text: from .resnet_preact import resnet18_preact
  from .resnet_preact_bin import resnet18_preact_bin
  import torch, torch.nn as nn
  _model_factory = {
      "resnet18_preact":resnet18_preact,
      "resnet18_preact_bin":resnet18_preact_bin
  }
  
  class Classifier(torch.nn.Module):
      def __init__(self, bin_backbone,num_classes=None):
          super(Classifier,self).__init__()
          self.bin_backbone = bin_backbone
          self.class_fc_bin = nn.Linear(bin_backbone.fc.in_features, num_classes)
      def forward(self,x):
          out_bin = self.bin_backbone(x)
          class_output_bin = self.class_fc_bin(out_bin[-1])
          return [{"logits":class_output_bin}]
  
  def get_model(arch_name, **kwargs):
      kwargs["binarize"] = True
      bin_backbone =  _model_factory[arch_name](**kwargs)
      model = Classifier(bin_backbone, num_classes = kwargs["num_classes"])
      return model