[Bug]: Channel mismatch when running on linux

[QiuhongAnnaWei]

Is there an existing issue for this?

• [X] I have searched the existing issues and checked the recent builds/commits of both this extension and the webui.

What happened?

Running control_v11f1p_sd15_depth [cfd03158], control_v11p_sd15_canny [d14c016b], or control_sd15_depth_anything [48a4bc3a] all result in

RuntimeError: Given groups=1, weight of size [320, 4, 3, 3], expected input[2, 5, 64, 64] to have 4 channels, but got 5 channels instead

This problem does not occur when I run locally on my Mac. The above error is from running it on Linux.

I've tried enabling "Do not append detectmap to output" in Settings, but it did not fix it.

Steps to reproduce the problem

What should have happened?

Run smoothly.

Commit where the problem happens

webui: latest controlnet: latest

What browsers do you use to access the UI ?

No response

Command Line Arguments

export COMMANDLINE_ARGS="--api --share --enable-insecure-extension-access"

List of enabled extensions

The only non-built-in I have is sd-webui-controlnet.

Console logs

File "~/stable-diffusion-webui/modules/api/api.py", line 440, in img2imgapi                                                                                 [4/1912]
        processed = process_images(p)                                                                                                                                                                    
      File "~/stable-diffusion-webui/modules/processing.py", line 734, in process_images                                                                                  
        res = process_images_inner(p)                                                                                                                                                                    
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/batch_hijack.py", line 41, in processing_process_images_hijack                                        
        return getattr(processing, '__controlnet_original_process_images_inner')(p, *args,**kwargs)                                                                                                           
       File "~/stable-diffusion-webui/modules/processing.py", line 868, 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 "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 438, in process_sample                                                                 
        return process.sample_before_CN_hack(*args, **kwargs)                                                                                                                                                  
      File "~/stable-diffusion-webui/modules/processing.py", line 1527, in sample                                                                                                 
        samples = self.sampler.sample_img2img(self, self.init_latent, x, conditioning, unconditional_conditioning, image_conditioning=self.image_conditioning)                                                 
      File "~/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 188, in sample_img2img                                                                              
        samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))          
      File "~/stable-diffusion-webui/modules/sd_samplers_common.py", line 261, in launch_sampling                                                                                 
        return func()
      File "~/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 188, in <lambda>
        samples = self.launch_sampling(t_enc + 1, lambda: self.func(self.model_wrap_cfg, xi, extra_args=self.sampler_extra_args, disable=False, callback=self.callback_state, **extra_params_kwargs))
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "~/stable-diffusion-webui/repositories/k-diffusion/k_diffusion/sampling.py", line 128, in sample_euler
        denoised = model(x, sigma_hat * s_in, **extra_args)
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/modules/sd_samplers_cfg_denoiser.py", line 169, in forward
        x_out = self.inner_model(x_in, sigma_in, cond=make_condition_dict(cond_in, image_cond_in))
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/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 "~/stable-diffusion-webui/repositories/k-diffusion/k_diffusion/external.py", line 138, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "~/stable-diffusion-webui/modules/sd_hijack_utils.py", line 17, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "~/stable-diffusion-webui/modules/sd_hijack_utils.py", line 28, in __call__
        return self.__orig_func(*args, **kwargs)
      File "~/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 "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/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 "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 862, in forward_webui
        raise e
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 859, in forward_webui
        return forward(*args, **kwargs)
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/hook.py", line 581, in forward
        control = param.control_model(
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/cldm.py", line 31, in forward
        return self.control_model(*args, **kwargs) 
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/extensions/sd-webui-controlnet/scripts/cldm.py", line 310, in forward
        h = module(h, emb, context)
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/repositories/generative-models/sgm/modules/diffusionmodules/openaimodel.py", line 102, in forward
        x = layer(x)
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "~/stable-diffusion-webui/extensions-builtin/Lora/networks.py", line 501, in network_Conv2d_forward                                                            
        return originals.Conv2d_forward(self, input)
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/conv.py", line 463, in forward                                                   
        return self._conv_forward(input, self.weight, self.bias)
      File "~/stable-diffusion-webui/venv/lib64/python3.9/site-packages/torch/nn/modules/conv.py", line 459, in _conv_forward
        return F.conv2d(input, weight, bias, self.stride,
    RuntimeError: Given groups=1, weight of size [320, 4, 3, 3], expected input[2, 5, 64, 64] to have 4 channels, but got 5 channels instead

Additional information