code: def test_forecaster_optimize_loader(self):
      train_loader, val_loader, test_loader = create_data(loader=True)
      forecaster = LSTMForecaster(
          past_seq_len=24,
          input_feature_num=2,
          output_feature_num=2,
          hidden_dim=16,
          layer_num=1,
          dropout=0.1,
          loss="mae",
          metrics=["mse"],
          lr=0.01,
      )
      forecaster.fit(train_loader, epochs=2)
      forecaster.optimize(
          train_data=train_loader,
          validation_data=val_loader,
          batch_size=32,
      )
      forecaster.evaluate(val_loader)
      forecaster.predict(test_loader)
  
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 30 for calling the TestChronosModelLSTMForecaster obj's underlying member method code with example usage: obj.test_forecaster_optimize_loader() without return types