Exception: device privateuseone:0 is invalid

[tangcan1600]

- It cannot work when using cpu,seems a tensor send to the wrong device,I could not solve this issue,how can I do to let it run correctly?

Traceback (most recent call last):
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\extra_networks.py", line 75, in activate
    extra_network.activate(p, extra_network_args)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions-builtin\Lora\extra_networks_lora.py", line 23, in activate
    lora.load_loras(names, multipliers)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions-builtin\Lora\lora.py", line 151, in load_loras
    lora = load_lora(name, lora_on_disk.filename)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions-builtin\Lora\lora.py", line 83, in load_lora
    sd = sd_models.read_state_dict(filename)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_models.py", line 217, in read_state_dict
    pl_sd = safetensors.torch.load_file(checkpoint_file, device=device)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\safetensors\torch.py", line 98, in load_file
    with safe_open(filename, framework="pt", device=device) as f:
Exception: device privateuseone:0 is invalid

Traceback (most recent call last):
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\call_queue.py", line 56, in f
    res = list(func(*args, **kwargs))
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\call_queue.py", line 37, in f
    res = func(*args, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\txt2img.py", line 56, in txt2img
    processed = process_images(p)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\processing.py", line 486, in process_images
    res = process_images_inner(p)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\processing.py", line 635, 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 "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\processing.py", line 835, in sample
    samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 351, in sample
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 227, in launch_sampling
    return func()
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 351, in <lambda>
    samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\sampling.py", line 150, in sample_euler_ancestral
    denoised = model(x, sigmas[i] * s_in, **extra_args)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 138, in forward
    x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond={"c_crossattn": c_crossattn, "c_concat": [image_cond_in[a:b]]})
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\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 "F:\ai\stable_diffusion\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 "F:\ai\stable_diffusion\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 "F:\ai\stable_diffusion\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 28, in __call__
    return self.__orig_func(*args, **kwargs)
  File "F:\ai\stable_diffusion\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 "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\models\diffusion\ddpm.py", line 1329, in forward
    out = self.diffusion_model(x, t, context=cc)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\hook.py", line 233, in forward2
    return forward(*args, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\hook.py", line 176, in forward
    control = param.control_model(x=x_in, hint=param.hint_cond, timesteps=timesteps, context=context)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\cldm.py", line 115, in forward
    return self.control_model(*args, **kwargs)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions\sd-webui-controlnet\scripts\cldm.py", line 370, in forward
    guided_hint = self.input_hint_block(cond_cast_unet(hint), emb, context)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 86, in forward
    x = layer(x)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
    return forward_call(*input, **kwargs)
  File "F:\ai\stable_diffusion\stable-diffusion-webui-directml\extensions-builtin\Lora\lora.py", line 182, in lora_Conv2d_forward
    return lora_forward(self, input, torch.nn.Conv2d_forward_before_lora(self, input))
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\conv.py", line 463, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "D:\Users\tangtang1600\Anaconda3\envs\automatic\Lib\site-packages\torch\nn\modules\conv.py", line 459, in _conv_forward
    return F.conv2d(input, weight, bias, self.stride,
RuntimeError: tensor.device().type() == at::DeviceType::PrivateUse1 INTERNAL ASSERT FAILED at "D:\\a\\_work\\1\\s\\pytorch-directml-plugin\\torch_directml\\csrc\\dml\\DMLTensor.cpp":31, please report a bug to PyTorch. unbox expects Dml at::Tensor as inputs