code: def test_seq2seq_forecaster_evaluate(self):
      train_tsdata, _, test_tsdata = create_tsdataset()
      forecaster = Seq2SeqForecaster.from_tsdataset(
          train_tsdata,
          past_seq_len=24,
          future_seq_len=2,
          lstm_hidden_dim=16,
          lstm_layer_num=2,
      )
      forecaster.fit(train_tsdata, epochs=1, batch_size=32)
  
      # tf dataset
      test = test_tsdata.to_tf_dataset(batch_size=32)
      metrics = forecaster.evaluate(test, multioutput="uniform_average")
  
      # TSDataset
      metrics_tsdata = forecaster.evaluate(
          test_tsdata, multioutput="uniform_average"
      )
      np.testing.assert_almost_equal(metrics, metrics_tsdata, decimal=5)
  
      # numpy
      test_data = test_tsdata.to_numpy()
      metrics_data = forecaster.evaluate(
          test_data, multioutput="uniform_average"
      )
      np.testing.assert_almost_equal(
          metrics_data, metrics_tsdata, decimal=5
      )
  
imports: import pytest
  import tempfile
  import os
  from unittest import TestCase
  import numpy
  from bigdl.chronos.utils import LazyImport
  from test.bigdl.chronos import op_tf2, op_distributed
label_desc: Use image node_id 4 for calling the TestSeq2SeqForecaster obj's underlying member method code with example usage: obj.test_seq2seq_forecaster_evaluate() without return types