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