code: def get_mismatched_param(
      models: Iterable[torch.nn.Module],
      rel_epsilon: Optional[float] = None,
      abs_epsilon: Optional[float] = None,
  ) -> str:
      """
      Return the name of the first mismatched parameter.
      Return an empty string if all the parameters of the modules are identical.
      """
      if rel_epsilon is None and abs_epsilon is not None:
          print(
              "WARNING: rel_epsilon is not specified, abs_epsilon is ignored."
          )
  
      if len(models) <= 1:
          return True
  
      # Verify all models have the same params.
      for model in models[1:]:
          for name, param in models[0].state_dict().items():
              param_here = model.state_dict()[name]
  
              # If epsilon is specified, do approx comparison.
              if rel_epsilon is not None:
                  if abs_epsilon is not None:
                      if not torch.allclose(
                          param,
                          param_here,
                          rtol=rel_epsilon,
                          atol=abs_epsilon,
                      ):
                          return name
                  else:
                      if not torch.allclose(
                          param, param_here, rtol=rel_epsilon
                      ):
                          return name
              else:
                  if not torch.equal(param, param_here):
                      return name
      return ""
  
imports: from typing import Iterable, Optional
  import torch
  from .cuda import Variable, zerovar
label_desc: Use image node_id 2 for calling a global function with example usage: get_mismatched_param(models, rel_epsilon, abs_epsilon) and returns: str, True, name, name, name