code: def _conv2d(
      channel,
      kernel,
      padding,
      stride,
      norm_layer=BatchNorm,
      norm_kwargs=None,
  ):
      """A common conv-bn-leakyrelu cell"""
      cell = nn.HybridSequential(prefix="")
      cell.add(
          nn.Conv2D(
              channel,
              kernel_size=kernel,
              strides=stride,
              padding=padding,
              use_bias=False,
          )
      )
      cell.add(
          norm_layer(
              epsilon=1e-5,
              momentum=0.9,
              **({} if norm_kwargs is None else norm_kwargs),
          )
      )
      cell.add(nn.LeakyReLU(0.1))
      return cell
  
file_path: gluon-cv/gluoncv/model_zoo/yolo/darknet.py
imports: from __future__ import absolute_import
  import os
  import mxnet
  from mxnet import gluon
  from mxnet.gluon import nn
  from mxnet.gluon.nn import BatchNorm
label_desc: Use image node_id 1 for calling a global function with example usage: _conv2d(channel, kernel, padding, stride, norm_layer, norm_kwargs) and returns: cell