code: def gather(data, dst=0, group=None):
      """
      Run gather on arbitrary picklable data (not necessarily tensors).
  
      Args:
          data: any picklable object
          dst (int): destination rank
          group: a torch process group. By default, will use a group which
              contains all ranks on gloo backend.
  
      Returns:
          list[data]: on dst, a list of data gathered from each rank. Otherwise,
              an empty list.
      """
      if get_world_size() == 1:
          return [data]
      if group is None:
          group = _get_global_gloo_group()
      if dist.get_world_size(group=group) == 1:
          return [data]
      rank = dist.get_rank(group=group)
  
      tensor = _serialize_to_tensor(data, group)
      size_list, tensor = _pad_to_largest_tensor(tensor, group)
  
      # receiving Tensor from all ranks
      if rank == dst:
          max_size = max(size_list)
          tensor_list = [
              torch.empty(
                  (max_size,), dtype=torch.uint8, device=tensor.device
              )
              for _ in size_list
          ]
          dist.gather(tensor, tensor_list, dst=dst, group=group)
  
          data_list = []
          for size, tensor in zip(size_list, tensor_list):
              buffer = tensor.cpu().numpy().tobytes()[:size]
              data_list.append(pickle.loads(buffer))
          return data_list
      else:
          dist.gather(tensor, [], dst=dst, group=group)
          return []
  
imports: import functools
  import logging
  import pickle
  import numpy
  import torch
  import torch.distributed
label_desc: Use image node_id 13 for calling a global function with example usage: gather(data, dst, group) and returns: list, list, data_list, list