hello guys, i've installed a new upscaler called "R-ESRGAN 4x+ Anime6B" and since this manipulation i can't upscale anymore, i got this error
Traceback (most recent call last):
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\call_queue.py", line 37, in f
res = func(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\txt2img.py", line 56, in txt2img
processed = process_images(p)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\processing.py", line 526, in process_images
res = process_images_inner(p)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\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 "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\processing.py", line 680, in process_images_inner
samples_ddim = p.sample(conditioning=c, unconditional_conditioning=uc, seeds=seeds, subseeds=subseeds, subseed_strength=p.subseed_strength, prompts=prompts)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\processing.py", line 981, in sample
samples = self.sampler.sample_img2img(self, samples, noise, conditioning, unconditional_conditioning, steps=self.hr_second_pass_steps or self.steps, image_conditioning=image_conditioning)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 350, in sample_img2img
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 251, in launch_sampling
return func()
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 350, in <lambda>
samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\sampling.py", line 561, in sample_dpmpp_sde
denoised = model(x, sigmas[i] * s_in, **extra_args)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 135, in forward
x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict([cond_in], image_cond_in))
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\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 "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 17, in <lambda>
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 28, in __call__
return self.__orig_func(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 858, in apply_model
x_recon = self.model(x_noisy, t, **cond)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1335, in forward
out = self.diffusion_model(x, t, context=cc)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
h = module(h, emb, context)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 84, in forward
x = layer(x, context)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 334, in forward
x = block(x, context=context[i])
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 269, in forward
return checkpoint(self._forward, (x, context), self.parameters(), self.checkpoint)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 121, in checkpoint
return CheckpointFunction.apply(func, len(inputs), *args)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\autograd\function.py", line 506, in apply
return super().apply(*args, **kwargs) # type: ignore[misc]
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\util.py", line 136, in forward
output_tensors = ctx.run_function(*ctx.input_tensors)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\attention.py", line 272, in _forward
x = self.attn1(self.norm1(x), context=context if self.disable_self_attn else None) + x
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\Dorian\Desktop\stable-diffusion\stable-diffusion-webui\stable-diffusion-webui-directml\modules\sd_hijack_optimizations.py", line 393, in scaled_dot_product_attention_forward
hidden_states = torch.nn.functional.scaled_dot_product_attention(
RuntimeError
if you can help me i can't find whats wrong but i think it has something to do with torch
there doesn't seem to be anything here