class_docstr: A wrapper class for existing PyTorch optimizers
class_docstr_tok: ["A","wrapper","class","for","existing","PyTorch","optimizers"]
code: def param_lists(self, v):
      for pg, v_ in zip(self.opt.param_groups, v):
          pg["params"] = v_
  
imports: from __future__ import annotations
  from .torch_basics import *
label_desc: Use image node_id 6 for calling the OptimWrapper obj's underlying member method code with example usage: obj.param_lists(v) without return types