code: def backward(ctx: Any, output_grad: Tensor) -> Tuple[Tensor, ...]:
      col_parallel_mode = ctx.col_parallel_mode
  
      if ctx.bias:
          grad = reduce_scatter(output_grad, -1, col_parallel_mode)
          return (
              None,
              grad,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
          )
      else:
          reduce_dim = tuple(range(output_grad.ndim - 1))
          reduce = torch.sum(output_grad, dim=reduce_dim)
          grad = reduce_scatter(reduce, -1, col_parallel_mode)
          return (
              output_grad,
              grad,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
              None,
          )
  
imports: from typing import Any, Optional, Tuple
  import torch
  import torch.distributed
  from torch import Tensor
  from torch.cuda.amp import custom_bwd, custom_fwd
  from colossalai.legacy.communication.collective import all_gather, all_reduce, reduce_scatter
  from colossalai.legacy.context.parallel_mode import ParallelMode
  from colossalai.legacy.core import global_context
  from colossalai.utils import get_current_device
label_desc: Use image node_id 2 for calling the _Add_Bias_2D obj's underlying member method code with example usage: obj.backward(ctx, output_grad) and returns: None,  grad,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None, output_grad,  grad,  None,  None,  None,  None,  None,  None,  None,  None,  None,  None