| import torch | |
| import torch.nn as nn | |
| from .activation import GELU | |
| class FeedForward(nn.Module): | |
| ''' | |
| Feed-forward neural network with GELU activation function. | |
| - Multi-Head Self-Attention → Captures relationships between tokens. | |
| - Feedforward Neural Network (FFN) → Processes each token independently after attention. | |
| ''' | |
| def __init__(self, cfg): | |
| super().__init__() | |
| self.layers = nn.Sequential( | |
| nn.Linear(cfg["emb_dim"], 4 * cfg["emb_dim"]), | |
| GELU(), | |
| nn.Linear(4 * cfg["emb_dim"], cfg["emb_dim"]), | |
| ) | |
| def forward(self, x): | |
| return self.layers(x) |