RuntimeError: Given groups=1, weight of size [320, 5, 3, 3], expected input[2, 9, 64, 64] to have 5 channels, but got 9 channels instead

[Antoinemr77]

Hi everyone,
I know this error might have been discussed here, but I am trying to fix it on my PC. I would be greatly appreciative for any help to diagnose the problem.

below is the error from the cmd:

*** Error completing request
*** Arguments: ('task(tp0k0fujzhpe5x1)', <gradio.routes.Request object at 0x00000221858E3310>, 'spiderman flying', '', [], 1, 1, 7, 512, 512, False, 0.7, 2, 'Latent', 0, 0, 0, 'Use same checkpoint', 'Use same sampler', 'Use same scheduler', '', '', [], 0, 20, 'DPM++ 2M', 'Automatic', False, '', 0.8, -1, False, -1, 0, 0, 0, False, False, 'positive', 'comma', 0, False, False, 'start', '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, False, False, False, 0, False) {}
Traceback (most recent call last):
File "C:\Users\user\stable-diffusion-webui\modules\call_queue.py", line 57, in f
res = list(func(*args, **kwargs))
File "C:\Users\user\stable-diffusion-webui\modules\call_queue.py", line 36, in f
res = func(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\modules\txt2img.py", line 109, in txt2img
processed = processing.process_images(p)
File "C:\Users\user\stable-diffusion-webui\modules\processing.py", line 845, in process_images
res = process_images_inner(p)
File "C:\Users\user\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:\Users\user\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:\Users\user\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:\Users\user\stable-diffusion-webui\modules\sd_samplers_common.py", line 272, in launch_sampling
return func()
File "C:\Users\user\stable-diffusion-webui\modules\sd_samplers_kdiffusion.py", line 218, 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 "C:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\utils_contextlib.py", line 115, in decorate_context
return func(*args, **kwargs)
File "C:\Users\user\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 "C:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\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:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\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 "C:\Users\user\stable-diffusion-webui\repositories\k-diffusion\k_diffusion\external.py", line 138, in get_eps
return self.inner_model.apply_model(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\modules\sd_hijack_utils.py", line 18, in
setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
File "C:\Users\user\stable-diffusion-webui\modules\sd_hijack_utils.py", line 32, in call
return self.__orig_func(*args, **kwargs)
File "C:\Users\user\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 "C:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1339, in forward
out = self.diffusion_model(xc, t, context=cc)
File "C:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\modules\sd_unet.py", line 91, in UNetModel_forward
return original_forward(self, x, timesteps, context, *args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 797, in forward
h = module(h, emb, context)
File "C:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 86, in forward
x = layer(x)
File "C:\Users\user\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:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\module.py", line 1527, in _call_impl
return forward_call(*args, **kwargs)
File "C:\Users\user\stable-diffusion-webui\extensions-builtin\Lora\networks.py", line 518, in network_Conv2d_forward
return originals.Conv2d_forward(self, input)
File "C:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 460, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\user\stable-diffusion-webui\venv\lib\site-packages\torch\nn\modules\conv.py", line 456, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: Given groups=1, weight of size [320, 5, 3, 3], expected input[2, 9, 64, 64] to have 5 channels, but got 9 channels instead

---

[Antoinemr77]

anyone?

[Antoinemr77]

Bump

[erickhavel]

Same issue here. Mac M1. Using 512-depth-ema.ckpt model.

[Antoinemr77]

I updated my Graphic Card driver. I now receive another kind of error.

[nagarjunr]

I encounter same issue as well in Mac M2. Using 512-depth-ema.ckpt model.