TypeError: add_() received an invalid combination of arguments - got (complex, Tensor)

I have git checkout d1ec858, but after completing 40000 steps, then error happened.

INFO     step:40000 G_lr:0.000000 G_loss:113.60744(mc:0.13908 pixelwise:113.43781 pairwise:0.00256) D_lr:0.000000 D_loss:0.01955
Traceback (most recent call last):
  File "train_and_eval.py", line 25, in <module>
    model.optimize_parameters()
  File "/home/shine/文档/structure_knowledge_distillation/networks/kd_model.py", line 171, in optimize_parameters
    self.G_solver.step()
  File "/home/shine/anaconda3/envs/wangnan/lib/python3.6/site-packages/torch/optim/sgd.py", line 107, in step
    p.data.add_(-group['lr'], d_p)
TypeError: add_() received an invalid combination of arguments - got (complex, Tensor), but expected one of:
 * (Tensor other, Number alpha)
      didn't match because some of the arguments have invalid types: (complex, Tensor)
 * (Number other, Number alpha)
      didn't match because some of the arguments have invalid types: (complex, Tensor)

[wl082013]

I have git checkout d1ec858, but after completing 40000 steps, then error happened.

INFO     step:40000 G_lr:0.000000 G_loss:113.60744(mc:0.13908 pixelwise:113.43781 pairwise:0.00256) D_lr:0.000000 D_loss:0.01955
Traceback (most recent call last):
  File "train_and_eval.py", line 25, in <module>
    model.optimize_parameters()
  File "/home/shine/文档/structure_knowledge_distillation/networks/kd_model.py", line 171, in optimize_parameters
    self.G_solver.step()
  File "/home/shine/anaconda3/envs/wangnan/lib/python3.6/site-packages/torch/optim/sgd.py", line 107, in step
    p.data.add_(-group['lr'], d_p)
TypeError: add_() received an invalid combination of arguments - got (complex, Tensor), but expected one of:
 * (Tensor other, Number alpha)
      didn't match because some of the arguments have invalid types: (complex, Tensor)
 * (Number other, Number alpha)
      didn't match because some of the arguments have invalid types: (complex, Tensor)

Exactly the same problem with you

[lmunan]

Although there was an error in the end, the final evaluation had a good performance. Now I want to use the official resnet18-imagenet for pretrain, and then I encountered the same problem #20 . I replace conv1-3x3 with 7x7 to load the pretrain. Then the following problem appeared.

Traceback (most recent call last):
  File "train_and_eval.py", line 19, in <module>
    model = NetModel(args)
  File "/home/mist/structure_knowledge_distillation/networks/kd_model.py", line 58, in __init__
    load_S_model(args, student, False)
  File "/home/mist/structure_knowledge_distillation/utils/utils.py", line 103, in load_S_model
    model.load_state_dict(new_params)
  File "/home/mist/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 719, in load_state_dict
    self.__class__.__name__, "\n\t".join(error_msgs)))
RuntimeError: Error(s) in loading state_dict for ResNet:
        size mismatch for layer1.0.conv1.weight: copying a param of torch.Size([64, 128, 3, 3]) from checkpoint, where the shape is torch.Size([64, 64, 3, 3]) in current model.

Me too have the same problem with you. Did you solve it?

I did not use the official pre-trained model, I downloaded the pre-trained model from here. No error was reported, but the final result has not been seen yet.