text: import torch
  import torch.nn as nn
  import imp
  import os
  
  current_path = os.path.abspath(__file__)
  filepath_to_classifier_definition = os.path.join(os.path.dirname(current_path), 'NonLinearClassifier.py')
  NonLinearClassifier = imp.load_source('', filepath_to_classifier_definition).create_model
  
  
  class MClassifier(nn.Module):
      def __init__(self, opts):
          super(MClassifier, self).__init__()
          self.classifiers = nn.ModuleList([NonLinearClassifier(opt) for opt in opts])
          self.num_classifiers = len(opts)
  
      def forward(self, feats):
          assert (len(feats) == self.num_classifiers)
          return [self.classifiers[i](feat) for i, feat in enumerate(feats)]
  
  
  def create_model(opt):
      return MClassifier(opt)
  