code: def load_state_dict(self, state_dict):
      self.l2_penalty = state_dict["l2_penalty"]
      self.l1_penalty = state_dict["l1_penalty"]
      self.alpha = state_dict["alpha"]
      self.method = state_dict["method"]
      self.optim_param = state_dict["optim_param"]
      dtype = state_dict["model_parameter_dtype"]
      self.init_optimizer(
          model_parameter=torch.nn.parameter.Parameter(
              torch.tensor(
                  state_dict["model_parameter"],
                  dtype=getattr(torch, dtype),
              )
          )
      )
      state = state_dict["optimizer"]
      state_all = state["state"].get(0, {})
      for k, v in state_all.items():
          if isinstance(v, list):
              state_all[k] = torch.tensor(v)
      self.optimizer.load_state_dict(state_dict["optimizer"])
  
imports: import logging
  import numpy
  import torch
label_desc: Use image node_id 7 for calling the Optimizer obj's underlying member method code with example usage: obj.load_state_dict(state_dict) without return types