*** Error completing request
*** Arguments: ('task(q4w36jkvvadphza)', <gradio.routes.Request object at 0x0000014E8DFD81C0>, 'cat', '', [], 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\reyals\stable-diffusion-webui-directml\modules\call_queue.py", line 57, in f
        res = list(func(*args, **kwargs))
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\call_queue.py", line 36, in f
        res = func(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\txt2img.py", line 109, in txt2img
        processed = processing.process_images(p)
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\processing.py", line 847, in process_images
        res = process_images_inner(p)
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\processing.py", line 1075, 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\reyals\stable-diffusion-webui-directml\modules\processing.py", line 1422, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 221, 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\reyals\stable-diffusion-webui-directml\modules\sd_samplers_common.py", line 272, in launch_sampling
        return func()
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\sd_samplers_kdiffusion.py", line 221, 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:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\utils\_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\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\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\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\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\external.py", line 167, in forward
        return self.get_v(input * c_in, self.sigma_to_t(sigma), **kwargs) * c_out + input * c_skip
      File "C:\Users\reyals\stable-diffusion-webui-directml\repositories\k-diffusion\k_diffusion\external.py", line 177, in get_v
        return self.inner_model.apply_model(x, t, cond)
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 18, in <lambda>
        setattr(resolved_obj, func_path[-1], lambda *args, **kwargs: self(*args, **kwargs))
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\sd_hijack_utils.py", line 32, in __call__
        return self.__orig_func(*args, **kwargs)
      File "C:\Users\reyals\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\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\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\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\modules\sd_unet.py", line 91, in UNetModel_forward
        return original_forward(self, x, timesteps, context, *args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\repositories\stable-diffusion-stability-ai\ldm\modules\diffusionmodules\openaimodel.py", line 789, in forward
        emb = self.time_embed(t_emb)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\container.py", line 217, in forward
        input = module(input)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1532, in _wrapped_call_impl
        return self._call_impl(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\module.py", line 1541, in _call_impl
        return forward_call(*args, **kwargs)
      File "C:\Users\reyals\stable-diffusion-webui-directml\extensions-builtin\Lora\networks.py", line 503, in network_Linear_forward
        return originals.Linear_forward(self, input)
      File "C:\Users\reyals\stable-diffusion-webui-directml\venv\lib\site-packages\torch\nn\modules\linear.py", line 116, in forward
        return F.linear(input, self.weight, self.bias)
    RuntimeError: mat1 and mat2 must have the same dtype, but got Float and Half

---