models.py 文件源码

def __init__(self, config):
        super(Classifier, self).__init__()
        if config['pooling'] == 'mean' or config['pooling'] == 'max':
            self.encoder = BiLSTM(config)
            self.fc = nn.Linear(config['nhid'] * 2, config['nfc'])
        elif config['pooling'] == 'all':
            self.encoder = SelfAttentiveEncoder(config)
            self.fc = nn.Linear(config['nhid'] * 2 * config['attention-hops'], config['nfc'])
        else:
            raise Exception('Error when initializing Classifier')
        self.drop = nn.Dropout(config['dropout'])
        self.tanh = nn.Tanh()
        self.pred = nn.Linear(config['nfc'], config['class-number'])
        self.dictionary = config['dictionary']
#        self.init_weights()