50 lines
1.4 KiB
Python
50 lines
1.4 KiB
Python
import os
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import torch
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class Dictionary(object):
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def __init__(self):
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self.word2idx = {}
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self.idx2word = []
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def add_word(self, word):
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if word not in self.word2idx:
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self.idx2word.append(word)
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self.word2idx[word] = len(self.idx2word) - 1
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return self.word2idx[word]
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def __len__(self):
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return len(self.idx2word)
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class Corpus(object):
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def __init__(self, path):
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self.dictionary = Dictionary()
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self.train = self.tokenize(os.path.join(path, 'train.txt'))
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self.valid = self.tokenize(os.path.join(path, 'valid.txt'))
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self.test = self.tokenize(os.path.join(path, 'test.txt'))
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def tokenize(self, path):
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"""Tokenizes a text file."""
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assert os.path.exists(path)
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# Add words to the dictionary
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with open(path, 'r') as f:
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tokens = 0
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for line in f:
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words = line.split() + ['<eos>']
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tokens += len(words)
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for word in words:
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self.dictionary.add_word(word)
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# Tokenize file content
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with open(path, 'r') as f:
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ids = torch.LongTensor(tokens)
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token = 0
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for line in f:
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words = line.split() + ['<eos>']
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for word in words:
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ids[token] = self.dictionary.word2idx[word]
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token += 1
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return ids
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