code: def _communicate(
      object: Any,
      send_dst: Optional[int],
      recv_src: Optional[int],
      send_group: Optional[ProcessGroup] = None,
      recv_group: Optional[ProcessGroup] = None,
      send_metadata: bool = True,
      metadata_recv: Optional[P2PMetadata] = None,
      send_prior_fallback: Optional[bool] = None,
  ) -> Any:
      """
      Send and receive object from send_dst and recv_src respectively
  
      Args:
          object (Any): object needed to be sent
          send_dst (int): rank of the destination
          recv_src (int): rank of the source
          send_group (ProcessGroup, optional): process group of sender
          recv_group (ProcessGroup, optional): process group of receiver
          send_metadata (bool, optional): whether to send metadata
          metadata_recv (P2PMetadata, optional): metadata of the object to be received
      """
      assert (
          send_dst is not None or recv_src is not None
      ), "send_dst and recv_src cannot be both None"
      assert (
          send_dst is None or send_group is not None
      ), "send_group must be specified when send_dst is not None"
      assert (
          recv_src is None or recv_group is not None
      ), "recv_group must be specified when recv_src is not None"
      assert (
          metadata_recv is None
          or len(metadata_recv.non_tensor_obj_idx) == 0
      ), "metadata_recv should not contain non-tensor objects"
  
      metadata_send, tensor_objs = None, None
      if object is not None:
          # NOTE: if object contains non-tensor objects, we have to send metadata
          metadata_send, tensor_objs = create_send_metadata(
              object, strict=False, return_tensor=True
          )
          send_metadata = (
              send_metadata or len(metadata_send.non_tensor_obj_idx) > 0
          )
  
      # NOTE: send & recv should be atomic operations. However, if we need to send metadata or receive metadata,
      #   we are not able to do that (1. send & recv metadata 2. send & recv). So we need to split the send & recv into two parts in this case.
      if (send_dst is not None and recv_src is not None) and (
          send_metadata or metadata_recv is None
      ):
          assert (
              send_prior_fallback is not None
          ), "Priority must be set if fallback happens"
          if send_prior_fallback:
              _communicate(
                  object,
                  send_dst=send_dst,
                  recv_src=None,
                  send_group=send_group,
                  send_metadata=send_metadata,
              )
              return _communicate(
                  None,
                  send_dst=None,
                  recv_src=recv_src,
                  recv_group=recv_group,
                  metadata_recv=metadata_recv,
              )
          else:
              recv_data = _communicate(
                  None,
                  send_dst=None,
                  recv_src=recv_src,
                  recv_group=recv_group,
                  metadata_recv=metadata_recv,
              )
              _communicate(
                  object,
                  send_dst=send_dst,
                  recv_src=None,
                  send_group=send_group,
                  send_metadata=send_metadata,
              )
              return recv_data
  
      # NOTE: only the following 5 cases are valid:
      #   1. send() [needs extra metadata] and no recv()
      #   2. recv() [needs extra metadata] and no send()
      #   3. neither send() nor recv() need extra metadata
      assert (
          not (send_dst is not None and send_metadata)
          or recv_src is None
      )
      assert (
          not (recv_src is not None and metadata_recv is None)
          or send_dst is None
      )
      assert not (send_dst is not None and recv_src is not None) or (
          not send_metadata and metadata_recv is not None
      )
      assert not c10d._rank_not_in_group(
          send_group
      ) and not c10d._rank_not_in_group(recv_group)
  
      current_send_device, is_send_nccl_backend = _check_device(
          send_group
      )
      current_recv_device, is_recv_nccl_backend = _check_device(
          recv_group
      )
  
      is_nccl_backend = is_send_nccl_backend and is_recv_nccl_backend
  
      assert current_send_device == current_recv_device
      current_device = current_send_device
  
      if (send_dst is not None and send_metadata) or (
          recv_src is not None and metadata_recv is None
      ):
          # Send and receive metadata
          _metadata_recv = _send_recv_serialization_object(
              object=metadata_send,
              send_dst=send_dst if send_metadata else None,
              recv_src=recv_src if metadata_recv is None else None,
              send_group=send_group if send_metadata else None,
              recv_group=recv_group if metadata_recv is None else None,
              current_device=current_device,
              is_nccl_backend=is_nccl_backend,
          )
          assert metadata_recv is None or _metadata_recv is None
          metadata_recv = (
              _metadata_recv if metadata_recv is None else metadata_recv
          )
  
      # Send and receive data
      recv_tensor_metadata = (
          None
          if metadata_recv is None
          else metadata_recv.tensor_metadata
      )
      recv_tensor_objs = _batch_send_recv_tensor(
          tensor_objs,
          recv_tensor_metadata,
          send_dst,
          recv_src,
          send_group,
          recv_group,
          current_device,
      )
  
      if metadata_recv is not None:
          assert isinstance(metadata_recv, P2PMetadata)
          tree_spec = metadata_recv.tree_spec
          non_tensor_obj_idx = metadata_recv.non_tensor_obj_idx
          non_tensor_objs = metadata_recv.non_tensor_objs
  
          if recv_tensor_objs is None:
              recv_tensor_objs = []
  
          for idx in non_tensor_obj_idx:
              recv_tensor_objs.insert(idx, non_tensor_objs.pop(0))
          recv_object = tree_unflatten(recv_tensor_objs, tree_spec)
  
          return recv_object
  
imports: import io
  import pickle
  import re
  from collections import namedtuple
  from typing import Any, Callable, List, Optional, Tuple, Union
  import torch
  import torch.distributed
  from packaging.version import Version
  from torch.distributed import ProcessGroup
  from torch.distributed import distributed_c10d
  from torch.utils._pytree import tree_flatten, tree_unflatten
  from .stage_manager import PipelineStageManager
label_desc: Use image node_id 10 for calling a global function with example usage: _communicate(object, send_dst, recv_src, send_group, recv_group, send_metadata, metadata_recv, send_prior_fallback) and returns: recv_object, _communicate, recv_data