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rosinality / style-based-gan-pytorch

Implementation A Style-Based Generator Architecture for Generative Adversarial Networks in PyTorch
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TypeError: forward() missing 1 required positional argument: 'input' #46

Open MichaelMonashev opened 5 years ago

MichaelMonashev commented 5 years ago 
> CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 python3 train.py --mixing --loss r1 --sched --phase 16 train-full
Size: 256; G: 2.811; D: 3.419; Grad: 0.003; Alpha: 1.00000:   0%|                                                       | 13/3000000 [01:08<17:22:00,  2.08s/it]Traceback (most recent call last):
  File "train_v3.py", line 345, in <module>
    train(args, dataset, generator, discriminator)
  File "train_v3.py", line 133, in train
    real_scores = discriminator(real_image, step=step, alpha=alpha)
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
    result = self.forward(*input, **kwargs)
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 152, in forward
    outputs = self.parallel_apply(replicas, inputs, kwargs)
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/parallel/data_parallel.py", line 162, in parallel_apply
    return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 85, in parallel_apply
    output.reraise()
  File "/home/michael/.local/lib/python3.6/site-packages/torch/_utils.py", line 369, in reraise
    raise self.exc_type(msg)
TypeError: Caught TypeError in replica 4 on device 4.
Original Traceback (most recent call last):
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/parallel/parallel_apply.py", line 60, in _worker
    output = module(*input, **kwargs)
  File "/home/michael/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 547, in __call__
    result = self.forward(*input, **kwargs)
TypeError: forward() missing 1 required positional argument: 'input'

Size: 256; G: 2.811; D: 3.419; Grad: 0.003; Alpha: 1.00000:   0%|                                                     | 13/3000000 [01:14<48:01:02,  5.76s/it]
hblflybird commented 5 years ago

Same issue, you could try adding drop_last=True in Dataloader in sample_data function in train.py

MichaelMonashev commented 5 years ago

I added drop_last=True in Dataloader, but got this error again.

MichaelMonashev commented 5 years ago

Sometimes this error is raised on 128 resolution, sometimes not.

gsygsy96 commented 5 years ago

Maybe some images in your dataset have crashed?