hyperparameter_setting.py

# Size of latent (noise) vector to generator
z_dim = 100 

# Learning ratess
learning_rate_D =  .00005 
learning_rate_G = 2e-4 

# Batch size
batch_size = 4
# Number of epochs
num_epochs = 500

# decay rates
alpha = 0.2
beta1 = 0.5

training_model.py

# Load the training data
training_dataset = helper.Dataset(glob(os.path.join(resized_data_dir, '*.jpg')))

# Train the model
with tf.Graph().as_default():
    train_gan_model(num_epochs, batch_size, z_dim, learning_rate_D, learning_rate_G, beta1, training_dataset.get_batches,
          training_dataset.shape, training_dataset.image_mode, alpha)