Test correct tokenizers after default switch (#3003)

* Renamed file generate by tokenizers when calling save_pretrained to match python.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added save_vocabulary tests.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Remove python quick and dirty fix for clean Rust impl.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Bump tokenizers dependency to 0.5.1

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* TransfoXLTokenizerFast uses a json vocabulary file + warning about incompatibility between Python and Rust

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Added some save_pretrained / from_pretrained unittests.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Update tokenizers to 0.5.2

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Quality and format.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* flake8

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

* Making sure there is really a bug in unittest

* Fix TransfoXL constructor vocab_file / pretrained_vocab_file mixin.

Signed-off-by: Morgan Funtowicz <morgan@huggingface.co>

docs/source/conf.py

@@ -26,7 +26,7 @@ author = u'huggingface'
 # The short X.Y version
 version = u''
 # The full version, including alpha/beta/rc tags
-release = u'2.5.0'
+release = u'2.5.1'
 
 
 # -- General configuration ---------------------------------------------------

setup.py

@@ -79,7 +79,7 @@ extras["dev"] = extras["testing"] + extras["quality"] + ["mecab-python3", "sciki
 
 setup(
     name="transformers",
-    version="2.5.0",
+    version="2.5.1",
     author="Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Sam Shleifer, Google AI Language Team Authors, Open AI team Authors, Facebook AI Authors, Carnegie Mellon University Authors",
     author_email="thomas@huggingface.co",
     description="State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch",

src/transformers/__init__.py

@@ -2,7 +2,7 @@
 # There's no way to ignore "F401 '...' imported but unused" warnings in this
 # module, but to preserve other warnings. So, don't check this module at all.
 
-__version__ = "2.5.0"
+__version__ = "2.5.1"
 
 # Work around to update TensorFlow's absl.logging threshold which alters the
 # default Python logging output behavior when present.

src/transformers/modeling_transfo_xl.py

@@ -645,7 +645,7 @@ class TransfoXLModel(TransfoXLPreTrainedModel):
         else:
             return None
 
-    def _update_mems(self, hids, mems, qlen, mlen):
+    def _update_mems(self, hids, mems, mlen, qlen):
         # does not deal with None
         if mems is None:
             return None

src/transformers/tokenization_auto.py

@@ -157,7 +157,7 @@ class AutoTokenizer:
                 A dictionary of proxy servers to use by protocol or endpoint, e.g.: {'http': 'foo.bar:3128', 'http://hostname': 'foo.bar:4012'}.
                 The proxies are used on each request.
 
-            use_fast: (`optional`) boolean, default True:
+            use_fast: (`optional`) boolean, default False:
                 Indicate if transformers should try to load the fast version of the tokenizer (True) or use the Python one (False).
 
             inputs: (`optional`) positional arguments: will be passed to the Tokenizer ``__init__`` method.
@@ -183,7 +183,7 @@ class AutoTokenizer:
         if "bert-base-japanese" in pretrained_model_name_or_path:
             return BertJapaneseTokenizer.from_pretrained(pretrained_model_name_or_path, *inputs, **kwargs)
 
-        use_fast = kwargs.pop("use_fast", True)
+        use_fast = kwargs.pop("use_fast", False)
         for config_class, (tokenizer_class_py, tokenizer_class_fast) in TOKENIZER_MAPPING.items():
             if isinstance(config, config_class):
                 if tokenizer_class_fast and use_fast:

tests/test_tokenization_auto.py

@@ -101,5 +101,5 @@ class AutoTokenizerTest(unittest.TestCase):
                             self.assertFalse(issubclass(child_model_fast, parent_model_fast))
 
     def test_from_pretrained_use_fast_toggle(self):
-        self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"), BertTokenizerFast)
-        self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased", use_fast=False), BertTokenizer)
+        self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased"), BertTokenizer)
+        self.assertIsInstance(AutoTokenizer.from_pretrained("bert-base-cased", use_fast=True), BertTokenizerFast)