| 1 | from dataclasses import replace |
| 2 | from typing import Protocol |
| 3 | |
| 4 | import torch |
| 5 | |
| 6 | from ltx_core.types import LatentState |
| 7 | |
| 8 | |
| 9 | class Noiser(Protocol): |
| 10 | """Protocol for adding noise to a latent state during diffusion.""" |
| 11 | |
| 12 | def __call__(self, latent_state: LatentState, noise_scale: float) -> LatentState: ... |
| 13 | |
| 14 | |
| 15 | class GaussianNoiser(Noiser): |
| 16 | """Adds Gaussian noise to a latent state, scaled by the denoise mask.""" |
| 17 | |
| 18 | def __init__(self, generator: torch.Generator): |
| 19 | super().__init__() |
| 20 | |
| 21 | self.generator = generator |
| 22 | |
| 23 | def __call__(self, latent_state: LatentState, noise_scale: float = 1.0) -> LatentState: |
| 24 | noise = torch.randn( |
| 25 | *latent_state.latent.shape, |
| 26 | device=latent_state.latent.device, |
| 27 | dtype=latent_state.latent.dtype, |
| 28 | generator=self.generator, |
| 29 | ) |
| 30 | scaled_mask = latent_state.denoise_mask * noise_scale |
| 31 | latent = noise * scaled_mask + latent_state.latent * (1 - scaled_mask) |
| 32 | return replace( |
| 33 | latent_state, |
| 34 | latent=latent.to(latent_state.latent.dtype), |
| 35 | ) |
| 36 |