RuntimeError: Given groups=1, weight of size [64, 18, 4, 4], expected input[2, 4, 256, 256] to have 18 channels, but got 4 channels instead

[YuanBo66668888]

we run command
python train.py --name celebahqedge --dataset_mode celebahqedge --dataroot dataset_path --niter 30 --niter_decay 30 --which_perceptual 4_2 --weight_perceptual 0.001 --use_attention --maskmix --PONO --PONO_C --vgg_normal_correct --fm_ratio 1.0 --warp_bilinear --warp_cycle_w 1 --batchSize 1 --gpu_ids 0

but have some errors

/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/functional.py:1558: UserWarning: nn.functional.tanh is deprecated. Use torch.tanh instead.
warnings.warn("nn.functional.tanh is deprecated. Use torch.tanh instead.")
Traceback (most recent call last):
File "train.py", line 58, in
trainer.run_discriminator_one_step(data_i)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/trainers/pix2pix_trainer.py", line 70, in run_discriminator_one_step
d_losses = self.pix2pix_model(data, mode='discriminator', GforD=GforD)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/models/pix2pix_model.py", line 75, in forward
input_semantics, real_image, GforD, label=input_label)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/models/pix2pix_model.py", line 289, in compute_discriminator_loss
input_semantics, fake_image, real_image)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/models/pix2pix_model.py", line 352, in discriminate
discriminator_out, seg, cam_logit = self.net'netD'
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/models/networks/discriminator.py", line 62, in forward
out, cam_logit = D(input)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "/home/dc2-user/tomyuan-workstation/CoCosNet/models/networks/discriminator.py", line 152, in forward
intermediate_output = submodel(x)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/container.py", line 100, in forward
input = module(input)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/module.py", line 550, in call
result = self.forward(*input, **kwargs)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 353, in forward
return self._conv_forward(input, self.weight)
File "/home/dc2-user/.local/lib/python3.7/site-packages/torch/nn/modules/conv.py", line 350, in _conv_forward
self.padding, self.dilation, self.groups)
RuntimeError: Given groups=1, weight of size [64, 18, 4, 4], expected input[2, 4, 256, 256] to have 18 channels, but got 4 channels instead

[panzhang0212]

Duplicate of #3

[YuanBo66668888]

It's effective!!
#3 solved by self.preprocess_input(data, ) to self.preprocess_input(data.copy(), ) in line 52 of pix2pix_model.py!

[YuanBo66668888]

The another question is we have only one gpu(0) is 16G，the train is very slow，have some method to improve train process, Thanks! I send a email to you! I very glad and hope to received your reply

[panzhang0212]

please check your email.

[YuanBo66668888]

Thank you very much, I'm working on cost functions,Is it convenient to add you as a friend?

[XiangyuSu611]

Hi, @YuanBo66668888 I have the same problems with you, training process is very slow. How did you slove this problem? Could you please give me a notice? By the way, I can speak chinese.

Thanks first.