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)
      example = self.indexed_dataset[idx]
      return self._process_example(example)
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/t0_dataset.py
imports: import numpy
  import torch
  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, TextMemMapDataset
  from nemo.core.classes import Dataset
label_desc: Use image node_id 4 for calling the T0Dataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: self