Support hunyuan image 2.1 regular model. (#9792)
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@@ -1408,3 +1408,27 @@ class QwenImage(BaseModel):
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if ref_latents is not None:
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out['ref_latents'] = list([1, 16, sum(map(lambda a: math.prod(a.size()), ref_latents)) // 16])
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return out
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class HunyuanImage21(BaseModel):
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def __init__(self, model_config, model_type=ModelType.FLOW, device=None):
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super().__init__(model_config, model_type, device=device, unet_model=comfy.ldm.hunyuan_video.model.HunyuanVideo)
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def extra_conds(self, **kwargs):
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out = super().extra_conds(**kwargs)
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attention_mask = kwargs.get("attention_mask", None)
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if attention_mask is not None:
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if torch.numel(attention_mask) != attention_mask.sum():
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out['attention_mask'] = comfy.conds.CONDRegular(attention_mask)
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cross_attn = kwargs.get("cross_attn", None)
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if cross_attn is not None:
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out['c_crossattn'] = comfy.conds.CONDRegular(cross_attn)
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conditioning_byt5small = kwargs.get("conditioning_byt5small", None)
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if conditioning_byt5small is not None:
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out['txt_byt5'] = comfy.conds.CONDRegular(conditioning_byt5small)
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guidance = kwargs.get("guidance", 6.0)
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if guidance is not None:
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out['guidance'] = comfy.conds.CONDRegular(torch.FloatTensor([guidance]))
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return out
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