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Initial ACE-Step model implementation. (#7972)

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comfyanonymous
2025-05-07 05:33:34 -07:00
committed by GitHub
parent 271c9c5b9e
commit 16417b40d9
18 changed files with 19738 additions and 4 deletions
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19
comfy/model_base.py
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@@ -39,6 +39,7 @@ import comfy.ldm.wan.model
import comfy.ldm.hunyuan3d.model
import comfy.ldm.hidream.model
import comfy.ldm.chroma.model
import comfy.ldm.ace.model
import comfy.model_management
import comfy.patcher_extension
@@ -1121,3 +1122,21 @@ class Chroma(Flux):
if guidance is not None:
out['guidance'] = comfy.conds.CONDRegular(torch.FloatTensor([guidance]))
return out
class ACEStep(BaseModel):
def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.ace.model.ACEStepTransformer2DModel)
def extra_conds(self, **kwargs):
out = super().extra_conds(**kwargs)
noise = kwargs.get("noise", None)
cross_attn = kwargs.get("cross_attn", None)
if cross_attn is not None:
out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
conditioning_lyrics = kwargs.get("conditioning_lyrics", None)
if cross_attn is not None:
out['lyric_token_idx'] = comfy.conds.CONDRegular(conditioning_lyrics)
out['speaker_embeds'] = comfy.conds.CONDRegular(torch.zeros(noise.shape[0], 512, device=noise.device, dtype=noise.dtype))
return out