a1111 webui에서 upscaler와 controlnet의 충돌

[seonukkim]

최근 controlnet이 SDXL을 지원하기 시작하면서, 크게 업데이트가 되었는데 이 과정에서 ddsd에 있는 upscaler와 controlnet이 충돌이 있는 듯 합니다. tensor 크기로 인한 문제인 것 같은데 아래와 같은 오류 메시지가 뜨며 upscaling이 skip됩니다.

실제로 controlnet을 SDXL 지원 이전으로 돌렸을 때는 다음과 같은 문제가 발생하지 않습니다.
(Upscaler before running detailer를 체크했을 때 포함)

한 번 확인해보고 이 부분 반영해서 업데이트 해주시면 감사하겠습니다 :)

Tile upscaling will process a total of 16 images tiled as 4x4 per upscale in a total of 17 batches (I2I).
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*** Error running postprocess_image: /home/ubuntu/stable-diffusion-webui/extensions/sd-webui-ddsd/scripts/ddsd.py

        processed = processing.process_images(pi)
      File "/home/ubuntu/stable-diffusion-webui/modules/processing.py", line 732, in process_images
        res = process_images_inner(p)
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/batch_hijack.py", line 42, in processing_process_images_hijack
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/modules/processing.py", line 867, in process_images_inner
        samples_ddim = p.sample(conditioning=p.c, unconditional_conditioning=p.uc, seeds=p.seeds, subseeds=p.subseeds, subseed_strength=p.subseed_strength, prompts=p.prompts)
      File "/home/ubuntu/stable-diffusion-webui/modules/processing.py", line 1528, in sample
        samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)
      File "/home/ubuntu/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 188, in sample_img2img
        samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/home/ubuntu/stable-diffusion-webui/modules/sd_samplers_common.py", line 261, in launch_sampling
        return func()
      File "/home/ubuntu/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 188, in <lambda>
        samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/repositories/k-diffusion/k_diffusion/sampling.py", line 668, in sample_dpmpp_3m_sde
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 188, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)

      File "/home/ubuntu/stable-diffusion-webui/modules/sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "/home/ubuntu/stable-diffusion-webui/modules/sd_hijack_utils.py", line 28, in __call__
        return self.__orig_func(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py", line 858, in apply_model
        x_recon = self.model(x_noisy, t, **cond)
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py", line 1335, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 858, in forward_webui
        raise e
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 855, in forward_webui
        return forward(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 592, in forward
        control = param.control_model(x=x_in, hint=hint, timesteps=timesteps, context=context, y=y)
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/cldm.py", line 31, in forward
        return self.control_model(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/home/ubuntu/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/cldm.py", line 311, in forward
        h += guided_hint
    RuntimeError: The size of tensor a (128) must match the size of tensor b (256) at non-singleton dimension 3