34 lines
1.1 KiB
Python
34 lines
1.1 KiB
Python
import torch
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import comfy.model_base
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def sdxl_encode_adm_patched(self, **kwargs):
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clip_pooled = kwargs["pooled_output"]
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width = kwargs.get("width", 768)
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height = kwargs.get("height", 768)
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crop_w = kwargs.get("crop_w", 0)
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crop_h = kwargs.get("crop_h", 0)
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target_width = kwargs.get("target_width", width)
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target_height = kwargs.get("target_height", height)
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if kwargs.get("prompt_type", "") == "negative":
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admk = 0.8
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width *= admk
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height *= admk
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target_width *= admk
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target_height *= admk
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out = []
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out.append(self.embedder(torch.Tensor([height])))
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out.append(self.embedder(torch.Tensor([width])))
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out.append(self.embedder(torch.Tensor([crop_h])))
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out.append(self.embedder(torch.Tensor([crop_w])))
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out.append(self.embedder(torch.Tensor([target_height])))
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out.append(self.embedder(torch.Tensor([target_width])))
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flat = torch.flatten(torch.cat(out))[None, ]
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return torch.cat((clip_pooled.to(flat.device), flat), dim=1)
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def patch_negative_adm():
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comfy.model_base.SDXL.encode_adm = sdxl_encode_adm_patched
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