from bert4keras.tokenizers import Tokenizer,load_vocab,save_vocab

dict_path = 'vocab...

import numpy as np
import keras
from keras import layers,models
from keras.utils import plot_mode...

import tensorflow as tf
import numpy as np
import ...

import keras
import keras.backend as K
import tensorflow as tf
label_num_list = [100,20...

import numpy as np

# 转移概率，单纯用了等概率 >> b分词开始, e分词结束, m分词的中间,s仅仅单字分开
zy = {'be...

D1： John re...