code: def extract_module(self, path: str, freeze: bool = True) -> Module:
          
          modules_dict = {path: module for path, module in self.model.named_modules()}
          module = modules_dict.get(path, None)
  
          if not module:
              raise ConfigurationError(f"You asked to transfer module at path {path} from "
                                       f"the model {type(self.model)}. But it's not present.")
          if not isinstance(module, Module):
              raise ConfigurationError(f"The transferred object from model {type(self.model)} at path "
                                       f"{path} is not a PyTorch Module.")
  
          for parameter in module.parameters(): # type: ignore
              parameter.requires_grad_(not freeze)
          return module
docs: This method can be used to load a module from the pretrained model archive.
  
          It is also used implicitly in FromParams based construction. So instead of using standard
          params to construct a module, you can instead load a pretrained module from the model
          archive directly. For eg, instead of using params like {"type": "module_type", ...}, you
          can use the following template::
  
              {
                  "_pretrained": {
                      "archive_file": "../path/to/model.tar.gz",
                      "path": "path.to.module.in.model",
                      "freeze": False
                  }
              }
  
          If you use this feature with FromParams, take care of the following caveat: Call to
          initializer(self) at end of model initializer can potentially wipe the transferred parameters
          by reinitializing them. This can happen if you have setup initializer regex that also
          matches parameters of the transferred module. To safe-guard against this, you can either
          update your initializer regex to prevent conflicting match or add extra initializer::
  
              [
                  [".*transferred_module_name.*", "prevent"]]
              ]
  
          Parameters
          ----------
          path : ``str``, required
              Path of target module to be loaded from the model.
              Eg. "_textfield_embedder.token_embedder_tokens"
          freeze : ``bool``, optional (default=True)
              Whether to freeze the module parameters or not.