def create_GAN_hparams(generator_hidden_layers=[30, 30], discriminator_hidden_layers=[30, 30], learning_rate=None,
                       epochs=100, batch_size=32, activation='relu',
                       optimizer='Adam', loss='mse', patience=4, reg_term=0, generator_dropout=0,
                       discriminator_dropout=0,
                       filters=3):
    """
    Creates hparam dict for input into GAN class. Contain Hyperparameter info
    :return: hparam dict
    """
    names = ['generator_hidden_layers', 'discriminator_hidden_layers', 'learning_rate', 'epochs', 'batch_size',
             'activation', 'optimizer', 'loss', 'patience',
             'reg_term', 'generator_dropout', 'discriminator_dropout',
             'filters']
    values = [generator_hidden_layers, discriminator_hidden_layers, learning_rate, epochs, batch_size, activation,
              optimizer, loss, patience, reg_term, generator_dropout, discriminator_dropout,
              filters]
    hparams = dict(zip(names, values))
    return hparams