| import torch.nn as nn | |
| class FeedForward(nn.Module): | |
| def __init__( | |
| self, | |
| d_model, | |
| dropout=0.1 | |
| ): | |
| super().__init__() | |
| self.network = nn.Sequential( | |
| nn.Linear( | |
| d_model, | |
| 4 * d_model | |
| ), | |
| nn.GELU(), | |
| nn.Linear( | |
| 4 * d_model, | |
| d_model | |
| ), | |
| nn.Dropout( | |
| dropout | |
| ) | |
| ) | |
| def forward(self, x): | |
| return self.network(x) |