Description
我应该如何修改，以适配自己的数据集，问题如
Traceback (most recent call last):
File "E:\GSAD-main\train.py", line 281, in
main()
File "E:\GSAD-main\train.py", line 220, in main
diffusion.test(continous=False)
File "E:\GSAD-main\model\model.py", line 142, in test
self.SR = self.netG.super_resolution(self.data['LQ'], continous)
File "D:\conda\envs\gsad\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "E:\GSAD-main\model\ddpm_modules\diffusion_Pt.py", line 214, in super_resolution
return self.p_sample_loop(x_in, continous)
File "D:\conda\envs\gsad\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "E:\GSAD-main\model\ddpm_modules\diffusion_Pt.py", line 198, in p_sample_loop
img = self.p_sample(img, i, condition_x=x)
File "D:\conda\envs\gsad\lib\site-packages\torch\autograd\grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "E:\GSAD-main\model\ddpm_modules\diffusion_Pt.py", line 173, in p_sample
model_mean, model_log_variance = self.p_mean_variance(
File "E:\GSAD-main\model\ddpm_modules\diffusion_Pt.py", line 159, in p_mean_variance
x, t=t, noise=self.denoise_fn(torch.cat([condition_x, x], dim=1), noise_level)[0])
File "D:\conda\envs\gsad\lib\site-packages\torch\nn\modules\module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "E:\GSAD-main\model\ddpm_modules\unet.py", line 267, in forward
x = layer(torch.cat((x, feats.pop()), dim=1), noise_level)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 16 but got size 15 for tensor number 1 in the list.