def METHOD_NAME(x):
    world_size = torch.distributed.get_world_size()
    if world_size > 1:
        rank = torch.distributed.get_rank()
        x_list = [torch.ones_like(x) for _ in range(world_size)]
        torch.distributed.METHOD_NAME(x_list, x.contiguous())
        # remove curr rank
        x_list.pop(rank)
        return torch.cat(x_list, dim=0)
    return None