code: def __init__(
      self,
      src: int,
      dest: int,
      queue_name: int,
      args: Any = None,
      tensors: Optional[Tensors] = None,
      tensor_count: int = 0,
  ):
      self.src = src
      self.dest = dest
      self.queue_name = queue_name
      self.args = args
      self.tensors = tensors or tuple()
      self.tensor_shapes = []
      self.tensor_dtypes = []
  
      global MessageGeneration
      self.tag = MessageGeneration
      if tensors is None:
          MessageGeneration += tensor_count
      else:
          MessageGeneration += len(self.tensors)
  
file_path: fairscale/fairscale/nn/pipe/types.py
imports: from dataclasses import dataclass
  from typing import Any, Callable, List, Optional, Tuple, Union
  import torch
  from torch import Tensor, nn
label_desc: Use image node_id 1 to create a new PipeMessage object  with example: obj = PipeMessage(src, dest, queue_name, args, tensors, tensor_count)