Transformers, Pytorch, Machine Learning, Deep Dives, Data Science.
= nn.Linear(d_ff, d_model) self.relu = nn.ReLU() def forward(self, x): return self.fc2(self.relu(self.fc1(x))) Putting the pieces together, we get an Encoder module ! class EncoderBlock(nn.Module): def __init__(self, n_dim: int, dropout: float, n_heads: int): super(EncoderBlock, self).__init__()