code: def test_fold_long_sequences(self):
      # Let's just say [PAD] is 0, [CLS] is 1, and [SEP] is 2
      token_ids = torch.LongTensor(
          [
              [
                  1,
                  101,
                  102,
                  103,
                  104,
                  2,
                  1,
                  105,
                  106,
                  107,
                  108,
                  2,
                  1,
                  109,
                  2,
              ],
              [
                  1,
                  201,
                  202,
                  203,
                  204,
                  2,
                  1,
                  205,
                  206,
                  207,
                  208,
                  2,
                  0,
                  0,
                  0,
              ],
              [1, 301, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
          ]
      )  # Shape: [3, 15]
      segment_concat_mask = (token_ids > 0).long()
  
      folded_token_ids = torch.LongTensor(
          [
              [1, 101, 102, 103, 104, 2],
              [1, 105, 106, 107, 108, 2],
              [1, 109, 2, 0, 0, 0],
              [1, 201, 202, 203, 204, 2],
              [1, 205, 206, 207, 208, 2],
              [0, 0, 0, 0, 0, 0],
              [1, 301, 2, 0, 0, 0],
              [0, 0, 0, 0, 0, 0],
              [0, 0, 0, 0, 0, 0],
          ]
      )
      folded_segment_concat_mask = (folded_token_ids > 0).long()
  
      token_embedder = PretrainedTransformerEmbedder(
          "bert-base-uncased", max_length=6
      )
  
      (
          folded_token_ids_out,
          folded_segment_concat_mask_out,
          _,
      ) = token_embedder._fold_long_sequences(
          token_ids, segment_concat_mask
      )
      assert (folded_token_ids_out == folded_token_ids).all()
      assert (
          folded_segment_concat_mask_out == folded_segment_concat_mask
      ).all()
  
imports: import math
  import pytest
  import torch
  from allennlp.common import Params, cached_transformers
  from allennlp.common.testing import AllenNlpTestCase, requires_gpu
  from allennlp.data import Vocabulary
  from allennlp.data.batch import Batch
  from allennlp.data.fields import TextField
  from allennlp.data.instance import Instance
  from allennlp.data.token_indexers import PretrainedTransformerIndexer
  from allennlp.data.tokenizers import PretrainedTransformerTokenizer
  from allennlp.modules.text_field_embedders import BasicTextFieldEmbedder
  from allennlp.modules.token_embedders import PretrainedTransformerEmbedder
label_desc: Use image node_id 8 for calling the TestPretrainedTransformerEmbedder obj's underlying member method code with example usage: obj.test_fold_long_sequences() without return types