wehub-resource-sync
58 lines
1.9 KiB
Python
58 lines
1.9 KiB
Python
# Copyright (c) 2023 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.chatglm_v2.tokenizer import ChatGLMv2Tokenizer
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from paddlenlp.transformers.tokenizer_utils import PretrainedTokenizer
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VOCAB_FILES_NAMES = {
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"vocab_file": "vocab.json",
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}
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class ChatGLMv2TokenizationTest(unittest.TestCase):
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tokenizer_class = ChatGLMv2Tokenizer
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test_decode_token = True
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def get_tokenizer(self, **kwargs) -> PretrainedTokenizer:
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tokenizer = ChatGLMv2Tokenizer.from_pretrained("THUDM/chatglm2-6b", **kwargs)
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return tokenizer
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def test_encode_special_tokens(self):
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tokenizer = self.get_tokenizer()
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query = "[gMASK]</s>"
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tokens = tokenizer.tokenize(query)
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self.assertEqual(len(tokens), 2)
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outputs = tokenizer.encode(query, add_special_tokens=False)
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self.assertEqual(len(outputs["input_ids"]), 2)
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class ChatGLMv3TokenizationTest(unittest.TestCase):
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tokenizer_class = ChatGLMv2Tokenizer
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def get_tokenizer(self, **kwargs) -> PretrainedTokenizer:
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return ChatGLMv2Tokenizer.from_pretrained("THUDM/chatglm3-6b", **kwargs)
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def test_encode_special_tokens(self):
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tokenizer = self.get_tokenizer()
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query = "[gMASK]<|user|><|assistant|></s>"
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tokens = tokenizer.tokenize(query)
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self.assertEqual(len(tokens), 4)
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