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Update model_base.py

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Subarasheese 2026-02-18 01:43:25 -03:00 committed by GitHub
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commit 8e04804d5e
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comfy/model_base.py
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@ -1588,6 +1588,35 @@ class ACEStep15(BaseModel):
refer_audio = torch.cat([refer_audio.to(pad), pad[:, :, refer_audio.shape[2]:]], dim=2) refer_audio = torch.cat([refer_audio.to(pad), pad[:, :, refer_audio.shape[2]:]], dim=2)
out['refer_audio'] = comfy.conds.CONDRegular(refer_audio) out['refer_audio'] = comfy.conds.CONDRegular(refer_audio)
audio_cover_strength = kwargs.get('audio_cover_strength', 1.0)
is_cover_mode = out.get('is_covers', comfy.conds.CONDConstant(None)).cond != False
if audio_cover_strength < 1.0 and is_cover_mode and self.current_patcher is not None:
if not self.current_patcher.get_wrappers(comfy.patcher_extension.WrappersMP.PREDICT_NOISE, 'ace_step_cover_strength'):
_strength = audio_cover_strength
def audio_cover_strength_wrapper(executor, x, timestep, model_options={}, seed=None):
sample_sigmas = model_options.get('transformer_options', {}).get('sample_sigmas', None)
if sample_sigmas is not None:
current_sigma = float(timestep.max())
max_sigma = float(sample_sigmas[0])
min_sigma = float(sample_sigmas[-1])
sigma_range = max_sigma - min_sigma
if sigma_range > 0:
progress = 1.0 - (current_sigma - min_sigma) / sigma_range
if progress >= _strength:
conds = model_options.get('conds', None)
if conds is not None:
for cond_list in conds.values():
for cond in cond_list:
if 'model_conds' in cond and 'is_covers' in cond['model_conds']:
cond['model_conds']['is_covers'] = comfy.conds.CONDConstant(False)
return executor(x, timestep, model_options, seed)
self.current_patcher.add_wrapper_with_key(
comfy.patcher_extension.WrappersMP.PREDICT_NOISE,
'ace_step_cover_strength',
audio_cover_strength_wrapper
)
return out return out
class Omnigen2(BaseModel): class Omnigen2(BaseModel):