Comments (4)
I have been 550 000+ steps for my images and result still not enough good.
But in fact the result was not improve (subjective, I didnt calc FID) after 30-60k steps.
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Have you tried logging the values for the loss functions and gp in a file and visualizing the results?
from lightweight-gan.
The loss values is not informative and dont have relative to visual quality like FID, but FID require other installed library and a lot of time so I still not calulate this =)
Visualising result is enabled by default, and I made command to show progress (see readme.md) and I really dont see improve after 60k steps (with batch size equal to 3)
from lightweight-gan.
The visualization of the result shows the generated images. However, Iām still improving the training phase and discovering the best settings combination for training, that is why I wanted to know the behavior of the networks with each iteration
from lightweight-gan.
Related Issues (20)
- question about generated images HOT 35
- Error(s) in loading state_dict for LightweightGAN HOT 2
- Batchnorm layer missing in the discriminator?
- showing results while training ? HOT 2
- G is showing up a negative number. What does that mean?
- Multi GPU utilization problem.
- TypeError: __init__() got an unexpected keyword argument 'hparams' HOT 1
- unable to load save model. please try downgrading the package to the version specified by the saved model HOT 7
- --load_strict=False failing to load model HOT 1
- Can't find "__main__" module (sorry if noob question) HOT 4
- loss implementation differs from paper HOT 1
- Doesn't detect CUDA from Nvidia GPU HOT 1
- Torchvision Assertion error while importing custom data
- Aim installation error HOT 4
- Discriminator Loss converges to 0 while Generator loss pretty high HOT 3
- Dont detects cuda HOT 1
- Using Lightweight GAN as a library
- Projecting generated Images to Latent Space HOT 1
- Executing with a trailing \ in the arguments sets the variable new to the truthy value '\\' and deletes all progress
- CUDA out of memory error while generating interpolations
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