Fix error in Graph when called during evaluation

Author: YNedderhoff

modules/graphs.py

@@ -56,10 +56,11 @@ def __init__(self, tokens, mode="sparse", feat_map=None, weight_vector=None):
                     distance = give_distance(0, token1.id, direction)
 
                     new_arc = Arc("sparse", 0, token1.id)
-                    new_arc.feat_vec = [f for f in (feat_map[feature] for feature in
-                                                    give_features("__ROOT__", "__ROOT__", "__ROOT__", token1.form,
-                                                                  token1.lemma, token1.pos, token1.rel, direction,
-                                                                  distance) if feature in feat_map)]
+                    if feat_map is not None:
+                        new_arc.feat_vec = [f for f in (feat_map[feature] for feature in
+                                                        give_features("__ROOT__", "__ROOT__", "__ROOT__", token1.form,
+                                                                      token1.lemma, token1.pos, token1.rel, direction,
+                                                                      distance) if feature in feat_map)]
                     self.heads[0].append(new_arc)
 
                 # add every other arc
@@ -69,10 +70,12 @@ def __init__(self, tokens, mode="sparse", feat_map=None, weight_vector=None):
                     distance = give_distance(token1.id, token2.id, direction)
 
                     new_arc = Arc("sparse", token1.id, token2.id)
-                    new_arc.feat_vec = [f for f in (feat_map[feature] for feature in
-                                                    give_features(token1.form, token1.lemma, token1.pos, token2.form,
-                                                                  token2.lemma, token2.pos, token2.rel, direction,
-                                                                  distance) if feature in feat_map)]
+                    if feat_map is not None:
+                        new_arc.feat_vec = [f for f in (feat_map[feature] for feature in
+                                                        give_features(token1.form, token1.lemma, token1.pos,
+                                                                      token2.form,
+                                                                      token2.lemma, token2.pos, token2.rel, direction,
+                                                                      distance) if feature in feat_map)]
                     dependents.append(new_arc)
                 if dependents:
                     self.heads[token1.id] = dependents

start-cle.sh

@@ -9,15 +9,15 @@ PREDICTIONS="predictions"
 EVALUATIONS="evaluations"
 
 #train (on small set)
-python -u dependency-parser.py -train -i $CORPORA/train/wsj_train.first-5k.conll06 -m model -e 10
+#python -u dependency-parser.py -train -i $CORPORA/train/wsj_train.first-5k.conll06 -m model -e 10
 #python -u dependency-parser.py -train -i $CORPORA/train/wsj_train_super_small.conll06 -m model -e 1
 #python -u dependency-parser.py -train -i $CORPORA/train/wsj_train_hyper_small.conll06 -m model -e 1
 
 #train
 #python -u dependency-parser.py -train -i $CORPORA/train/wsj_train.conll06 -m $MODELS/model -e 2 -decrease-alpha
 
 #test
-python -u dependency-parser.py -test -i $CORPORA/dev/wsj_dev_without_head.conll06 -m model -o predicted.conll06
+#python -u dependency-parser.py -test -i $CORPORA/dev/wsj_dev_without_head.conll06 -m model -o predicted.conll06
 
 #evaluate sentence based
 python -u dependency-parser.py -ev -i predicted.conll06 -g $CORPORA/dev/wsj_dev.conll06 -o evaluation_sentence.txt