code: def gather_tensor_along_batch_with_backward(tensor, dim=0):
      world_size = get_world_size()
  
      if world_size < 2:
          return tensor
  
      if is_xla():
          tensor_list = XLAGatherLayer.apply(tensor, dim)
          tensor_list = tensor_list.flatten(
              start_dim=dim, end_dim=dim + 1
          )
      else:
          tensor_list = GatherLayer.apply(tensor)
          tensor_list = torch.cat(tensor_list, dim=dim)
      return tensor_list
  
imports: import contextlib
  import logging
  import os
  import pickle
  import socket
  import subprocess
  import warnings
  from itertools import chain
  import torch
  from mmf.common.registry import registry
  from torch import distributed
label_desc: Use image node_id 13 for calling a global function with example usage: gather_tensor_along_batch_with_backward(tensor, dim) and returns: tensor_list, tensor