ස්ථාවර විසරණය සඳහා නියැදි ඇල්ගොරිතම

18from typing import Optional, List
19
20import torch
21
22from labml_nn.diffusion.stable_diffusion.latent_diffusion import LatentDiffusion

25class DiffusionSampler:

29    model: LatentDiffusion

31    def __init__(self, model: LatentDiffusion):

35        super().__init__()

37        self.model = model

39        self.n_steps = model.n_steps

41    def get_eps(self, x: torch.Tensor, t: torch.Tensor, c: torch.Tensor, *,
42                uncond_scale: float, uncond_cond: Optional[torch.Tensor]):

55        if uncond_cond is None or uncond_scale == 1.:
56            return self.model(x, t, c)

59        x_in = torch.cat([x] * 2)
60        t_in = torch.cat([t] * 2)

62        c_in = torch.cat([uncond_cond, c])

64        e_t_uncond, e_t_cond = self.model(x_in, t_in, c_in).chunk(2)

67        e_t = e_t_uncond + uncond_scale * (e_t_cond - e_t_uncond)

70        return e_t

72    def sample(self,
73               shape: List[int],
74               cond: torch.Tensor,
75               repeat_noise: bool = False,
76               temperature: float = 1.,
77               x_last: Optional[torch.Tensor] = None,
78               uncond_scale: float = 1.,
79               uncond_cond: Optional[torch.Tensor] = None,
80               skip_steps: int = 0,
81               ):

95        raise NotImplementedError()

97    def paint(self, x: torch.Tensor, cond: torch.Tensor, t_start: int, *,
98              orig: Optional[torch.Tensor] = None,
99              mask: Optional[torch.Tensor] = None, orig_noise: Optional[torch.Tensor] = None,
100              uncond_scale: float = 1.,
101              uncond_cond: Optional[torch.Tensor] = None,
102              ):

116        raise NotImplementedError()

118    def q_sample(self, x0: torch.Tensor, index: int, noise: Optional[torch.Tensor] = None):

126        raise NotImplementedError()