code: def _make_nConv(nchan, depth, elu):
      """
      Make depth number of layer(convbnrelu) and don't change the channel
      Add Nonlinearity into the network
      """
      layers = []
      for _ in range(depth):
          layers.append(LUConv(nchan, elu))
      return nn.Sequential(*layers)
  
imports: import os
  import sys
  import paddle
  import paddle.nn
  import numpy
  from inference.ops import DistMaps3D, ScaleLayer, BatchImageNormalize3D
  from paddleseg.utils import utils
label_desc: Use image node_id 2 for calling a global function with example usage: _make_nConv(nchan, depth, elu) and returns: nn