code: def quantize_model(self, model):
      """
      quantize a model
      """
      import torch
  
      if self.torch_device == "cpu":
          return torch.quantization.quantize_dynamic(
              model, {torch.nn.Linear}, dtype=torch.qint8
          )
      elif self.torch_device != "cpu":
          return model.half()
  
imports: import warnings
label_desc: Use image node_id 2 for calling the TorchBase obj's underlying member method code with example usage: obj.quantize_model(model) and returns: torch, model