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Method cond_fn

gen_img_diffusers.py:1586–1624  ·  view source on GitHub ↗
(
        self,
        latents,
        timestep,
        index,
        text_embeddings,
        noise_pred_original,
        guide_embeddings_clip,
        clip_guidance_scale,
        num_cutouts,
        use_cutouts=True,
    )

Source from the content-addressed store, hash-verified

1584
1585 # バッチを分解して1件ずつ処理する
1586 def cond_fn(
1587 self,
1588 latents,
1589 timestep,
1590 index,
1591 text_embeddings,
1592 noise_pred_original,
1593 guide_embeddings_clip,
1594 clip_guidance_scale,
1595 num_cutouts,
1596 use_cutouts=True,
1597 ):
1598 if len(latents) == 1:
1599 return self.cond_fn1(
1600 latents,
1601 timestep,
1602 index,
1603 text_embeddings,
1604 noise_pred_original,
1605 guide_embeddings_clip,
1606 clip_guidance_scale,
1607 num_cutouts,
1608 use_cutouts,
1609 )
1610
1611 noise_pred = []
1612 cond_latents = []
1613 for i in range(len(latents)):
1614 lat1 = latents[i].unsqueeze(0)
1615 tem1 = text_embeddings[i].unsqueeze(0)
1616 npo1 = noise_pred_original[i].unsqueeze(0)
1617 gem1 = guide_embeddings_clip[i].unsqueeze(0)
1618 npr1, cla1 = self.cond_fn1(lat1, timestep, index, tem1, npo1, gem1, clip_guidance_scale, num_cutouts, use_cutouts)
1619 noise_pred.append(npr1)
1620 cond_latents.append(cla1)
1621
1622 noise_pred = torch.cat(noise_pred)
1623 cond_latents = torch.cat(cond_latents)
1624 return noise_pred, cond_latents
1625
1626 @torch.enable_grad()
1627 def cond_fn1(

Callers 1

__call__Method · 0.95

Calls 1

cond_fn1Method · 0.95

Tested by

no test coverage detected