ls_mlkit.diffusion.euclidean_diffuser module¶

class ls_mlkit.diffusion.euclidean_diffuser.EuclideanDiffuser(config: EuclideanDiffuserConfig, time_scheduler: DiffusionTimeScheduler, masker: MaskerInterface)[source]¶

Bases: BaseDiffuser

inpainting(x: Tensor, padding_mask: Tensor, inpainting_mask: Tensor, device, x_init_posterior: Tensor = None, inpainting_mask_key='inpainting_mask', n_repaint_steps: int = 1, return_all=False, *args: Any, **kwargs: Any) → dict[source]¶

_summary_

Parameters:

x (_type_) – _description_
padding_mask (_type_) – _description_
inpainting_mask (_type_) – _description_
device (_type_) – _description_
x_init_posterior (_type_, optional) – _description_. Defaults to None.
inpainting_mask_key (str, optional) – _description_. Defaults to “inpainting_mask”.
sapmling_condition_key (str, optional) – _description_. Defaults to “sapmling_condition”.
return_all (bool, optional) – _description_. Defaults to False.
sampling_condition (_type_, optional) – _description_. Defaults to None.

Returns:

_description_

Return type:

dict

recover_bright_region(x_known, x_t, t, padding_mask, inpainting_mask, x_prior, *args, **kwargs) → Tensor[source]¶

sampling(shape: Tuple[int, ...], device, x_init_posterior: Tensor = None, return_all=False, *args: Any, **kwargs: Any) → dict[source]¶