class_docstr: An autograd function that performs allgather on a tensor.
code: def forward(ctx, tensor, args):
      if args.world_size == 1:
          ctx.rank = args.local_rank
          ctx.batch_size = tensor.shape[0]
          return tensor
      else:
          output = [
              torch.empty_like(tensor) for _ in range(args.world_size)
          ]
          torch.distributed.all_gather(output, tensor)
          ctx.rank = args.local_rank
          ctx.batch_size = tensor.shape[0]
          return torch.cat(output, dim=0)
  
imports: import logging
  import torch
  from torch import nn
  import torch.nn.functional
  import math
label_desc: Use image node_id 1 for calling the AllGather2 obj's underlying member method code with example usage: obj.forward(ctx, tensor, args) and returns: tensor, torch