code: def get_auto_estimator():
      auto_lstm = AutoLSTM(
          input_feature_num=input_feature_dim,
          output_target_num=output_feature_dim,
          past_seq_len=5,
          optimizer="Adam",
          loss=torch.nn.MSELoss(),
          metric="mse",
          hidden_dim=hp.grid_search([32, 64]),
          layer_num=hp.randint(1, 3),
          lr=hp.choice([0.001, 0.003, 0.01]),
          dropout=hp.uniform(0.1, 0.2),
          logs_dir="/tmp/auto_lstm",
          cpus_per_trial=2,
          name="auto_lstm",
      )
      return auto_lstm
  
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_lstm import AutoLSTM
  from zoo.orca.automl import hp
label_desc: Use image node_id 4 for calling a global function with example usage: get_auto_estimator() and returns: auto_lstm