code: def init_hidden(self, x):
      # batch_first
      batch_size = x.shape[0]
      h0 = jt.randn(1, batch_size, self.hidden_size)
      c0 = jt.randn(1, batch_size, self.hidden_size)
  
      return h0, c0
  
imports: import os
  import sys
  import time
  from datasets import load_dataset
  from datasets import DatasetDict
  import jittor
  from jittor import nn, Module
  from jittor.dataset import Dataset
  from fastNLP.core.controllers.trainer import Trainer
  from fastNLP.core.metrics.accuracy import Accuracy
  from fastNLP.core.vocabulary import Vocabulary
  from fastNLP.core.callbacks.progress_callback import RichCallback
  from fastNLP.core.callbacks.callback import Callback
  from fastNLP.core.dataloaders.jittor_dataloader.fdl import JittorDataLoader
label_desc: Use image node_id 2 for calling the LSTM obj's underlying member method code with example usage: obj.init_hidden(x) and returns: h0,  c0