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)
code: def __setattr__(self, key, value):
      if isinstance(value, collections.abc.Mapping):
          value = Sample(value)
      self[key] = value
  
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 2 for calling the Sample obj's underlying member method code with example usage: obj.__setattr__(key, value) without return types