code: def test_predict_evaluation(self):
      auto_seq2seq = get_auto_estimator()
      auto_seq2seq.fit(
          data=train_dataloader_creator(config={"batch_size": 64}),
          epochs=1,
          validation_data=valid_dataloader_creator(
              config={"batch_size": 64}
          ),
          n_sampling=1,
      )
      test_data_x, test_data_y = get_x_y(size=100)
      auto_seq2seq.predict(test_data_x)
      auto_seq2seq.evaluate((test_data_x, test_data_y))
  
imports: from torch.utils.data import Dataset, DataLoader
  import torch
  import numpy
  from unittest import TestCase
  import pytest
  import tempfile
  from zoo.chronos.autots.model.auto_seq2seq import AutoSeq2Seq
  from zoo.orca.automl import hp
label_desc: Use image node_id 5 for calling the TestAutoSeq2Seq obj's underlying member method code with example usage: obj.test_predict_evaluation() without return types