research/gam/gam/trainer/trainer_classification.py [786:811]:
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    if self.use_graph:
      pair_ll_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='ll')
      pair_lu_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='lu')
      pair_uu_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='uu')
    else:
      pair_ll_iterator = self.pair_iterator(train_indices, train_indices,
                                            self.num_pairs_reg, data)
      pair_lu_iterator = self.pair_iterator(train_indices, unlabeled_indices,
                                            self.num_pairs_reg, data)
      pair_uu_iterator = self.pair_iterator(unlabeled_indices,
                                            unlabeled_indices,
                                            self.num_pairs_reg, data)

    step = 0
    iter_below_tol = 0
    min_num_iter = self.min_num_iter
    has_converged = step >= self.max_num_iter
    prev_loss_val = np.inf
    best_test_acc = -1
    best_val_acc = -1
    checkpoint_saved = False
    while not has_converged:
      feed_dict = self._construct_feed_dict(
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research/gam/gam/trainer/trainer_classification_gcn.py [785:810]:
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    if self.use_graph:
      pair_ll_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='ll')
      pair_lu_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='lu')
      pair_uu_iterator = self.edge_iterator(
          data, batch_size=self.num_pairs_reg, labeling='uu')
    else:
      pair_ll_iterator = self.pair_iterator(train_indices, train_indices,
                                            self.num_pairs_reg, data)
      pair_lu_iterator = self.pair_iterator(train_indices, unlabeled_indices,
                                            self.num_pairs_reg, data)
      pair_uu_iterator = self.pair_iterator(unlabeled_indices,
                                            unlabeled_indices,
                                            self.num_pairs_reg, data)

    step = 0
    iter_below_tol = 0
    min_num_iter = self.min_num_iter
    has_converged = step >= self.max_num_iter
    prev_loss_val = np.inf
    best_test_acc = -1
    best_val_acc = -1
    checkpoint_saved = False
    while not has_converged:
      feed_dict = self._construct_feed_dict(
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