(self, x)
| 35 | self.dim = dim |
| 36 | |
| 37 | def forward(self, x): |
| 38 | device = x.device |
| 39 | half_dim = self.dim // 2 |
| 40 | emb = math.log(10000) / (half_dim - 1) |
| 41 | emb = torch.exp(torch.arange(half_dim, device=device) * -emb) |
| 42 | emb = x[:, None] * emb[None, :] |
| 43 | emb = torch.cat((emb.sin(), emb.cos()), dim=-1) |
| 44 | return emb |
| 45 | |
| 46 | |
| 47 | def Conv1d(*args, **kwargs): |
nothing calls this directly
no outgoing calls
no test coverage detected