code: def all_gather(tensors):
      """
      All gathers the provided tensors from all processes across machines.
      Args:
          tensors (list): tensors to perform all gather across all processes in
          all machines.
      """
  
      gather_list = []
      output_tensor = []
      world_size = dist.get_world_size()
      for tensor in tensors:
          tensor_placeholder = [
              torch.ones_like(tensor) for _ in range(world_size)
          ]
          dist.all_gather(tensor_placeholder, tensor, async_op=False)
          gather_list.append(tensor_placeholder)
      for gathered_tensor in gather_list:
          output_tensor.append(torch.cat(gathered_tensor, dim=0))
      return output_tensor
  
imports: import functools
  import logging
  import pickle
  import torch
  import torch.distributed
  from pytorchvideo.layers.distributed import cat_all_gather, get_local_process_group, get_local_rank, get_local_size, get_world_size, init_distributed_training
label_desc: Use image node_id 2 for calling a global function with example usage: all_gather(tensors) and returns: output_tensor