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Fix SDXL area composition sometimes not using the right pooled output.
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@ -126,9 +126,15 @@ class BaseModel(torch.nn.Module):
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cond_concat.append(blank_inpaint_image_like(noise))
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data = torch.cat(cond_concat, dim=1)
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out['c_concat'] = comfy.conds.CONDNoiseShape(data)
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adm = self.encode_adm(**kwargs)
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if adm is not None:
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out['y'] = comfy.conds.CONDRegular(adm)
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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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def load_model_weights(self, sd, unet_prefix=""):
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@ -322,6 +328,10 @@ class SVD_img2vid(BaseModel):
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out['c_concat'] = comfy.conds.CONDNoiseShape(latent_image)
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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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if "time_conditioning" in kwargs:
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out["time_context"] = comfy.conds.CONDCrossAttn(kwargs["time_conditioning"])
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@ -599,6 +599,10 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
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calculate_start_end_timesteps(model, negative)
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calculate_start_end_timesteps(model, positive)
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if hasattr(model, 'extra_conds'):
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positive = encode_model_conds(model.extra_conds, positive, noise, device, "positive", latent_image=latent_image, denoise_mask=denoise_mask)
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negative = encode_model_conds(model.extra_conds, negative, noise, device, "negative", latent_image=latent_image, denoise_mask=denoise_mask)
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#make sure each cond area has an opposite one with the same area
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for c in positive:
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create_cond_with_same_area_if_none(negative, c)
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@ -613,9 +617,6 @@ def sample(model, noise, positive, negative, cfg, device, sampler, sigmas, model
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if latent_image is not None:
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latent_image = model.process_latent_in(latent_image)
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if hasattr(model, 'extra_conds'):
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positive = encode_model_conds(model.extra_conds, positive, noise, device, "positive", latent_image=latent_image, denoise_mask=denoise_mask)
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negative = encode_model_conds(model.extra_conds, negative, noise, device, "negative", latent_image=latent_image, denoise_mask=denoise_mask)
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extra_args = {"cond":positive, "uncond":negative, "cond_scale": cfg, "model_options": model_options, "seed":seed}
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