text: """
  The RegNet model.
  
  Ilija Radosavovic, et al., "Designing Network Design Spaces,"
  https://arxiv.org/abs/2003.13678
  """
  
  import torchvision
  from plato.config import Config
  
  
  class Model():
      """The RegNet model."""
      @staticmethod
      def get_model(model_type):
          """Obtaining an instance of the RegNet model."""
  
          # If True, will return a RegNet model pre-trained on ImageNet
          pretrained = Config().trainer.pretrained if hasattr(
              Config().trainer, 'pretrained') else False
  
          if model_type == 'regnet_x_400mf':
              return torchvision.models.regnet_x_400mf(pretrained=pretrained)
          if model_type == 'regnet_x_800mf':
              return torchvision.models.regnet_x_800mf(pretrained=pretrained)
          if model_type == 'regnet_x_1_6gf':
              return torchvision.models.regnet_x_1_6gf(pretrained=pretrained)
          if model_type == 'regnet_x_3_2gf':
              return torchvision.models.regnet_x_3_2gf(pretrained=pretrained)
          if model_type == 'regnet_x_8gf':
              return torchvision.models.regnet_x_8gf(pretrained=pretrained)
          if model_type == 'regnet_x_16gf':
              return torchvision.models.regnet_x_16gf(pretrained=pretrained)
          if model_type == 'regnet_x_32gf':
              return torchvision.models.regnet_x_32gf(pretrained=pretrained)
          if model_type == 'regnet_y_400mf':
              return torchvision.models.regnet_y_400mf(pretrained=pretrained)
          if model_type == 'regnet_y_800mf':
              return torchvision.models.regnet_y_800mf(pretrained=pretrained)
          if model_type == 'regnet_y_1_6gf':
              return torchvision.models.regnet_y_1_6gf(pretrained=pretrained)
          if model_type == 'regnet_y_3_2gf':
              return torchvision.models.regnet_y_3_2gf(pretrained=pretrained)
          if model_type == 'regnet_y_8gf':
              return torchvision.models.regnet_y_8gf(pretrained=pretrained)
          if model_type == 'regnet_y_16gf':
              return torchvision.models.regnet_y_16gf(pretrained=pretrained)
          if model_type == 'regnet_y_32gf':
              return torchvision.models.regnet_y_32gf(pretrained=pretrained)
  