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(dist.get_world_size())
      ]
      dist.all_gather(output, x)
      return tuple(output)
  
file_path: vissl/vissl/utils/distributed_utils.py
imports: from typing import List
  import torch
  import torch.distributed
  from classy_vision.generic.distributed_util import convert_to_distributed_tensor, convert_to_normal_tensor, is_distributed_training_run
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