docstr: Numerical features are returned in the order they appear in the channel spec section
  For performance reasons, this is required to be the order they are saved in, as specified
  by the relevant chunk in source spec.
  Categorical features are returned in the order they appear in the channel spec section
docstr_tok: ["Numerical","features","are","returned","in","the","order","they","appear","in","the","channel","spec","section","For","performance","reasons",",","this","is","required","to","be","the","order","they","are","saved","in",",","as","specified","by","the","relevant","chunk","in","source","spec",".","Categorical","features","are","returned","in","the","order","they","appear","in","the","channel","spec","section"]
code: def __getitem__(self, idx: int):
      """Numerical features are returned in the order they appear in the channel spec section
      For performance reasons, this is required to be the order they are saved in, as specified
      by the relevant chunk in source spec.
      Categorical features are returned in the order they appear in the channel spec section
      """
  
      if idx >= self._num_entries:
          raise IndexError()
  
      return self._get_item(idx)
  
imports: import concurrent
  import math
  import os
  from typing import Dict, List, Optional, Tuple
  import numpy
  import torch
  from torch.utils import data
  from torch.utils.data import Dataset
  from torch.utils.data.distributed import DistributedSampler
  from torchrec.datasets.criteo import CAT_FEATURE_COUNT, DEFAULT_CAT_NAMES, DEFAULT_INT_NAMES
  from torchrec.datasets.utils import Batch
  from torchrec.sparse.jagged_tensor import KeyedJaggedTensor
label_desc: Use image node_id 3 for calling the ParametricDataset obj's underlying member method code with example usage: obj.__getitem__(idx) and returns: self