| 8 | |
| 9 | |
| 10 | class Classifier(nn.Module): |
| 11 | def __init__(self, hidden_size): |
| 12 | super(Classifier, self).__init__() |
| 13 | self.linear1 = nn.Linear(hidden_size, 1) |
| 14 | self.sigmoid = nn.Sigmoid() |
| 15 | |
| 16 | def forward(self, x, mask_cls): |
| 17 | h = self.linear1(x).squeeze(-1) |
| 18 | sent_scores = self.sigmoid(h) * mask_cls.float() |
| 19 | return sent_scores |
| 20 | |
| 21 | |
| 22 | class PositionalEncoding(nn.Module): |