code: def test_lstm_forecaster_tune_fit(self):
      train_data, val_data, _ = create_data()
      import bigdl.nano.automl.hpo.space as space
  
      forecaster = LSTMForecaster(
          past_seq_len=24,
          input_feature_num=2,
          output_feature_num=2,
          hidden_dim=space.Categorical(16, 32, 64),
          layer_num=1,
          dropout=0.1,
          loss="mae",
          metrics=["mse"],
          lr=0.01,
      )
      forecaster.tune(
          train_data,
          val_data,
          epochs=10,
          n_trials=3,
          target_metric="mse",
          direction="minimize",
      )
      forecaster.fit(train_data, epochs=10)
  
imports: import numpy
  import tempfile
  import os
  from bigdl.chronos.utils import LazyImport
  from unittest import TestCase
  import pytest
  from ..None import op_torch, op_distributed, op_inference, op_automl
label_desc: Use image node_id 27 for calling the TestChronosModelLSTMForecaster obj's underlying member method code with example usage: obj.test_lstm_forecaster_tune_fit() without return types