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transformers/tests/models/cpmant/test_tokenization_cpmant.py

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+# Copyright 2022 The OpenBMB Team and The HuggingFace Inc. team.
+#
+# 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.
+
+import os
+import unittest
+
+from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
+from transformers.testing_utils import require_rjieba, tooslow
+
+from ...test_tokenization_common import TokenizerTesterMixin
+
+
+@require_rjieba
+class CPMAntTokenizationTest(TokenizerTesterMixin, unittest.TestCase):
+    from_pretrained_id = "openbmb/cpm-ant-10b"
+    tokenizer_class = CpmAntTokenizer
+    test_rust_tokenizer = False
+
+    @classmethod
+    def setUpClass(cls):
+        super().setUpClass()
+
+        vocab_tokens = [
+            "<d>",
+            "</d>",
+            "<s>",
+            "</s>",
+            "</_>",
+            "<unk>",
+            "<pad>",
+            "</n>",
+            "我",
+            "是",
+            "C",
+            "P",
+            "M",
+            "A",
+            "n",
+            "t",
+        ]
+        cls.vocab_file = os.path.join(cls.tmpdirname, VOCAB_FILES_NAMES["vocab_file"])
+        with open(cls.vocab_file, "w", encoding="utf-8") as vocab_writer:
+            vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))
+
+    @tooslow
+    def test_pre_tokenization(self):
+        tokenizer = CpmAntTokenizer.from_pretrained("openbmb/cpm-ant-10b")
+        texts = "今天天气真好！"
+        rjieba_tokens = ["今天", "天气", "真", "好", "！"]
+        tokens = tokenizer.tokenize(texts)
+        self.assertListEqual(tokens, rjieba_tokens)
+        normalized_text = "今天天气真好！"
+        input_tokens = [tokenizer.bos_token] + tokens
+
+        input_rjieba_tokens = [6, 9802, 14962, 2082, 831, 244]
+        self.assertListEqual(tokenizer.convert_tokens_to_ids(input_tokens), input_rjieba_tokens)
+
+        reconstructed_text = tokenizer.decode(input_rjieba_tokens)
+        self.assertEqual(reconstructed_text, normalized_text)