code: def all_reduce(
      self, tensor, op=ReduceOp.SUM, group=None, async_op=False
  ):
      use_caching = False
      if use_caching:
          match_id = f"{tensor.size()}-{op}"
          return self.run_collective(
              name="all_reduce_caching",
              tensor=tensor,
              op=op,
              match_id=match_id,
              group=group,
              async_op=async_op,
          )
      else:
          return self.run_collective(
              name="all_reduce",
              tensor=tensor,
              op=op,
              group=group,
              async_op=async_op,
          )
  
imports: import torch
  from deepspeed.accelerator import get_accelerator
  from .reduce_op import ReduceOp
  from .torch import TorchBackend
label_desc: Use image node_id 4 for calling the CCLBackend obj's underlying member method code with example usage: obj.all_reduce(tensor, op, group, async_op) and returns: self, self