Sentence-pair tasks handling. Using common tests on RoBERTa. Forced push to fix indentation.

pytorch_transformers/tests/tokenization_roberta_test.py

@@ -12,32 +12,45 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-from __future__ import (absolute_import, division, print_function,
-                        unicode_literals)
+from __future__ import absolute_import, division, print_function, unicode_literals
 
 import os
 import unittest
-import pytest
-import six
 
-from pytorch_transformers.tokenization_roberta import RobertaTokenizer
+from pytorch_transformers.tokenization_roberta import RobertaTokenizer, VOCAB_FILES_NAMES
+from .tokenization_tests_commons import create_and_check_tokenizer_commons, TemporaryDirectory
 
 
 class RobertaTokenizationTest(unittest.TestCase):
 
-    # @pytest.mark.slow
     def test_full_tokenizer(self):
-        tokenizer = RobertaTokenizer.from_pretrained('roberta-base')
-        self.assertListEqual(
-            tokenizer.encode('Hello world!'),
-            [0, 31414, 232, 328, 2]
-        )
-        if six.PY3:
-            self.assertListEqual(
-                tokenizer.encode('Hello world! cécé herlolip'),
-                [0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]
-            )
+        """ Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt """
+        vocab = ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n",
+                 "lo", "low", "er",
+                 "low", "lowest", "newer", "wider", "<unk>"]
+        vocab_tokens = dict(zip(vocab, range(len(vocab))))
+        special_tokens_map = {"unk_token": "<unk>"}
 
+        with TemporaryDirectory() as tmpdirname:
+            vocab_file = os.path.join(tmpdirname, VOCAB_FILES_NAMES['vocab_file'])
+            with open(vocab_file, "w") as fp:
+                [fp.write(f"{vocab} {index}\n") for index, vocab in enumerate(vocab_tokens)]
+
+            input_text = u"lower newer"
+            output_text = u"lower<unk>newer"
+
+            create_and_check_tokenizer_commons(self, input_text, output_text, RobertaTokenizer, tmpdirname, **special_tokens_map)
+
+            tokenizer = RobertaTokenizer(vocab_file, **special_tokens_map)
+            text = "lower"
+            bpe_tokens = ["low", "er"]
+            tokens = tokenizer.tokenize(text)
+            self.assertListEqual(tokens, bpe_tokens)
+
+            input_tokens = tokens + [tokenizer.unk_token]
+            input_bpe_tokens = [13, 12, 17]
+            self.assertListEqual(
+                tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
 
 
 if __name__ == '__main__':