Fatal Error 'unfolded2d_copy not implemented' When Attempting to Run for the First Time

[DC-19]

Hello,
I have finished installing CLIP-Guided-Diffusion, but when I run it, this error happens:
Device: cpu
Size: 256
Setting up [LPIPS] perceptual loss: trunk [vgg], v[0.1], spatial [off]
Loading model from: C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\lpips\weights\v0.1\vgg.pth
Seed: 1221123546082200
Text prompt: A rope tied in a figure-eight knot
0%| | 0/1000 [00:00<?, ?it/s]
Traceback (most recent call last):
File "C:\Users\XXXXXX\CLIP-Guided-Diffusion\generate_diffuse.py", line 460, in
do_run()
File "C:\Users\XXXXXX\CLIP-Guided-Diffusion\generate_diffuse.py", line 359, in do_run
for j, sample in enumerate(samples):
File "c:\users\XXXXXX\guided-diffusion\guided_diffusion\gaussian_diffusion.py", line 637, in p_sample_loop_progressive
out = sample_fn(
File "c:\users\XXXXXXX\guided-diffusion\guided_diffusion\gaussian_diffusion.py", line 461, in p_sample
out = self.p_mean_variance(
File "c:\users\XXXXXXX\guided-diffusion\guided_diffusion\respace.py", line 91, in p_mean_variance
return super().p_mean_variance(self._wrap_model(model), *args, **kwargs)
File "c:\users\XXXXXX\guided-diffusion\guided_diffusion\gaussian_diffusion.py", line 260, in p_mean_variance
model_output = model(x, self._scale_timesteps(t), **model_kwargs)
File "c:\users\XXXXXX\guided-diffusion\guided_diffusion\respace.py", line 128, in call
return self.model(x, new_ts, **kwargs)
File "C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "c:\users\XXXXX\guided-diffusion\guided_diffusion\unet.py", line 656, in forward
h = module(h, emb)
File "C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "c:\users\XXXXXX\guided-diffusion\guided_diffusion\unet.py", line 77, in forward
x = layer(x)
File "C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\torch\nn\modules\conv.py", line 443, in forward
return self._conv_forward(input, self.weight, self.bias)
File "C:\Users\XXXXXX\Anaconda3\envs\cgd\lib\site-packages\torch\nn\modules\conv.py", line 439, in _conv_forward
return F.conv2d(input, weight, bias, self.stride,
RuntimeError: "unfolded2d_copy" not implemented for 'Half'

Any help would be appreciated.

[ZaneA]

In case you didn't find it yet, you can pass -nfp to the script (e.g. python3 generate_diffuse.py -nfp -p "A painting of an apple") to force 32bit floating point instead of half/16bit floating point. This gets things working on a CPU for me (very slowly) :)