An error occurs when using layer_diffusion_cond_fg_all.json

[wTechArtist]

An error occurs when using layer_diffusion_cond_fg_all.json
After I downloaded it and ran it directly, the following error occurred：

Error occurred when executing KSampler:

Sizes of tensors must match except in dimension 1. Expected size 128 but got size 144 for tensor number 1 in the list.

File "D:\Software\Ai\ComfyUI-aki-v1.2\execution.py", line 152, in recursive_execute
output_data, output_ui = get_output_data(obj, input_data_all)
File "D:\Software\Ai\ComfyUI-aki-v1.2\execution.py", line 82, in get_output_data
return_values = map_node_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True)
File "D:\Software\Ai\ComfyUI-aki-v1.2\execution.py", line 75, in map_node_over_list
results.append(getattr(obj, func)(**slice_dict(input_data_all, i)))
File "D:\Software\Ai\ComfyUI-aki-v1.2\nodes.py", line 1368, in sample
return common_ksampler(model, seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise)
File "D:\Software\Ai\ComfyUI-aki-v1.2\nodes.py", line 1338, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "D:\Software\Ai\ComfyUI-aki-v1.2\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 22, in informative_sample
raise e
File "D:\Software\Ai\ComfyUI-aki-v1.2\custom_nodes\ComfyUI-Impact-Pack\modules\impact\sample_error_enhancer.py", line 9, in informative_sample
return original_sample(*args, **kwargs) # This code helps interpret error messages that occur within exceptions but does not have any impact on other operations.
File "D:\Software\Ai\ComfyUI-aki-v1.2\custom_nodes\ComfyUI-AnimateDiff-Evolved\animatediff\sampling.py", line 248, in motion_sample
return orig_comfy_sample(model, noise, *args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\sample.py", line 100, in sample
samples = sampler.sample(noise, positive_copy, negative_copy, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 703, in sample
return sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 608, in sample
samples = sampler.sample(model_wrap, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 547, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "D:\Software\Ai\ComfyUI-aki-v1.2\python\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\k_diffusion\sampling.py", line 137, in sample_euler
denoised = model(x, sigma_hat * s_in, **extra_args)
File "D:\Software\Ai\ComfyUI-aki-v1.2\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self._call_impl(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 285, in forward
out = self.inner_model(x, sigma, cond=cond, uncond=uncond, cond_scale=cond_scale, model_options=model_options, seed=seed)
File "D:\Software\Ai\ComfyUI-aki-v1.2\python\lib\site-packages\torch\nn\modules\module.py", line 1518, in _wrapped_call_impl
return self.call_impl(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\python\lib\site-packages\torch\nn\modules\module.py", line 1527, in call_impl
return forward_call(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 272, in forward
return self.apply_model(*args, **kwargs)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 269, in apply_model
out = sampling_function(self.inner_model, x, timestep, uncond, cond, cond_scale, model_options=model_options, seed=seed)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 249, in sampling_function
cond_pred, uncond_pred = calc_cond_uncond_batch(model, cond, uncond, x, timestep, model_options)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\samplers.py", line 223, in calc_cond_uncond_batch
output = model.apply_model(input_x, timestep, **c).chunk(batch_chunks)
File "D:\Software\Ai\ComfyUI-aki-v1.2\comfy\model_base.py", line 76, in apply_model
xc = torch.cat([xc] + [c_concat], dim=1)

[huchenlei]

This is likely caused by input image having size that is different from latent noise. You can add a crop image node to crop/resize the image to match the latent's size.