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Tensorflow implementation for training GANs with various objectives and gradient penalties, different network architectures, both image and word generations

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GAN-general

Tensorflow implementation for training GANs with various objectives and gradient penalties, different network architectures, both image and word generations

Requirements

  • Python >=2.7
  • Tensorflow >=1.1.0

Usage

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

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Tensorflow implementation for training GANs with various objectives and gradient penalties, different network architectures, both image and word generations

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