class_docstr: A wrapper class for existing PyTorch optimizers
class_docstr_tok: ["A","wrapper","class","for","existing","PyTorch","optimizers"]
code: def _set_hyper(self, k, v):
      for pg, v_ in zip(self.opt.param_groups, v):
          pg = set_item_pg(pg, self.bwd_map[k], v_)
  
imports: from __future__ import annotations
  from .torch_basics import *
label_desc: Use image node_id 3 for calling the OptimWrapper obj's underlying member method code with example usage: obj._set_hyper(k, v) without return types