Merge branch 'develop' of https://github.com/explosion/spaCy into develop

spacy/cli/train.py

@@ -140,7 +140,8 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=10, n_sents=0,
                 with nlp.use_params(optimizer.averages):
                     dill.dump(nlp, file_, -1)
         except:
-            pass
+            print("Error saving model")
+
 
 def _render_parses(i, to_render):
     to_render[0].user_data['title'] = "Batch %d" % i

spacy/tests/lang/en/test_lemmatizer.py

@@ -57,7 +57,6 @@ def test_en_lemmatizer_punct(en_lemmatizer):
 def test_en_lemmatizer_lemma_assignment(EN):
     text = "Bananas in pyjamas are geese."
     doc = EN.make_doc(text)
-    EN.tensorizer(doc)
     assert all(t.lemma_ == '' for t in doc)
     EN.tagger(doc)
     assert all(t.lemma_ != '' for t in doc)

spacy/tests/lang/en/test_models.py

@@ -52,6 +52,7 @@ def test_en_models_vectors(example):
     # this isn't a perfect test since this could in principle fail
     # in a sane model as well,
     # but that's very unlikely and a good indicator if something is wrong
+    if example.vocab.vectors_length:
         vector0 = example[0].vector
         vector1 = example[1].vector
         vector2 = example[2].vector

spacy/tests/regression/test_issue429.py

@@ -22,7 +22,6 @@ def test_issue429(EN):
     matcher = Matcher(EN.vocab)
     matcher.add('TEST', merge_phrases, [{'ORTH': 'a'}])
     doc = EN.make_doc('a b c')
-    EN.tensorizer(doc)
     EN.tagger(doc)
     matcher(doc)
     EN.entity(doc)