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Tensorflow implementation of 1D Generative Adversarial Network

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1D_GAN (WIP)

Tensorflow implementation of 1D convolutional Generative Adversarial Network (improved WGAN variant, see Improved Training of Wasserstein GANs).

Be aware this is a Work In Progress (see #1)

Run instructions

Assuming you installed Python 3 with tensorflow, numpy, matplotlib, scikit-learn and pandas you need to:

  • Clone the project
git clone https://github.com/PaulEmmanuelSotir/1D_GAN.git
cd ./1D_GAN
  • And train the model
# By default, the model will be trained on sinusoidal curves of random frequency and offset
python gan1d.py

You can see training progress on tensorboard:

# Launch the following command and browse to localhost:6006
tensorboard --logdir=./models

Also note that this project can run on Floyd (Heroku for deep learning):

# To run a Floyd training job, use the following command:
floyd run --data paulemmanuel/datasets/btc_eur_1y/1 --env tensorflow-1.4 --tensorboard --gpu "python gan1d.py --floyd-job"

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