code: def predict_with_uncertainty(self, x, n_iter=100):
      result = np.zeros(
          (n_iter,) + (x.shape[0], self.config["output_feature_num"])
      )
      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 torch
  from torch.utils.data import TensorDataset, DataLoader
  import types
  import numpy
  import math
  import pandas
  import tempfile
  import os
  from zoo.orca.automl.model.abstract import BaseModel, ModelBuilder
  from zoo.orca.automl.metrics import Evaluator
  from zoo.orca.automl.pytorch_utils import LR_NAME, DEFAULT_LR
label_desc: Use image node_id 16 for calling the PytorchBaseModel obj's underlying member method code with example usage: obj.predict_with_uncertainty(x, n_iter) and returns: prediction,  uncertainty