Just a thought

[silveroxides]

in batch_hijack.py on line 59. Doesn't it assume there even if CN is not enabled or called that there is anything to fallback to?
Because this hijack got triggered by me starting generation in short succession. I do have batch cond/uncond set in optimizations so it it that i initiate next generation using 'ctrl+enter' just at moment button to generate becomes available or is it the optimixation setting?
Reason for me not posting actual bug report is because I don't have time to collect all the requirements just to point out one line of code and asking if that might interfer with any other operations.

    def processing_process_images_hijack(self, p, *args, **kwargs):
        try:
            from scripts.animatediff_utils import get_animatediff_arg
            ad_params = get_animatediff_arg(p)
            if ad_params and ad_params.enable:
                return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)
        except ImportError:
            pass

        if self.is_batch:
            # we are in img2img batch tab, do a single batch iteration
            return self.process_images_cn_batch(p, *args, **kwargs)

        cn_is_batch, batches, output_dir, input_file_names = get_cn_batches(p)
        if not cn_is_batch:
            # we are not in batch mode, fallback to original function
            return getattr(processing, '__controlnet_original_process_images_inner')(p, *args, **kwargs)

Console

    Traceback (most recent call last):
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\txt2img.py", line 109, in txt2img
        processed = processing.process_images(p)
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\processing.py", line 845, in process_images
        res = process_images_inner(p)
      File "C:\Stable_Diffusion\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 "C:\Stable_Diffusion\stable-diffusion-webui\modules\processing.py", line 981, 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 "C:\Stable_Diffusion\stable-diffusion-webui\modules\processing.py", line 1328, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, 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 "C:\Stable_Diffusion\stable-diffusion-webui\modules\sd_samplers_common.py", line 272, in launch_sampling
        return func()
      File "C:\Stable_Diffusion\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, in <lambda>
        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 "C:\Stable_Diffusion\stable-diffusion-webui\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "C:\Stable_Diffusion\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\sampling.py", line 145, in sample_euler_ancestral
        denoised = model(x, sigmas[i] * s_in, **extra_args)
      File "C:\Stable_Diffusion\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 "C:\Stable_Diffusion\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Stable_Diffusion\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 "C:\Stable_Diffusion\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 "C:\Stable_Diffusion\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Stable_Diffusion\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 113, in forward
        return input + eps * c_out
    RuntimeError: The size of tensor a (128) must match the size of tensor b (256) at non-singleton dimension 3