code: def _generate_config(self):
      configs = []
      name = self.name
  
      input_dim = self.descriptors["input"]["dim"]
      input_descriptor = self.descriptors["input"]["final-string"]
      small_dim = self.config["small-dim"]
      big_dim = self.config["big-dim"]
      l2_regularize = self.config["l2-regularize"]
      max_change = self.config["max-change"]
      self_repair_scale = self.config["self-repair-scale"]
  
      # The affine layer, from input-dim to big-dim.
      configs.append(
          "component name={0}.affine type=NaturalGradientAffineComponent "
          "input-dim={1} output-dim={2} l2-regularize={3} max-change={4}".format(
              name, input_dim, big_dim, l2_regularize, max_change
          )
      )
      configs.append(
          "component-node name={0}.affine component={0}.affine "
          "input={1}".format(name, input_descriptor)
      )
  
      # The ReLU layer
      configs.append(
          "component name={0}.relu type=RectifiedLinearComponent dim={1} "
          "self-repair-scale={2}".format(
              name, big_dim, self_repair_scale
          )
      )
      configs.append(
          "component-node name={0}.relu component={0}.relu "
          "input={0}.affine".format(name)
      )
  
      # The first BatchNorm layer
      configs.append(
          "component name={0}.batchnorm1 type=BatchNormComponent "
          "dim={1}".format(name, big_dim)
      )
      configs.append(
          "component-node name={0}.batchnorm1 component={0}.batchnorm1 "
          "input={0}.relu".format(name)
      )
  
      # The linear layer, from big-dim to small-dim, with orthonormal-constraint=-1
      # ("floating" orthonormal constraint).
      configs.append(
          "component name={0}.linear type=LinearComponent "
          "input-dim={1} output-dim={2} l2-regularize={3} max-change={4} "
          "orthonormal-constraint=-1 ".format(
              name, big_dim, small_dim, l2_regularize, max_change
          )
      )
      configs.append(
          "component-node name={0}.linear component={0}.linear "
          "input={0}.batchnorm1".format(name)
      )
  
      # The second BatchNorm layer
      configs.append(
          "component name={0}.batchnorm2 type=BatchNormComponent "
          "dim={1}".format(name, small_dim)
      )
      configs.append(
          "component-node name={0}.batchnorm2 component={0}.batchnorm2 "
          "input={0}.linear".format(name)
      )
  
      return configs
  
imports: from __future__ import print_function
  import math
  import re
  import sys
  from libs.nnet3.xconfig.basic_layers import XconfigLayerBase
label_desc: Use image node_id 8 for calling the XconfigPrefinalLayer obj's underlying member method code with example usage: obj._generate_config() and returns: configs