lstm_crf.py 文件源码

def __init__(self):
        self.embeddingSize = ner_tv.flags.embedding_dim
        self.distinctTagNum = ner_tv.flags.tags_num
        self.numHidden = ner_tv.flags.hidden_neural_size
        self.c2v = load_word2Vec(ner_tv.word2vec_path)
        self.words = tf.Variable(self.c2v,name = 'words')
        self.sentence_length = ner_tv.flags.sentence_length
        self.initial_learning_rate = ner_tv.flags.initial_learning_rate

        with tf.variable_scope('Softmax') as scope:
            self.W = tf.get_variable(shape=[self.numHidden *2,self.distinctTagNum],
                                     initializer=tf.truncated_normal_initializer(stddev=0.01),
                                     name='weights',
                                     regularizer= l2_regularizer(0.001))
            self.b = tf.Variable(tf.zeros([self.distinctTagNum],name='bias'))
        self.trains_params = None
        self.inp = tf.placeholder(tf.int32,shape=[None,self.sentence_length],name='input_placeholder')

        self.model_save_path = ner_tv.training_model_bi_lstm
        self.saver = tf.train.Saver()