code: def test_output(self):
      batch_size = 64
      max_length = 1000
      seed = 2357
      dataset = AssociativeRecallDataset(100, seqlen=13, seed=seed)
      print(dataset[0])
      print(dataset[1])
      print(dataset[2])
  
      datamodule = AssociativeRecallDataModule(seqlen=13, seed=seed)
      datamodule.prepare_data()
      datamodule.setup(stage="fit")
      train_loader = datamodule.train_dataloader()
      val_loader = datamodule.val_dataloader()
      datamodule.setup(stage="test")
      test_loader = datamodule.test_dataloader()
      x, y = next(iter(train_loader))
      print(x, y)
  
imports: import pytest
  import torch
  from src.datamodules.associative_recall import AssociativeRecallDataset, AssociativeRecallDataModule
label_desc: Use image node_id 1 for calling the TestAssociativeRecall obj's underlying member method code with example usage: obj.test_output() without return types