class_docstr: Transfer the input into 16 channels + tiled input
class_docstr_tok: ["Transfer","the","input","into","16","channels","+","tiled","input"]
code: def __init__(self, in_channels, elu):
      super(InputTransition, self).__init__()
      self.num_features = 16
      self.in_channels = in_channels
  
      self.conv1 = nn.Conv3D(
          self.in_channels, self.num_features, kernel_size=5, padding=2
      )
  
      self.bn1 = nn.BatchNorm3D(self.num_features)
  
      self.relu1 = nn.ELU() if elu else nn.PReLU(self.num_features)
  
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 1 to create a new InputTransition object from inherited base classes: nn with example: obj = InputTransition(in_channels, elu)