code: def test_nested_labels(self):
      raw = ["Indico Is the best"]
      finetunex = [["Indico ", "Is the", " best"]]
      finetuney = [[("1",), ("1", "2", "3"), ("1",)]]
      encoder = GPTEncoder()
      indicox_pred, indicoy_pred = finetune_to_indico_sequence(
          raw, finetunex, finetuney, none_value="<PAD>"
      )
  
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 6 for calling the TestFinetuneIndicoConverters obj's underlying member method code with example usage: obj.test_nested_labels() without return types