| 82 | |
| 83 | |
| 84 | class TemporalTimesteps(torch.nn.Module): |
| 85 | def __init__(self, num_channels: int, flip_sin_to_cos: bool, downscale_freq_shift: float, computation_device = None): |
| 86 | super().__init__() |
| 87 | self.num_channels = num_channels |
| 88 | self.flip_sin_to_cos = flip_sin_to_cos |
| 89 | self.downscale_freq_shift = downscale_freq_shift |
| 90 | self.computation_device = computation_device |
| 91 | |
| 92 | def forward(self, timesteps): |
| 93 | t_emb = get_timestep_embedding( |
| 94 | timesteps, |
| 95 | self.num_channels, |
| 96 | flip_sin_to_cos=self.flip_sin_to_cos, |
| 97 | downscale_freq_shift=self.downscale_freq_shift, |
| 98 | computation_device=self.computation_device, |
| 99 | ) |
| 100 | return t_emb |
| 101 | |
| 102 | |
| 103 | class TrainableTemporalTimesteps(torch.nn.Module): |