code: def conv_bn_layer(
      input,
      ch_out,
      filter_size,
      stride,
      padding,
      act="relu",
      bias_attr=False,
  ):
      tmp = fluid.layers.conv2d(
          input=input,
          filter_size=filter_size,
          num_filters=ch_out,
          stride=stride,
          padding=padding,
          act=None,
          bias_attr=bias_attr,
      )
      return fluid.layers.batch_norm(input=tmp, act=act)
  
imports: from __future__ import division
  from builtins import range
  from builtins import object
  from past.utils import old_div
  import paddle.fluid
  import math
label_desc: Use image node_id 1 for calling a global function with example usage: conv_bn_layer(input, ch_out, filter_size, stride, padding, act, bias_attr) and returns: fluid