init

transformers/tests/models/distilbert/test_tokenization_distilbert.py

@@ -0,0 +1,42 @@
+# Copyright 2020 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# 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 transformers import DistilBertTokenizer, DistilBertTokenizerFast
+from transformers.testing_utils import require_tokenizers, slow
+
+from ..bert import test_tokenization_bert
+
+
+@require_tokenizers
+class DistilBertTokenizationTest(test_tokenization_bert.BertTokenizationTest):
+    tokenizer_class = DistilBertTokenizer
+    rust_tokenizer_class = DistilBertTokenizerFast
+    test_rust_tokenizer = True
+    from_pretrained_id = "distilbert/distilbert-base-uncased"
+
+    @slow
+    def test_sequence_builders(self):
+        tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased")
+
+        text = tokenizer.encode("sequence builders", add_special_tokens=False)
+        text_2 = tokenizer.encode("multi-sequence build", add_special_tokens=False)
+
+        encoded_sentence = tokenizer.build_inputs_with_special_tokens(text)
+        encoded_pair = tokenizer.build_inputs_with_special_tokens(text, text_2)
+
+        assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
+        assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + text_2 + [
+            tokenizer.sep_token_id
+        ]