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added intermediate latent during DDIM inversion for content querying #25

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added intermediate latent during DDIM inversion for content querying #25

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460d108
added intermediate latent during DDIM inversion for content querying
Jun 28, 2023
512033c
Merge branch 'main' of https://github.com/Ragzz258/MasaCtrl into main
Jun 28, 2023
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8 changes: 7 additions & 1 deletion masactrl_w_adapter/ddim.py
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Original file line number Diff line number Diff line change
Expand Up @@ -71,6 +71,7 @@ def sample(self,
corrector_kwargs=None,
verbose=True,
x_T=None,
ld = None,
log_every_t=100,
unconditional_guidance_scale=1.,
unconditional_conditioning=None,
Expand Down Expand Up @@ -114,6 +115,7 @@ def sample(self,
append_to_context=append_to_context,
cond_tau=cond_tau,
style_cond_tau=style_cond_tau,
ld = ld,
)
return samples, intermediates

Expand All @@ -124,7 +126,7 @@ def ddim_sampling(self, cond, shape,
mask=None, x0=None, img_callback=None, log_every_t=100,
temperature=1., noise_dropout=0., score_corrector=None, corrector_kwargs=None,
unconditional_guidance_scale=1., unconditional_conditioning=None, features_adapter=None,
append_to_context=None, cond_tau=0.4, style_cond_tau=1.0):
append_to_context=None, cond_tau=0.4, style_cond_tau=1.0,ld = None):
device = self.model.betas.device
b = shape[0]
if x_T is None:
Expand All @@ -148,6 +150,10 @@ def ddim_sampling(self, cond, shape,
for i, step in enumerate(iterator):
index = total_steps - i - 1
ts = torch.full((b,), step, device=device, dtype=torch.long)
if ld != None:
latent_ref = ld['x_inter'][index]
_, latents_cur =img.chunk(2)
img = torch.cat([latent_ref,latents_cur])

if mask is not None:
assert x0 is not None
Expand Down
1 change: 1 addition & 0 deletions masactrl_w_adapter/masactrl_w_adapter.py
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Expand Up @@ -191,6 +191,7 @@ def main():
verbose=False,
unconditional_guidance_scale=opt.scale,
unconditional_conditioning=uc,
ld = latents_dict,
x_T=start_code,
features_adapter=adapter_features,
append_to_context=append_to_context,
Expand Down