class_docstr: Transfer the input into 16 channels + tiled input
class_docstr_tok: ["Transfer","the","input","into","16","channels","+","tiled","input"]
code: def forward(self, x):
      out = self.conv1(x)
      repeat_rate = int(self.num_features / self.in_channels)
      out = self.bn1(out)
      x_tile = x.tile([1, repeat_rate, 1, 1, 1])
      return self.relu1(paddle.add(out, x_tile))
  
imports: import os
  import sys
  import paddle
  import paddle.nn
  import paddle.nn.functional
  from medicalseg.cvlibs import manager
  from medicalseg.utils import utils
label_desc: Use image node_id 2 for calling the InputTransition obj's underlying member method code with example usage: obj.forward(x) and returns: self