carpedm20 / began-pytorch Goto Github PK

Excuse me，I try to run the code of BEGAN-pytorch, but the generate images are a mess ,like this:

Could u tell me the reason？
Must I use the BEGAN-tensorflow to get the good result?
thanks！

Hi! Refering your code, I make below changes in my code.

I change the way of the initializing at first.
Then, I change the way to get the loss. In my code, the both part of the g_loss would be used for learning G's parameters, but in your code it maybe only the AE_G be used for learning G's parameters.
I'm not sure about this, but maybe you can try it. And it's not big changes.
I'm sorry for my pool English~

Hi, @dribnet @carpedm20 @scott-vsi

I met this error:

ctilab@ctilab:~/BEGAN-pytorch$ python main.py --dataset=images --num_gpu=0
RuntimeError: module compiled against API version 0xb but this version of numpy is 0xa
Traceback (most recent call last):
File "main.py", line 1, in
import torch
File "/usr/local/lib/python2.7/dist-packages/torch/init.py", line 53, in
from torch._C import *
ImportError: numpy.core.multiarray failed to import

What's wrong with me?

How many Gb ram on Nvidia graphic card is needed? Thanks

In the BEGAN paper ,it says:"Implementation note: while the updates are made simultaneously, they are still adversarial. As such, it is important to optimize θD and θG independently with respect to their corresponding losses".
Maybe this will get better results?

Not sure exactly what occurred, but while training with your code with default parameters and tensorboard enabled, the training lost it at 14000/500000.

The network then began outputting completely black images for all three _D, _D, and _D_fake.

Not much more insight from my end I am afraid. Trained on a Titan XP in ubuntu with pytorch 0.1.10 - py27_1cu80 [cuda80] - soumith, torchvision 0.1.6, and python 2.7.13 on ubuntu 16.04.

Loss_D went from 0.0436 to 1.45, and L_x went from 0.0436 to 1.522

Hi, @dribnet @carpedm20 @scott-vsi

I met this error:

ctilab@ctilab:~/BEGAN-pytorch$ python main.py --dataset=CelebA --num_gpu=1 --use_tensorboard=True
Found 162770 images in subfolders of: data/CelebA/splits/train
[] MODEL dir: logs/CelebA_1008_173315
[] PARAM path: logs/CelebA_1008_173315/params.json
0%| | 0/500000 [00:00<?, ?it/s]/usr/local/lib/python2.7/dist-packages/torch/nn/modules/upsampling.py:135: UserWarning: nn.UpsamplingNearest2d is deprecated. Use nn.Upsample instead.
warnings.warn("nn.UpsamplingNearest2d is deprecated. Use nn.Upsample instead.")

Traceback (most recent call last):
File "main.py", line 42, in
main(config)
File "main.py", line 34, in main
trainer.train()
File "/home/ctilab/BEGAN-pytorch/trainer.py", line 160, in train
d_loss_real = l1(AE_x, x)
File "/usr/local/lib/python2.7/dist-packages/torch/nn/modules/module.py", line 224, in call
result = self.forward(*input, **kwargs)
File "/home/ctilab/BEGAN-pytorch/models.py", line 117, in forward
return backend_fn(self.size_average)(input, target)
TypeError: forward() takes at least 3 arguments (2 given)
ctilab@ctilab:~/BEGAN-pytorch$

What's wrong with me?