wehub-resource-sync
54 lines
2.0 KiB
Python
54 lines
2.0 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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# Copyright 2020 The HuggingFace Team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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from paddlenlp.transformers import RemBertTokenizer
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from ..test_tokenizer_common import TokenizerTesterMixin
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class TestTokenizationRemBert(TokenizerTesterMixin, unittest.TestCase):
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tokenizer_class = RemBertTokenizer
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test_offsets = False
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def get_tokenizer(self, **kwargs):
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return self.tokenizer_class.from_pretrained("rembert", **kwargs)
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def get_clean_sequence(self, tokenizer, with_prefix_space=False, max_length=20, min_length=5):
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output_text = "unwanted, running,running."
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if with_prefix_space:
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output_text = " " + output_text
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output_ids = tokenizer.encode(output_text, return_token_type_ids=None, add_special_tokens=False)["input_ids"]
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return output_text, output_ids
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def test_consecutive_unk_string(self):
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tokenizers = self.get_tokenizers(fast=True, do_lower_case=True)
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for tokenizer in tokenizers:
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tokens = [tokenizer.unk_token for _ in range(2)]
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string = tokenizer.convert_tokens_to_string(tokens)
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encoding = tokenizer(
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text=string,
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truncation=True,
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return_offsets_mapping=True,
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)
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self.assertEqual(len(encoding["input_ids"]), 4)
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self.assertEqual(len(encoding["offset_mapping"]), 2)
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def test_pretokenized_inputs(self):
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self.skipTest("not implement yet")
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