code: def conv_bn(
      input, filter, ksize, stride, padding, act_type="relu", name=""
  ):
      conv = mx.symbol.Convolution(
          data=input,
          kernel=(ksize, ksize),
          pad=(padding, padding),
          stride=(stride, stride),
          num_filter=filter,
          name=name + "_conv",
      )
      ret = mx.sym.BatchNorm(
          data=conv,
          fix_gamma=False,
          eps=2e-5,
          momentum=0.9,
          name=name + "_bn",
      )
      if act_type is not None:
          ret = mx.symbol.Activation(
              data=ret,
              act_type=act_type,
              name="{}_{}".format(name, act_type),
          )
      return ret
  
file_path: insightface/detection/retinaface/rcnn/symbol/symbol_ssh.py
imports: import mxnet
  import numpy
  from rcnn.config import config
  from rcnn.PY_OP import rpn_fpn_ohem3
label_desc: Use image node_id 4 for calling a global function with example usage: conv_bn(input, filter, ksize, stride, padding, act_type, name) and returns: ret