model/data_utils.py [224:234]:
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        total_sample_num = len(split_data)

        def iterator():
            perm = np.arange(total_sample_num)
            if do_shuffle:
                rng = np.random.RandomState(seed)
                rng.shuffle(perm)
            assert batch_size < total_sample_num
            tracker_list = [(i, 0) for i in range(batch_size)]
            next_idx = batch_size
            data = torch.LongTensor(bptt, batch_size)
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model/data_utils.py [324:334]:
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        total_sample_num = len(split_data)

        def iterator():
            perm = np.arange(total_sample_num)
            if do_shuffle:
                rng = np.random.RandomState(seed)
                rng.shuffle(perm)
            assert batch_size < total_sample_num
            tracker_list = [(i, 0) for i in range(batch_size)]
            next_idx = batch_size
            data = torch.LongTensor(bptt, batch_size)
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