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hub / github.com/openai/point-e / ddim_sample_loop

Method ddim_sample_loop

point_e/diffusion/gaussian_diffusion.py:638–672  ·  view source on GitHub ↗

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

(
        self,
        model,
        shape,
        noise=None,
        clip_denoised=False,
        denoised_fn=None,
        cond_fn=None,
        model_kwargs=None,
        device=None,
        progress=False,
        eta=0.0,
        temp=1.0,
    )

Source from the content-addressed store, hash-verified

636 return {"sample": mean_pred, "pred_xstart": out["pred_xstart"]}
637
638 def ddim_sample_loop(
639 self,
640 model,
641 shape,
642 noise=None,
643 clip_denoised=False,
644 denoised_fn=None,
645 cond_fn=None,
646 model_kwargs=None,
647 device=None,
648 progress=False,
649 eta=0.0,
650 temp=1.0,
651 ):
652 """
653 Generate samples from the model using DDIM.
654
655 Same usage as p_sample_loop().
656 """
657 final = None
658 for sample in self.ddim_sample_loop_progressive(
659 model,
660 shape,
661 noise=noise,
662 clip_denoised=clip_denoised,
663 denoised_fn=denoised_fn,
664 cond_fn=cond_fn,
665 model_kwargs=model_kwargs,
666 device=device,
667 progress=progress,
668 eta=eta,
669 temp=temp,
670 ):
671 final = sample
672 return final["sample"]
673
674 def ddim_sample_loop_progressive(
675 self,

Callers

nothing calls this directly

Calls 1

Tested by

no test coverage detected