RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1 but got size 2 for tensor number 1 in the list.

[atbgams]

This error occurs when using any inpaint models, while the same error does not occur when using the standard sd1.5 model

Traceback (most recent call last):
File "E:\AI\stable-diffusion-webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "E:\AI\stable-diffusion-webui\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\modules\txt2img.py", line 110, in txt2img
processed = processing.process_images(p)
File "E:\AI\stable-diffusion-webui\modules\processing.py", line 785, in process_images
res = process_images_inner(p)
File "E:\AI\stable-diffusion-webui\extensions\sd-webui-controlnet\scripts\batch_hijack.py", line 59, in processing_process_images_hijack
return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
File "E:\AI\stable-diffusion-webui\modules\processing.py", line 921, 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 "E:\AI\stable-diffusion-webui\modules\processing.py", line 1257, in sample
samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
File "E:\AI\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 234, in sample
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "E:\AI\stable-diffusion-webui\modules\sd_samplers_common.py", line 261, in launch_sampling
return func()
File "E:\AI\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 234, in
samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 594, in sample_dpmpp_2m
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\modules\sd_samplers_cfg_denoiser.py", line 237, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 112, in forward
eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
File "E:\AI\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\modules\sd_hijack_utils.py", line 18, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "E:\AI\stable-diffusion-webui\modules\sd_hijack_utils.py", line 32, in call
return self.__orig_func(*args, **kwargs)
File "E:\AI\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 "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1568, in _call_impl
result = forward_call(*args, **kwargs)
File "E:\AI\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1337, in forward
xc = torch.cat([x] + c_concat, dim=1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 1 but got size 2 for tensor number 1 in the list.

[atbgams]

The same settings and prompt words will cause this error when using the inpaint model, while the normal model will not

[atbgams]

Finally, the problem was discovered, as long as the value is not 0, an error will be reported