code: def one_hot_encoder(y_train, y_test):
      y_train, y_test = asfloat(y_train), asfloat(y_test)
  
      target_scaler = OneHotEncoder(categories="auto", sparse=False)
      y_train = target_scaler.fit_transform(y_train.reshape(-1, 1))
      y_test = target_scaler.transform(y_test.reshape(-1, 1))
  
      return y_train, y_test
  
file_path: neupy/examples/cnn/cifar10_cnn.py
imports: import numpy
  from sklearn import metrics
  from sklearn.preprocessing import OneHotEncoder
  from neupy.layers import *
  from neupy import algorithms
  from neupy.utils import asfloat
  from load_cifar10 import read_cifar10
label_desc: Use image node_id 2 for calling a global function with example usage: one_hot_encoder(y_train, y_test) and returns: y_train,  y_test