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import copy |
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import random |
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import numpy as np |
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from openrec.preprocess.ctc_label_encode import BaseRecLabelEncode |
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class SMTRLabelEncode(BaseRecLabelEncode): |
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"""Convert between text-label and text-index.""" |
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BOS = '<s>' |
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EOS = '</s>' |
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IN_F = '<INF>' |
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IN_B = '<INB>' |
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PAD = '<pad>' |
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def __init__(self, |
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max_text_length, |
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character_dict_path=None, |
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use_space_char=False, |
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sub_str_len=5, |
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**kwargs): |
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super(SMTRLabelEncode, |
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self).__init__(max_text_length, character_dict_path, |
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use_space_char) |
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self.substr_len = sub_str_len |
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self.rang_subs = [i for i in range(1, self.substr_len + 1)] |
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self.idx_char = [i for i in range(1, self.num_character - 5)] |
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def __call__(self, data): |
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text = data['label'] |
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text = self.encode(text) |
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if text is None: |
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return None |
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if len(text) > self.max_text_len: |
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return None |
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data['length'] = np.array(len(text)) |
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text_in = [self.dict[self.IN_F]] * (self.substr_len) + text + [ |
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self.dict[self.IN_B] |
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] * (self.substr_len) |
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sub_string_list_pre = [] |
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next_label_pre = [] |
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sub_string_list = [] |
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next_label = [] |
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for i in range(self.substr_len, len(text_in) - self.substr_len): |
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sub_string_list.append(text_in[i - self.substr_len:i]) |
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next_label.append(text_in[i]) |
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if self.substr_len - i == 0: |
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sub_string_list_pre.append(text_in[-i:]) |
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else: |
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sub_string_list_pre.append(text_in[-i:self.substr_len - i]) |
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next_label_pre.append(text_in[-(i + 1)]) |
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sub_string_list.append( |
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[self.dict[self.IN_F]] * |
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(self.substr_len - len(text[-self.substr_len:])) + |
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text[-self.substr_len:]) |
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next_label.append(self.dict[self.EOS]) |
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sub_string_list_pre.append( |
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text[:self.substr_len] + [self.dict[self.IN_B]] * |
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(self.substr_len - len(text[:self.substr_len]))) |
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next_label_pre.append(self.dict[self.EOS]) |
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for sstr, l in zip(sub_string_list[self.substr_len:], |
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next_label[self.substr_len:]): |
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id_shu = np.random.choice(self.rang_subs, 2) |
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sstr1 = copy.deepcopy(sstr) |
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sstr1[id_shu[0] - 1] = random.randint(1, self.num_character - 5) |
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if sstr1 not in sub_string_list: |
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sub_string_list.append(sstr1) |
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next_label.append(l) |
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sstr[id_shu[1] - 1] = random.randint(1, self.num_character - 5) |
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for sstr, l in zip(sub_string_list_pre[self.substr_len:], |
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next_label_pre[self.substr_len:]): |
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id_shu = np.random.choice(self.rang_subs, 2) |
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sstr1 = copy.deepcopy(sstr) |
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sstr1[id_shu[0] - 1] = random.randint(1, self.num_character - 5) |
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if sstr1 not in sub_string_list_pre: |
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sub_string_list_pre.append(sstr1) |
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next_label_pre.append(l) |
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sstr[id_shu[1] - 1] = random.randint(1, self.num_character - 5) |
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data['length_subs'] = np.array(len(sub_string_list)) |
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sub_string_list = sub_string_list + [ |
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[self.dict[self.PAD]] * self.substr_len |
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] * ((self.max_text_len * 2) + 2 - len(sub_string_list)) |
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next_label = next_label + [self.dict[self.PAD]] * ( |
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(self.max_text_len * 2) + 2 - len(next_label)) |
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data['label_subs'] = np.array(sub_string_list) |
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data['label_next'] = np.array(next_label) |
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data['length_subs_pre'] = np.array(len(sub_string_list_pre)) |
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sub_string_list_pre = sub_string_list_pre + [ |
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[self.dict[self.PAD]] * self.substr_len |
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] * ((self.max_text_len * 2) + 2 - len(sub_string_list_pre)) |
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next_label_pre = next_label_pre + [self.dict[self.PAD]] * ( |
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(self.max_text_len * 2) + 2 - len(next_label_pre)) |
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data['label_subs_pre'] = np.array(sub_string_list_pre) |
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data['label_next_pre'] = np.array(next_label_pre) |
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text = [self.dict[self.BOS]] + text + [self.dict[self.EOS]] |
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text = text + [self.dict[self.PAD] |
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] * (self.max_text_len + 2 - len(text)) |
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data['label'] = np.array(text) |
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return data |
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def add_special_char(self, dict_character): |
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dict_character = [self.EOS] + dict_character + [ |
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self.BOS, self.IN_F, self.IN_B, self.PAD |
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] |
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self.num_character = len(dict_character) |
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return dict_character |
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