code: def conv_bn_relu(
      input, filter_size, num_filters, strides=(1, 1), init=he_normal()
  ):
      r = conv_bn(input, filter_size, num_filters, strides, init, 1)
      return relu(r)
  
file_path: CNTK/Examples/Image/Classification/ResNet/Python/resnet_models.py
imports: import numpy
  from cntk.initializer import he_normal, normal
  from cntk.layers import AveragePooling, MaxPooling, BatchNormalization, Convolution, Dense
  from cntk.ops import element_times, relu
label_desc: Use image node_id 2 for calling a global function with example usage: conv_bn_relu(input, filter_size, num_filters, strides, init) and returns: relu