layers.py 文件源码

def __init__(self, input_size, hidden_size, num_layers,
                 dropout_rate=0, dropout_output=False, rnn_type=nn.LSTM,
                 concat_layers=False, padding=False):
        super(StackedBRNN, self).__init__()
        self.padding = padding
        self.dropout_output = dropout_output
        self.dropout_rate = dropout_rate
        self.num_layers = num_layers
        self.concat_layers = concat_layers
        self.rnns = nn.ModuleList()
        for i in range(num_layers):
            input_size = input_size if i == 0 else 2 * hidden_size
            #self.rnns.append(rnn_type(input_size, hidden_size,
            #                          num_layers=1,
            #                          bidirectional=True))
            self.rnns.append(MF.SRUCell(input_size, hidden_size,
                                      dropout=dropout_rate,
                                      rnn_dropout=dropout_rate,
                                      use_tanh=1,
                                      bidirectional=True))