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hub / github.com/LTH14/mar / ddim_sample_loop

Method ddim_sample_loop

diffusion/gaussian_diffusion.py:606–637  ·  view source on GitHub ↗

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,
    )

Source from the content-addressed store, hash-verified

604 return {"sample": mean_pred, "pred_xstart": out["pred_xstart"]}
605
606 def ddim_sample_loop(
607 self,
608 model,
609 shape,
610 noise=None,
611 clip_denoised=True,
612 denoised_fn=None,
613 cond_fn=None,
614 model_kwargs=None,
615 device=None,
616 progress=False,
617 eta=0.0,
618 ):
619 """
620 Generate samples from the model using DDIM.
621 Same usage as p_sample_loop().
622 """
623 final = None
624 for sample in self.ddim_sample_loop_progressive(
625 model,
626 shape,
627 noise=noise,
628 clip_denoised=clip_denoised,
629 denoised_fn=denoised_fn,
630 cond_fn=cond_fn,
631 model_kwargs=model_kwargs,
632 device=device,
633 progress=progress,
634 eta=eta,
635 ):
636 final = sample
637 return final["sample"]
638
639 def ddim_sample_loop_progressive(
640 self,

Callers

nothing calls this directly

Calls 1

Tested by

no test coverage detected