Cleanup old TODO.
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@ -148,7 +148,9 @@ class BaseModel(torch.nn.Module):
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xc = xc.to(dtype)
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xc = xc.to(dtype)
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t = self.model_sampling.timestep(t).float()
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t = self.model_sampling.timestep(t).float()
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context = context.to(dtype)
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if context is not None:
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context = context.to(dtype)
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extra_conds = {}
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extra_conds = {}
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for o in kwargs:
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for o in kwargs:
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extra = kwargs[o]
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extra = kwargs[o]
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@ -549,6 +551,10 @@ class SD_X4Upscaler(BaseModel):
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out['c_concat'] = comfy.conds.CONDNoiseShape(image)
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out['c_concat'] = comfy.conds.CONDNoiseShape(image)
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out['y'] = comfy.conds.CONDRegular(noise_level)
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out['y'] = comfy.conds.CONDRegular(noise_level)
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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.CONDCrossAttn(cross_attn)
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return out
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return out
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class IP2P:
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class IP2P:
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@ -58,7 +58,6 @@ def convert_cond(cond):
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temp = c[1].copy()
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temp = c[1].copy()
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model_conds = temp.get("model_conds", {})
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model_conds = temp.get("model_conds", {})
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if c[0] is not None:
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if c[0] is not None:
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model_conds["c_crossattn"] = comfy.conds.CONDCrossAttn(c[0]) #TODO: remove
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temp["cross_attn"] = c[0]
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temp["cross_attn"] = c[0]
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temp["model_conds"] = model_conds
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temp["model_conds"] = model_conds
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temp["uuid"] = uuid.uuid4()
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temp["uuid"] = uuid.uuid4()
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