Tensorflow implementation for training GANs with various objectives and gradient penalties, different network architectures, both image and word generations
- Python >=2.7
- Tensorflow >=1.1.0
First download CelebA or other datasets with:
$ python download.py --dataset CelebA --data_dir data
To train a model for image generation:
$ python GAN_GP_Img.py
To train a model for word generation:
$ python GAN_GP_Char.py
You might need to customize the training process by changing the default arguments