code: def shortcut(input, ch_out, stride):
      if input.num_filters != ch_out:
          return conv_bn_layer(
              input, ch_out, 1, stride, 0, paddle.activation.Linear()
          )
      else:
          return input
  
file_path: MMdnn/mmdnn/conversion/examples/paddle/models/resnet.py
imports: import paddle.v2
label_desc: Use image node_id 2 for calling a global function with example usage: shortcut(input, ch_out, stride) and returns: conv_bn_layer, input