text: # to check if the tensorflow model is saved in separate file we try to run it for
  # predictions and check a single case
  import tensorflow as tf
  import matplotlib.pyplot as plt
  import numpy as np
  # To disable the the warning, doesn't enable AVX/FMA
  import os
  os.environ['TF_CPP_MIN_LOG_LEVEL'] = '2'
  
  
  # use a template dataset from keras api - it's kind of "hello world" example for ML
  mnist = tf.keras.datasets.mnist  # 28x28 images of hand written digits 0-9
  # load dataset to test and train sets (use only test set!)
  (x_train, y_train), (x_test, y_test) = mnist.load_data()
  # load saved model
  saved_model = tf.keras.models.load_model("simple_num_reader.model")
  # using the test dataset we use the new_model (loaded one) and run for all of the x_test data (inputs)
  test_predictions = saved_model.predict([x_test])
  # use numpy to get a single case from predictions and run it against the picture itself (using matplotlib)
  # show image
  plt.imshow(x_test[15])
  plt.show()
  # check prediction
  print(np.argmax(test_predictions[15]))
  