code: def __getitem__(self, idx):
      if isinstance(idx, np.int64):
          idx = idx.item()
  
      if self.samples_mapping is not None:
          assert idx < len(self.samples_mapping)
          idx, _, _ = self.samples_mapping[idx]
          if isinstance(idx, np.uint32):
              idx = idx.item()
  
      assert idx < len(self.indexed_dataset)
      # idx may < 0 because we pad_samples_to_global_batch_size, e.g. id = -1
      if idx < 0:
          idx = len(self) + idx
          auto_gen_idx = True
      else:
          auto_gen_idx = False
      try:
          example = self.indexed_dataset[idx]
          if auto_gen_idx:
              example["__AUTOGENERATED__"] = True
      except Exception as e:
          logging.error(
              f"Error while loading example {idx} from dataset {self.file_path}"
          )
          raise e
      return self._process_example(example)
  
imports: import re
  from typing import List, Mapping, Optional
  import datasets
  import numpy
  import torch
  from datasets import load_dataset
  from nemo.collections.common.tokenizers.tokenizer_spec import TokenizerSpec
  from nemo.collections.nlp.data.language_modeling.megatron.dataset_utils import get_samples_mapping
  from nemo.collections.nlp.data.language_modeling.text_memmap_dataset import JSONLMemMapDataset
  from nemo.core.classes import Dataset
  from nemo.utils import logging
label_desc: Use image node_id 5 for calling the GPTSFTDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: self