mirror of https://github.com/YifanXu74/MQ-Det.git
101 lines
3.2 KiB
Python
101 lines
3.2 KiB
Python
"""
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Language-related data loading helper functions and class wrappers.
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"""
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import re
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import torch
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import codecs
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UNK_TOKEN = '<unk>'
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PAD_TOKEN = '<pad>'
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END_TOKEN = '<eos>'
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SENTENCE_SPLIT_REGEX = re.compile(r'(\W+)')
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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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def __getitem__(self, a):
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if isinstance(a, int):
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return self.idx2word[a]
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elif isinstance(a, list):
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return [self.idx2word[x] for x in a]
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elif isinstance(a, str):
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return self.word2idx[a]
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else:
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raise TypeError("Query word/index argument must be int or str")
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def __contains__(self, word):
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return word in self.word2idx
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class Corpus(object):
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def __init__(self):
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self.dictionary = Dictionary()
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def set_max_len(self, value):
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self.max_len = value
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def load_file(self, filename):
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with codecs.open(filename, 'r', 'utf-8') as f:
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for line in f:
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line = line.strip()
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self.add_to_corpus(line)
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self.dictionary.add_word(UNK_TOKEN)
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self.dictionary.add_word(PAD_TOKEN)
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def add_to_corpus(self, line):
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"""Tokenizes a text line."""
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# Add words to the dictionary
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words = line.split()
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# tokens = len(words)
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for word in words:
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word = word.lower()
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self.dictionary.add_word(word)
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def tokenize(self, line, max_len=20):
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# Tokenize line contents
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words = SENTENCE_SPLIT_REGEX.split(line.strip())
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# words = [w.lower() for w in words if len(w) > 0]
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words = [w.lower() for w in words if (len(w) > 0 and w != ' ')] ## do not include space as a token
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if words[-1] == '.':
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words = words[:-1]
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if max_len > 0:
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if len(words) > max_len:
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words = words[:max_len]
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elif len(words) < max_len:
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# words = [PAD_TOKEN] * (max_len - len(words)) + words
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words = words + [END_TOKEN] + [PAD_TOKEN] * (max_len - len(words) - 1)
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tokens = len(words) ## for end token
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ids = torch.LongTensor(tokens)
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token = 0
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for word in words:
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if word not in self.dictionary:
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word = UNK_TOKEN
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# print(word, type(word), word.encode('ascii','ignore').decode('ascii'), type(word.encode('ascii','ignore').decode('ascii')))
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if type(word) != type('a'):
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print(word, type(word), word.encode('ascii', 'ignore').decode('ascii'),
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type(word.encode('ascii', 'ignore').decode('ascii')))
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word = word.encode('ascii', 'ignore').decode('ascii')
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ids[token] = self.dictionary[word]
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token += 1
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# ids[token] = self.dictionary[END_TOKEN]
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return ids
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def __len__(self):
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return len(self.dictionary)
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