class_docstr: Sample represent some arbitrary data. All datasets in MMF must
  return an object of type ``Sample``.
  
  Args:
      init_dict (Dict): Dictionary to init ``Sample`` class with.
  
  Usage::
  
      >>> sample = Sample({"text": torch.tensor(2)})
      >>> sample.text.zero_()
      # Custom attributes can be added to ``Sample`` after initialization
      >>> sample.context = torch.tensor(4)
docstr: Get current attributes/fields registered under the sample.
  
  Returns:
      List[str]: Attributes registered under the Sample.
code: def fields(self):
      """Get current attributes/fields registered under the sample.
  
      Returns:
          List[str]: Attributes registered under the Sample.
  
      """
      return list(self.keys())
  
imports: import collections
  import collections.abc
  import warnings
  from collections import OrderedDict
  from typing import Any, Dict, Union
  import torch
label_desc: Use image node_id 5 for calling the Sample obj's underlying member method code with example usage: obj.fields() and returns: list