code: def predict_with_uncertainty(self, x, n_iter=100):
      result = np.array(
          [self.predict(x, mc=True) for i in range(n_iter)]
      )
      prediction = result.mean(axis=0)
      uncertainty = result.var(axis=0)
      return prediction, uncertainty
  
imports: import pickle
  import numpy
  from tensorflow.keras.models import Model
  from tensorflow.keras.layers import Input, LSTM, Dense
  import tensorflow.keras
  from bigdl.orca.automl.model.abstract import BaseModel
  from bigdl.orca.automl.metrics import Evaluator
label_desc: Use image node_id 13 for calling the LSTMSeq2Seq obj's underlying member method code with example usage: obj.predict_with_uncertainty(x, n_iter) and returns: prediction,  uncertainty