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Fix logspam and live previews

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This commit is contained in:
space-nuko
2023-02-10 04:47:08 -08:00
parent 1253199889
commit 21880eb9e5
3 changed files with 41 additions and 31 deletions
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20
modules/models/diffusion/uni_pc/sampler.py
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@@ -19,9 +19,10 @@ class UniPCSampler(object):
attr = attr.to(torch.device("cuda"))
setattr(self, name, attr)
def set_hooks(self, before, after):
self.before_sample = before
self.after_sample = after
def set_hooks(self, before_sample, after_sample, after_update):
self.before_sample = before_sample
self.after_sample = after_sample
self.after_update = after_update
@torch.no_grad()
def sample(self,
@@ -50,9 +51,17 @@ class UniPCSampler(object):
):
if conditioning is not None:
if isinstance(conditioning, dict):
cbs = conditioning[list(conditioning.keys())[0]].shape[0]
ctmp = conditioning[list(conditioning.keys())[0]]
while isinstance(ctmp, list): ctmp = ctmp[0]
cbs = ctmp.shape[0]
if cbs != batch_size:
print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
elif isinstance(conditioning, list):
for ctmp in conditioning:
if ctmp.shape[0] != batch_size:
print(f"Warning: Got {cbs} conditionings but batch-size is {batch_size}")
else:
if conditioning.shape[0] != batch_size:
print(f"Warning: Got {conditioning.shape[0]} conditionings but batch-size is {batch_size}")
@@ -60,6 +69,7 @@ class UniPCSampler(object):
# sampling
C, H, W = shape
size = (batch_size, C, H, W)
print(f'Data shape for UniPC sampling is {size}, eta {eta}')
device = self.model.betas.device
if x_T is None:
@@ -79,7 +89,7 @@ class UniPCSampler(object):
guidance_scale=unconditional_guidance_scale,
)
uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=False, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=self.before_sample, after_sample=self.after_sample)
uni_pc = UniPC(model_fn, ns, predict_x0=True, thresholding=False, condition=conditioning, unconditional_condition=unconditional_conditioning, before_sample=self.before_sample, after_sample=self.after_sample, after_update=self.after_update)
x = uni_pc.sample(img, steps=S, skip_type="time_uniform", method="multistep", order=3, lower_order_final=True)
return x.to(device), None