code: def model_creator(config):
      model = LSTMSeq2Seq(
          input_feature_num=config["input_feature_num"],
          output_feature_num=config["output_feature_num"],
          future_seq_len=config["future_seq_len"],
          lstm_hidden_dim=config.get("lstm_hidden_dim", 128),
          lstm_layer_num=config.get("lstm_layer_num", 2),
          dropout=config.get("dropout", 0.25),
          teacher_forcing=config.get("teacher_forcing", False),
      )
      learning_rate = config.get("lr", 1e-3)
      model.compile(
          optimizer=getattr(
              tf.keras.optimizers, config.get("optim", "Adam")
          )(learning_rate),
          loss=config.get("loss", "mse"),
          metrics=[config.get("metics", "mse")],
      )
      return model
  
imports: import numpy
  import tensorflow
  from tensorflow.keras import backend
  from bigdl.nano.tf.keras import Model
  from tensorflow.keras.layers import LSTM, Dense, Lambda, Reshape, Layer, Input
label_desc: Use image node_id 1 for calling a global function with example usage: model_creator(config) and returns: model