Repository: stable-diffusion-webui
Issue: [Bug]:     RuntimeError: "upsample_nearest2d_channels_last" not implemented for 'Half'
Labels: bug-report,platform:mac

### Is there an existing issue for this?

- [X] I have searched the existing issues and checked the recent builds/commits

### What happened?

Cannot generate images. Not sure what changed since a few days ago when it was running fine, but here is the error I generated.
 `RuntimeError: "upsample_nearest2d_channels_last" not implemented for 'Half'`

Image tries to generate for like 2 seconds before pulling this error.

### Steps to reproduce the problem

1. Add prompt
2. attempt to generate image
3. Image does not generate


### What should have happened?

...Image should generate.

### Version or Commit where the problem happens

v1.5.2, commit hash c9c8485bc1e8720aba70f029d25cba1c4abf2b5c

### What Python version are you running on ?

Python 3.10.x

### What platforms do you use to access the UI ?

MacOS

### What device are you running WebUI on?

CPU

### Cross attention optimization

Automatic

### What browsers do you use to access the UI ?

Google Chrome

### Command Line Arguments

```Shell
No
```


### List of extensions

a1111-sd-webui-lycoris

stable-diffusion-webui-images-browser




### Console logs

```Shell
Running on local URL:  http://127.0.0.1:7860

To create a public link, set `share=True` in `launch()`.
Startup time: 4.3s (launcher: 0.2s, import torch: 1.3s, import gradio: 0.6s, setup paths: 0.3s, other imports: 0.3s, list SD models: 0.1s, load scripts: 0.4s, create ui: 0.8s).
Applying attention optimization: InvokeAI... done.
Model loaded in 5.1s (load weights from disk: 0.6s, create model: 0.8s, apply weights to model: 1.4s, apply half(): 1.5s, move model to device: 0.6s, calculate empty prompt: 0.1s).
  0%|                                                    | 0/77 [00:01<?, ?it/s]
*** Error completing request
*** Arguments: ('task(cqwpl7x78uin03e)', '(masterpiece:1.2, best quality:1.2, high quality, highres:1.1, high contrast, vibrant colors), (unique character design), extremely detailed, (cast shadows), 4K, perfect eyes, perfect face, ((adult school teacher)), (pencil skirt), (button-down shirt),  ((strained buttons)), (straight blonde hair),\n\n', 'easynegative, (bad character design:1.6),  ((nipples)), bad quality, worst quality, blur, bad anatomy, extra limbs, loli, child, watermark, logo, signature,  ng_deepnegative_v1_75t, ((blurry)),  (no arms),  squashed face, deformed face, bizarre facial features, unnatural facial features, (too many arms), ((multiple people))', [], 77, 15, False, False, 1, 1, 8.5, 2431381970.0, -1.0, 0, 0, 0, False, 728, 528, False, 0.7, 2, 'Latent', 0, 0, 0, 0, '', '', [], <gradio.routes.Request object at 0x2930fead0>, 0, False, False, 'positive', 'comma', 0, False, False, '', 1, '', [], 0, '', [], 0, '', [], True, False, False, False, 0) {}
    Traceback (most recent call last):
      File "/Users/karsten/stable-diffusion-webui/modules/call_queue.py", line 58, in f
        res = list(func(*args, **kwargs))
      File "/Users/karsten/stable-diffusion-webui/modules/call_queue.py", line 37, in f
        res = func(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/modules/txt2img.py", line 62, in txt2img
        processed = processing.process_images(p)
      File "/Users/karsten/stable-diffusion-webui/modules/processing.py", line 677, in process_images
        res = process_images_inner(p)
      File "/Users/karsten/stable-diffusion-webui/modules/processing.py", line 794, 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 "/Users/karsten/stable-diffusion-webui/modules/processing.py", line 1054, in sample
        samples = self.sampler.sample(self, x, conditioning, unconditional_conditioning, image_conditioning=self.txt2img_image_conditioning(x))
      File "/Users/karsten/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 464, in sample
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
      File "/Users/karsten/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 303, in launch_sampling
        return func()
      File "/Users/karsten/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 464, in <lambda>
        samples = self.launch_sampling(steps, lambda: self.func(self.model_wrap_cfg, x, extra_args={
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
        return func(*args, **kwargs)
      File "/Users/karsten/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 "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/modules/sd_samplers_kdiffusion.py", line 202, in forward
        x_out[a:b] = self.inner_model(x_in[a:b], sigma_in[a:b], cond=make_condition_dict(c_crossattn, image_cond_in[a:b]))
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/k-diffusion/k_diffusion/external.py", line 114, in forward
        eps = self.get_eps(input * c_in, self.sigma_to_t(sigma), **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/k-diffusion/k_diffusion/external.py", line 140, in get_eps
        return self.inner_model.apply_model(*args, **kwargs)
      File "/Users/karsten/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 "/Users/karsten/stable-diffusion-webui/modules/sd_hijack_utils.py", line 26, in __call__
        return self.__sub_func(self.__orig_func, *args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/modules/sd_hijack_unet.py", line 48, in apply_model
        return orig_func(self, x_noisy.to(devices.dtype_unet), t.to(devices.dtype_unet), cond, **kwargs).float()
      File "/Users/karsten/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 "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/models/diffusion/ddpm.py", line 1335, in forward
        out = self.diffusion_model(x, t, context=cc)
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/modules/sd_unet.py", line 91, in UNetModel_forward
        return ldm.modules.diffusionmodules.openaimodel.copy_of_UNetModel_forward_for_webui(self, x, timesteps, context, *args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py", line 802, in forward
        h = module(h, emb, context)
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py", line 86, in forward
        x = layer(x)
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1501, in _call_impl
        return forward_call(*args, **kwargs)
      File "/Users/karsten/stable-diffusion-webui/repositories/stable-diffusion-stability-ai/ldm/modules/diffusionmodules/openaimodel.py", line 115, in forward
        x = F.interpolate(x, scale_factor=2, mode="nearest")
      File "/Users/karsten/stable-diffusion-webui/venv/lib/python3.10/site-packages/torch/nn/functional.py", line 3931, in interpolate
        return torch._C._nn.upsample_nearest2d(input, output_size, scale_factors)
    RuntimeError: "upsample_nearest2d_channels_last" not implemented for 'Half'
```


### Additional information

_No response_