| 5 | |
| 6 | |
| 7 | class PositionwiseFeedForward(nn.Module): |
| 8 | def __init__(self, d_in, d_hid, dropout=0.1): |
| 9 | super().__init__() |
| 10 | self.w_1 = nn.Conv1d(d_in, d_hid, 1) |
| 11 | self.w_2 = nn.Conv1d(d_hid, d_in, 1) |
| 12 | self.layer_norm = nn.LayerNorm(d_in) |
| 13 | self.dropout = nn.Dropout(dropout) |
| 14 | |
| 15 | def forward(self, x): |
| 16 | residual = x |
| 17 | output = x.transpose(1, 2) |
| 18 | output = self.w_2(F.relu(self.w_1(output))) |
| 19 | output = output.transpose(1, 2) |
| 20 | output = self.dropout(output) |
| 21 | output = self.layer_norm(output + residual) |
| 22 | return output |
| 23 | |
| 24 | |
| 25 | |