45 lines
1.1 KiB
Python
45 lines
1.1 KiB
Python
#!/usr/bin/env python
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# coding: utf-8
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# In[9]:
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import regex as re
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from tqdm.notebook import tqdm
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def _clean(text):
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text = text.replace('-\\n', '').replace('\\n', ' ').replace('\\t', ' ')#.replace('<s>','s')
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while ' ' in text:
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text = text.replace(' ',' ')
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return re.sub(r'\p{P}', '', text)
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def clean(text):
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text = text.replace('-\\n', '').replace('\\n', ' ').replace('\\t', ' ')
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text = re.sub(r'\n', ' ', text)
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text = re.sub(r'(?<=\w)[,-](?=\w)', '', text)
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text = re.sub(r'\s+', ' ', text)
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text = re.sub(r'\p{P}', '', text)
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text = text.strip()
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return text
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def generate_file(input_path, expected_path, output_path):
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with open(input_path, encoding='utf8') as input_file, open(expected_path, encoding='utf8') as expected_file, open(output_path, 'w', encoding='utf-8') as output_file:
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for line, word in tqdm(zip(input_file, expected_file), total=432022):
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columns = line.split('\t')
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prefix = clean(columns[6])
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suffix = clean(columns[7])
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train_line = f"{prefix.strip()} {word.strip()} {suffix.strip()}\n"
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output_file.write(train_line)
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generate_file('train/in.tsv', 'train/expected.tsv', 'train/train.txt')
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# In[ ]:
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