code: def label_to_one_hot_y(y, classes):
      # original .mat files has the 'y' classes labeled from 1 up to 10
      Y = np.zeros(classes)
      Y[y - 1] = 1  # classes labeled from 0 up to 9: one_hot vector y
      return Y
  
file_path: tflearn/tflearn/datasets/svhn.py
imports: from __future__ import print_function
  import numpy
  import scipy.io
  from six.moves import urllib
  import os
label_desc: Use image node_id 4 for calling a global function with example usage: label_to_one_hot_y(y, classes) and returns: Y