Method ddim_sample_loop

src/diffusion/gaussian_diffusion.py:640–678

Generate samples from the model using DDIM. Same usage as p_sample_loop().

(
        self,
        model,
        shape,
        noise=None,
        clip_denoised=True,
        denoised_fn=None,
        cond_fn=None,
        model_kwargs=None,
        device=None,
        progress=False,
        eta=0.0,
        y0=None,
        mask=None,
        is_mask_t0=False,
    )

        return {"sample": mean_pred, "pred_xstart": out["pred_xstart"]}

    def ddim_sample_loop(
        self,
        model,
        shape,
        noise=None,
        clip_denoised=True,
        denoised_fn=None,
        cond_fn=None,
        model_kwargs=None,
        device=None,
        progress=False,
        eta=0.0,
        y0=None,
        mask=None,
        is_mask_t0=False,
    ):
        """
        Generate samples from the model using DDIM.

        Same usage as p_sample_loop().
        """
        final = None
        for sample in self.ddim_sample_loop_progressive(
            model,
            shape,
            noise=noise,
            clip_denoised=clip_denoised,
            denoised_fn=denoised_fn,
            cond_fn=cond_fn,
            model_kwargs=model_kwargs,
            device=device,
            progress=progress,
            eta=eta,
            y0=y0,
            mask=mask,
            is_mask_t0=is_mask_t0,
        ):
            final = sample
        return final["sample"]

    def ddim_sample_loop_progressive(
        self,