code: def check_params(self, params):
      if isinstance(params, TorchModule) or isinstance(
          params, Sequential
      ):
          params.add_optimizer(self)
          params = params.parameters()
      else:
          params = params
  
      l_param = list(params)
      if len(l_param) == 0:
          # fake parameters, for the case that there are only cust model
          return [t.nn.Parameter(t.Tensor([0]))]
  
      return l_param
  
imports: import torch
  from fate.components.components.nn.loader import Loader
  from torch.nn import Sequential
  import json
label_desc: Use image node_id 3 for calling the TorchOptimizer obj's underlying member method code with example usage: obj.check_params(params) and returns: l_param, list