class_docstr: Bidirectional LSTM running over word embeddings.
class_docstr_tok: ["Bidirectional","LSTM","running","over","word","embeddings","."]
code: def save(self, output_path: str):
      with open(
          os.path.join(output_path, "lstm_config.json"), "w"
      ) as fOut:
          json.dump(self.get_config_dict(), fOut, indent=2)
  
      torch.save(
          self.state_dict(),
          os.path.join(output_path, "pytorch_model.bin"),
      )
  
file_path: sentence-transformers/sentence_transformers/models/LSTM.py
imports: import torch
  from torch import nn
  from typing import List
  import os
  import json
label_desc: Use image node_id 5 for calling the LSTM obj's underlying member method code with example usage: obj.save(output_path) without return types