docstr: Tie or clone module weights depending of weither we are using
  TorchScript or not
docstr_tok: ["Tie","or","clone","module","weights","depending","of","weither","we","are","using","TorchScript","or","not"]
code: def _tie_or_clone_weights(self, first_module, second_module):
      """Tie or clone module weights depending of weither we are using
      TorchScript or not
      """
      if self.config.torchscript:
          first_module.weight = nn.Parameter(
              second_module.weight.clone()
          )
      else:
          first_module.weight = second_module.weight
  
imports: import torch
  from mmf.common.registry import registry
  from mmf.models.pythia import Pythia
  from mmf.modules.embeddings import ProjectionEmbedding
  from mmf.utils.transform import transform_to_batch_sequence
  from torch import nn
label_desc: Use image node_id 7 for calling the MMFBert obj's underlying member method code with example usage: obj._tie_or_clone_weights(first_module, second_module) without return types