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57 lines
2.1 KiB
Python
57 lines
2.1 KiB
Python
# coding=utf-8
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# Copyright 2018 The Google AI Language Team Authors.
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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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from __future__ import absolute_import, division, print_function, unicode_literals
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import os
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import unittest
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import json
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from pytorch_pretrained_bert.tokenization_openai import OpenAIGPTTokenizer
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class OpenAIGPTTokenizationTest(unittest.TestCase):
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def test_full_tokenizer(self):
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""" Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt """
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vocab = ["l", "o", "w", "e", "r", "s", "t", "i", "d", "n",
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"w</w>", "r</w>", "t</w>",
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"lo", "low", "er</w>",
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"low</w>", "lowest</w>", "newer</w>", "wider</w>"]
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vocab_tokens = dict(zip(vocab, range(len(vocab))))
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merges = ["#version: 0.2", "l o", "lo w", "e r</w>", ""]
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with open("/tmp/openai_tokenizer_vocab_test.json", "w") as fp:
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json.dump(vocab_tokens, fp)
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vocab_file = fp.name
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with open("/tmp/openai_tokenizer_merges_test.txt", "w") as fp:
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fp.write("\n".join(merges))
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merges_file = fp.name
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tokenizer = OpenAIGPTTokenizer(vocab_file, merges_file, special_tokens=["<unk>"])
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os.remove(vocab_file)
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os.remove(merges_file)
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text = "lower"
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bpe_tokens = ["low", "er</w>"]
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tokens = tokenizer.tokenize(text)
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self.assertListEqual(tokens, bpe_tokens)
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input_tokens = tokens + ["<unk>"]
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input_bpe_tokens = [14, 15, 20]
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self.assertListEqual(
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tokenizer.convert_tokens_to_ids(input_tokens), input_bpe_tokens)
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if __name__ == '__main__':
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unittest.main()
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