class_docstr: ``SampleList`` is used to collate a list of ``Sample`` into a batch during batch
  preparation. It can be thought of as a merger of list of Dicts into a single Dict.
  
  If ``Sample`` contains an attribute 'text' of size (2) and there are 10 samples in
  list, the returned ``SampleList`` will have an attribute 'text' which is a tensor
  of size (10, 2).
  
  Args:
      samples (type): List of ``Sample`` from which the ``SampleList``
                      will be created.
  
  Usage::
  
      >>> sample_list = [
              Sample({"text": torch.tensor(2)}),
              Sample({"text": torch.tensor(2)})
          ]
      >>> sample_list.text
      torch.tensor([2, 2])
code: def _set_tensor_field(self, value):
      self.__dict__[SampleList._TENSOR_FIELD_] = 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 15 for calling the SampleList obj's underlying member method code with example usage: obj._set_tensor_field(value) without return types