(self, use_timesteps, **kwargs)
| 1247 | """ |
| 1248 | |
| 1249 | def __init__(self, use_timesteps, **kwargs): |
| 1250 | self.use_timesteps = set(use_timesteps) |
| 1251 | self.timestep_map = [] |
| 1252 | self.original_num_steps = len(kwargs["betas"]) |
| 1253 | |
| 1254 | base_diffusion = GaussianDiffusion(**kwargs) # pylint: disable=missing-kwoa |
| 1255 | last_alpha_cumprod = 1.0 |
| 1256 | new_betas = [] |
| 1257 | for i, alpha_cumprod in enumerate(base_diffusion.alphas_cumprod): |
| 1258 | if i in self.use_timesteps: |
| 1259 | new_betas.append(1 - alpha_cumprod / last_alpha_cumprod) |
| 1260 | last_alpha_cumprod = alpha_cumprod |
| 1261 | self.timestep_map.append(i) |
| 1262 | kwargs["betas"] = np.array(new_betas) |
| 1263 | super().__init__(**kwargs) |
| 1264 | |
| 1265 | def p_mean_variance(self, model, *args, **kwargs): |
| 1266 | return super().p_mean_variance(self._wrap_model(model), *args, |
nothing calls this directly
no test coverage detected