Method decode

layered_diffusion.py:236–258

(
        self,
        samples,
        images: torch.Tensor,
        frames: int,
        sd_version: str,
        sub_batch_size: int,
    )

    RETURN_TYPES = ("IMAGE",) * MAX_FRAMES

    def decode(
        self,
        samples,
        images: torch.Tensor,
        frames: int,
        sd_version: str,
        sub_batch_size: int,
    ):
        sliced_samples = copy.copy(samples)
        sliced_samples["samples"] = sliced_samples["samples"][::frames]
        return tuple(
            (
                (
                    super(LayeredDiffusionDecodeSplit, self).decode(
                        sliced_samples, imgs, sd_version, sub_batch_size
                    )[0]
                    if i == 0
                    else imgs
                )
                for i in range(frames)
                for imgs in (images[i::frames],)
            )
        ) + (None,) * (self.MAX_FRAMES - frames)


class LayerMethod(Enum):