class_docstr: A wrapper class for existing PyTorch optimizers
class_docstr_tok: ["A","wrapper","class","for","existing","PyTorch","optimizers"]
code: def hypers(self):
      return [
          {
              self.fwd_map.get(k, k): v
              for k, v in detuplify_pg(pg).items()
              if k != "params"
          }
          for pg in self.opt.param_groups
      ]
  
imports: from __future__ import annotations
  from .torch_basics import *
label_desc: Use image node_id 2 for calling the OptimWrapper obj's underlying member method code with example usage: obj.hypers() and returns: unknown