code: def state_dict(self):
      optimizer_state_dict = self.optimizer.state_dict()
      state_all = optimizer_state_dict["state"].get(0, {})
      for k, v in state_all.items():
          if isinstance(v, torch.Tensor):
              state_all[k] = v.tolist()
      dtype = str(self.model_parameter.dtype).split(".", -1)[-1]
      return {
          "l2_penalty": self.l2_penalty,
          "l1_penalty": self.l1_penalty,
          "alpha": self.alpha,
          "optimizer": optimizer_state_dict,
          "method": self.method,
          "optim_param": self.optim_param,
          "model_parameter": self.model_parameter.tolist(),
          "model_parameter_dtype": dtype,
      }
  
imports: import logging
  import numpy
  import torch
label_desc: Use image node_id 6 for calling the Optimizer obj's underlying member method code with example usage: obj.state_dict() and returns: dict