Update a random test to reflect the latest models

stanfordnlp · Dec 21, 2024 · 449daeb · 449daeb
1 parent d50517f
commit 449daeb
Showing 1 changed file with 4 additions and 4 deletions.
diff --git a/stanza/tests/pipeline/test_decorators.py b/stanza/tests/pipeline/test_decorators.py
@@ -45,7 +45,7 @@
 
 <Token id=1;words=[<Word id=1;text=This;lemma=cool;upos=PRON;xpos=DT;feats=Number=Sing|PronType=Dem>]>
 <Token id=2;words=[<Word id=2;text=is;lemma=cool;upos=AUX;xpos=VBZ;feats=Mood=Ind|Number=Sing|Person=3|Tense=Pres|VerbForm=Fin>]>
-<Token id=3;words=[<Word id=3;text=another;lemma=cool;upos=DET;xpos=DT>]>
+<Token id=3;words=[<Word id=3;text=another;lemma=cool;upos=DET;xpos=DT;feats=PronType=Ind>]>
 <Token id=4;words=[<Word id=4;text=!;lemma=cool;upos=PUNCT;xpos=.>]>'''
 
 @register_processor("lowercase")
@@ -72,7 +72,7 @@ def process(self, doc):
         return doc
 
 def test_register_processor():
-    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors='tokenize,lowercase')
+    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors='tokenize,lowercase', download_method=None)
     doc = nlp(EN_DOC)
     assert EN_DOC_LOWERCASE_TOKENS == '\n\n'.join(sent.tokens_string() for sent in doc.sentences)
 
@@ -94,7 +94,7 @@ def process(self, text):
         return Document([sentence], text)
 
 def test_register_processor_variant():
-    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors={"tokenize": "lol"}, package=None)
+    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors={"tokenize": "lol"}, package=None, download_method=None)
     doc = nlp(EN_DOC)
     assert EN_DOC_LOL_TOKENS == '\n\n'.join(sent.tokens_string() for sent in doc.sentences)
 
@@ -115,7 +115,7 @@ def process(self, document):
         return document
 
 def test_register_processor_variant_with_override():
-    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors={"tokenize": "combined", "pos": "combined_nocharlm", "lemma": "cool"}, package=None)
+    nlp = stanza.Pipeline(dir=TEST_MODELS_DIR, lang='en', processors={"tokenize": "combined", "pos": "combined_nocharlm", "lemma": "cool"}, package=None, download_method=None)
     doc = nlp(EN_DOC)
     result = '\n\n'.join(sent.tokens_string() for sent in doc.sentences)
     assert EN_DOC_COOL_LEMMAS == result