code: def predict_with_uncertainty(self, x, n_iter=100):
      result = np.zeros((n_iter,) + (x.shape[0], self.output_dim))
  
      for i in range(n_iter):
          result[i, :, :] = self.predict(x, mc=True)
  
      prediction = result.mean(axis=0)
      uncertainty = result.std(axis=0)
      return prediction, uncertainty
  
imports: import pickle
  import numpy
  import time
  from tensorflow.keras.models import Model
  from tensorflow.keras.layers import *
  from tensorflow.keras.initializers import TruncatedNormal, Constant
  import tensorflow.keras.backend
  import tensorflow
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.model.abstract import BaseModel
label_desc: Use image node_id 13 for calling the MTNetKeras obj's underlying member method code with example usage: obj.predict_with_uncertainty(x, n_iter) and returns: prediction,  uncertainty