(self, use_timesteps, **kwargs)
| 70 | """ |
| 71 | |
| 72 | def __init__(self, use_timesteps, **kwargs): |
| 73 | self.use_timesteps = set(use_timesteps) |
| 74 | self.timestep_map = [] |
| 75 | self.original_num_steps = len(kwargs["betas"]) |
| 76 | |
| 77 | base_diffusion = GaussianDiffusion(**kwargs) # pylint: disable=missing-kwoa |
| 78 | last_alpha_cumprod = 1.0 |
| 79 | new_betas = [] |
| 80 | for i, alpha_cumprod in enumerate(base_diffusion.alphas_cumprod): |
| 81 | if i in self.use_timesteps: |
| 82 | new_betas.append(1 - alpha_cumprod / last_alpha_cumprod) |
| 83 | last_alpha_cumprod = alpha_cumprod |
| 84 | self.timestep_map.append(i) |
| 85 | kwargs["betas"] = np.array(new_betas) |
| 86 | super().__init__(**kwargs) |
| 87 | |
| 88 | def p_mean_variance( |
| 89 | self, model, *args, **kwargs |
nothing calls this directly
no test coverage detected