(self, config)
| 19 | class Encoder(nn.Module): |
| 20 | |
| 21 | def __init__(self, config): |
| 22 | super(Encoder, self).__init__() |
| 23 | self.config = config |
| 24 | input_size = config.d_proj if config.projection else config.d_embed |
| 25 | dropout = 0 if config.n_layers == 1 else config.dp_ratio |
| 26 | self.rnn = nn.LSTM(input_size=input_size, hidden_size=config.d_hidden, |
| 27 | num_layers=config.n_layers, dropout=dropout, |
| 28 | bidirectional=config.birnn) |
| 29 | |
| 30 | def forward(self, inputs): |
| 31 | batch_size = inputs.size()[1] |