(self, x: torch.Tensor)
| 61 | self.norm2 = nn.LayerNorm(hidden_size) |
| 62 | |
| 63 | def forward(self, x: torch.Tensor) -> torch.Tensor: |
| 64 | x = self.norm1(x + self.attention(x)) |
| 65 | x = self.norm2(x + self.mlp(x)) |
| 66 | return x |
| 67 | |
| 68 | |
| 69 | class BertModel(nn.Module): |
nothing calls this directly
no outgoing calls
no test coverage detected