import tensorflow as tf

    batch_iter_idx = 1
    n_iters_per_epoch = len(dataset.training_X) // self.training_iterator.batch_size
    self.lr_policy.n_iters_per_epoch = n_iters_per_epoch
    for epoch in range(start_epoch, self.cnf.get('mum_epochs', 550) + 1):
      np.random.seed(epoch + seed_delta)
      tf.set_random_seed(epoch + seed_delta)
      tic = time.time()
      d_train_losses = []
      g_train_losses = []
      batch_train_sizes = []
