import tensorflow as tf

                  False -> Create or search of variables before creating
    :return: tensor of shape [batch_size, 1]
    """
    if reuse:
        tf.get_variable_scope().reuse_variables()
    with tf.name_scope('Discriminator_Gauss'):
        dc_den1 = tf.nn.relu(dense(x, z_dim, n_l1, name='dc_g_den1'))
        dc_den2 = tf.nn.relu(dense(dc_den1, n_l1, n_l2, name='dc_g_den2'))
        output = dense(dc_den2, n_l2, 1, name='dc_g_output')
        return output
