ID" in col2index :
     result["Sentences"] = spans_score(gold_ud.sentences, system_ud.sentences)
 
+  for colName in col2index :
+    if colName not in defaultColumns and colName != "_" :
+      result[colName] = alignment_score(alignment, lambda w, _ : w.columns[col2index[colName]])
+
   return result
 ################################################################################
 

scripts/readMCD.py

@@ -2,8 +2,11 @@ def readMCD(mcd) :
   col2index = {}
   index2col = {}
 
+  curId = 0
+
   for col in mcd.split(' ') :
-    col2index[col] = len(col2index)
-    index2col[len(index2col)] = col
+    col2index[col] = curId
+    index2col[curId] = col
+    curId += 1
 
   return col2index, index2col