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