code: def backward(ctx, *grad):
      ctx.message.tensors = tuple(grad)
      ctx.transport.send_message(
          ctx.message, sync=False, skip_header=True
      )
      ctx.event.set()
      # torch.futures.wait_all(ctx.futures)
      return (None, None, None, None, None, None)
  
imports: from threading import Event, Lock, Thread
  from typing import Any, Callable, Dict, List, Optional, Tuple, Union, cast
  import torch
  from torch import nn
  from torch.distributed import ProcessGroup, rpc
  from torch.distributed.distributed_c10d import _get_global_rank
  from fairscale.nn.model_parallel.initialize import get_pipeline_parallel_group
  from .async_pipe import AsyncPipe
  from .types import EVENT_LOOP_QUEUE, PipeMessage, TensorOrTensors
label_desc: Use image node_id 2 for calling the PipeBackRedirect obj's underlying member method code with example usage: obj.backward(ctx) and returns: None,  None,  None,  None,  None,  None