40 lines
1.1 KiB
Python
40 lines
1.1 KiB
Python
import sys
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import lzma
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import regex as re
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import pickle
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from tqdm import tqdm
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from collections import Counter
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def get_words(text):
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for m in re.finditer(r'[\p{L}\']+', text):
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yield m.group(0)
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def get_ngrams(iterable, n):
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ngram = []
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for item in iterable:
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ngram.append(item)
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if len(ngram) == n:
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yield tuple(ngram)
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ngram = ngram[1:]
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def get_stats():
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word_stats = Counter()
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bigram_stats = Counter()
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with lzma.open("train/in.tsv.xz", mode="rt", encoding="utf-8") as file:
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for line in tqdm(file):
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_, _, _, _, _, _, l_context, r_context = line.split("\t")
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text = f"{l_context.strip()} {r_context.strip()}".replace("\n", " ")
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word_stats.update(get_words(text))
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bigram_stats.update(get_ngrams(get_words(text), 2))
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with open("word_stats.pickle", "wb") as file:
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pickle.dump(word_stats, file, protocol=pickle.HIGHEST_PROTOCOL)
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with open("bigram_stats.pickle", "wb") as file:
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pickle.dump(bigram_stats, file, protocol=pickle.HIGHEST_PROTOCOL)
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get_stats()
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