code: def test_no_whitespace_in_idxs(self):
      def make_comparible(text):
          return unicodedata.normalize(
              "NFKC", text.replace("\u200c", "")
          ).lower()
  
      encoded = self.encoder.encode_multi_input(
          [self.text], max_length=2000
      )
      print(encoded)
      for tok, start, end in zip(
          encoded.tokens, encoded.token_starts, encoded.token_ends
      ):
          if start == -1:
              continue  # this is the special tokens
          print(start, end)
          sub_seq = self.text[start:end]
          self.assertEqual(
              sub_seq, sub_seq.strip()
          )  # no leading or trailing whitespace
          self.assertNotIn("\n", sub_seq)
          self.assertIn(make_comparible(sub_seq), make_comparible(tok))
  
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 TestGPTEncoder obj's underlying member method code with example usage: obj.test_no_whitespace_in_idxs() and returns: unicodedata