train problem

[cyanymore]

Traceback (most recent call last):
File "train.py", line 58, in
trainer.run_discriminator_one_step(data_i)
File "C:\Users\64883\Desktop\ref_code\CoCosNet-master\trainers\pix2pix_trainer.py", line 70, in run_discriminator_one_step
d_losses = self.pix2pix_model(data, mode='discriminator', GforD=GforD)
File "D:\Anaconda3\envs\paddlepaddle\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "C:\Users\64883\Desktop\ref_code\CoCosNet-master\models\pix2pix_model.py", line 52, in forward
input_label, input_semantics, real_image, self_ref, ref_image, ref_label, ref_semantics = self.preprocess_input(data, )
File "C:\Users\64883\Desktop\ref_code\CoCosNet-master\models\pix2pix_model.py", line 193, in preprocess_input
input_semantics[:,-3:-2,:,:] = glasses
RuntimeError: The expanded size of the tensor (1) must match the existing size (0) at non-singleton dimension 1. Target sizes: [1, 1, 256, 256]. Tensor sizes: [0, 256, 256]

the problem is solved by setting the self.preprocess_input(data, ) to self.preprocess_input(data.copy(), ) in line 52 of pix2pix_model.py.

thanks to #3