class_docstr: Conv3x3 and norm.
class_docstr_tok: ["Conv3x3","and","norm","."]
code: def forward(self, x, **kwargs):
      x = self.conv(x, **kwargs)
      if self.bn:
          x = self.bn(x)
      return x
  
imports: import copy
  import math
  from typing import Callable, List, Optional, Sequence, Tuple, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from mmcv.cnn import Scale
  from mmcv.ops.modulated_deform_conv import ModulatedDeformConv2d
  from mmengine.config import ConfigDict
  from mmengine.model import BaseModel
  from mmengine.structures import InstanceData
  from torch import Tensor
  from mmdet.registry import MODELS
  from mmdet.structures.bbox import cat_boxes
  from mmdet.utils import InstanceList, OptInstanceList, reduce_mean
  from ..utils import BertEncoderLayer, VLFuse, filter_scores_and_topk, permute_and_flatten, select_single_mlvl, unpack_gt_instances
  from ..utils.vlfuse_helper import MAX_CLAMP_VALUE
  from .atss_head import ATSSHead
label_desc: Use image node_id 2 for calling the Conv3x3Norm obj's underlying member method code with example usage: obj.forward(x) and returns: x