code: def train_step(self, x, y):
      x = self(x)
      outputs = self.loss_fn(x, y)
      return {"loss": outputs}
  
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 4 for calling the LSTM obj's underlying member method code with example usage: obj.train_step(x, y) and returns: dict