code: def test_predict_different_inputs(self):
      pnnet = algorithms.PNN(std=0.1, verbose=False)
  
      data = np.array([[1, 2, 3]]).T
      target = np.array([[1, 0, 1]]).T
  
      pnnet.train(data, target)
      self.assertInvalidVectorPred(
          pnnet, data.ravel(), target.ravel(), decimal=2
      )
  
file_path: neupy/tests/algorithms/rbfn/test_pnn.py
imports: from __future__ import division
  import numpy
  from sklearn import datasets
  from sklearn import metrics
  from sklearn.model_selection import StratifiedKFold, train_test_split
  from neupy import algorithms
  from neupy.exceptions import NotTrained
  from base import BaseTestCase
label_desc: Use image node_id 6 for calling the PNNTestCase obj's underlying member method code with example usage: obj.test_predict_different_inputs() without return types