code: def test_lstm_from_tsdataset(self):
      train, _, test = create_tsdataset(roll=True)
      lstm = LSTMForecaster.from_tsdataset(
          train, hidden_dim=16, layer_num=2
      )
      lstm.fit(train, epochs=2, batch_size=32)
      yhat = lstm.predict(test, batch_size=32)
      test.roll(
          lookback=lstm.model_config["past_seq_len"],
          horizon=lstm.model_config["future_seq_len"],
      )
      _, y_test = test.to_numpy()
      assert yhat.shape == y_test.shape
  
      del lstm
  
      train, _, test = create_tsdataset(roll=False)
      lstm = LSTMForecaster.from_tsdataset(
          train, past_seq_len=24, hidden_dim=16, layer_num=2
      )
      lstm.fit(train, epochs=2, batch_size=32)
      yhat = lstm.predict(test, batch_size=None)
      test.roll(
          lookback=lstm.model_config["past_seq_len"],
          horizon=lstm.model_config["future_seq_len"],
      )
      _, y_test = test.to_numpy()
      assert yhat.shape == y_test.shape
  
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 7 for calling the TestLSTMForecaster obj's underlying member method code with example usage: obj.test_lstm_from_tsdataset() without return types