class_docstr: ``CommDebugMode`` is a context manager that counts the number of
  functional collectives within its context. It does this using a
  ``TorchDispatchMode``.
  
  NOTE: this mode only works for functional collective atm and the
  distributed_c10d collectives are not supported yet.
  
  Example usage
  
  .. code-block:: python
  
      mod = ...
      comm_mode = CommDebugMode()
      with comm_mode:
          mod.sum().backward()
docstr: Returns the communication counts as a dictionary.
  
  Returns:
      Dict[Any, int]: The communication counts as a dictionary.
code: def get_comm_counts(self) -> Dict[Any, int]:
      """Returns the communication counts as a dictionary.
  
      Returns:
          Dict[Any, int]: The communication counts as a dictionary.
      """
      return self.comm_counts
  
file_path: pytorch/torch/distributed/_tensor/debug/comm_mode.py
imports: from collections import defaultdict
  from typing import Any, Dict
  import torch
  from torch.utils._python_dispatch import TorchDispatchMode
label_desc: Use image node_id 3 for calling the CommDebugMode obj's underlying member method code with example usage: obj.get_comm_counts() and returns: self