class_docstr: Gather tensors from all workers with support for backward propagation:
  This implementation does not cut the gradients as torch.distributed.all_gather does.
code: def forward(ctx, x):
      output = [
          torch.zeros_like(x)
          for _ in range(torch.distributed.get_world_size())
      ]
      torch.distributed.all_gather(output, x)
      return tuple(output)
  
imports: import logging
  import os
  import numpy
  import torch
  import torch.nn
  from lavis.common.dist_utils import download_cached_file, is_dist_avail_and_initialized
  from lavis.common.utils import get_abs_path, is_url
  from omegaconf import OmegaConf
label_desc: Use image node_id 1 for calling the GatherLayer obj's underlying member method code with example usage: obj.forward(ctx, x) and returns: tuple