code: def test_overlapping_gpt2(self):
      raw = ["Indico Is the best hey"]
      finetunex = [["Indico", " Is the", " best", " hey"]]
      finetuney = [[("1",), ("1", "2"), ("2",), ("<PAD>")]]
      encoder = GPT2Encoder()
      indicox_pred, indicoy_pred = finetune_to_indico_sequence(
          raw,
          finetunex,
          finetuney,
          none_value="<PAD>",
          subtoken_predictions=False,
      )
      indicoy = [
          [
              {
                  "start": 0,
                  "end": 13,
                  "label": "1",
                  "text": "Indico Is the",
              },
              {
                  "start": 7,
                  "end": 18,
                  "label": "2",
                  "text": "Is the best",
              },
          ]
      ]
      self.assertEqual(indicoy, indicoy_pred)
      self.assertEqual(raw, indicox_pred)
  
imports: import unittest
  from collections import Counter
  import pytest
  import numpy
  import tensorflow
  import unicodedata
  from finetune.encoding.sequence_encoder import finetune_to_indico_sequence
  from finetune.optimizers.gradient_accumulation import get_grad_accumulation_optimizer
  from finetune.util.imbalance import compute_class_weights
  from finetune.util.optimize_loss import OPTIMIZERS
  from finetune.util.timing import ProgressBar
  from finetune.errors import FinetuneError
  from finetune import Classifier, SequenceLabeler
  from finetune.base_models.gpt.encoder import GPTEncoder
  from finetune.base_models.gpt2.encoder import GPT2Encoder
  from finetune.base_models.bert.roberta_encoder import RoBERTaEncoderV2, RoBERTaEncoder, RoBERTaEncoderSlow
  from finetune.base_models.bert.encoder import BERTEncoderMultuilingal, BERTEncoder
  from finetune.base_models.oscar.encoder import GPCEncoder
  from finetune.scheduler import Scheduler
label_desc: Use image node_id 4 for calling the TestFinetuneIndicoConverters obj's underlying member method code with example usage: obj.test_overlapping_gpt2() without return types