(self)
| 266 | skip_small_t_freqs=self.cfg.get('skip_small_t_freqs', 0)) |
| 267 | |
| 268 | def get_dim(self) -> int: |
| 269 | if self.cfg.sampling.num_frames_per_video == 1: |
| 270 | return 1 |
| 271 | else: |
| 272 | if self.cfg.sampling.type == 'uniform': |
| 273 | return self.d + self.time_encoder.get_dim() |
| 274 | else: |
| 275 | return (self.d + self.time_encoder.get_dim()) * (self.cfg.sampling.num_frames_per_video - 1) |
| 276 | |
| 277 | def forward(self, t: torch.Tensor) -> torch.Tensor: |
| 278 | misc.assert_shape(t, [None, self.cfg.sampling.num_frames_per_video]) |