def preprocessing()

in content/advanced/420_kubeflow/kubeflow.files/mnist-tensorflow-docker.py [0:0]

• 12 lines of code
• 2 McCabe index (conditional complexity)

def preprocessing():
  fashion_mnist = keras.datasets.fashion_mnist
  (train_images, train_labels), (test_images, test_labels) = fashion_mnist.load_data()

  # scale the values to 0.0 to 1.0
  train_images = train_images / 255.0
  test_images = test_images / 255.0

  # reshape for feeding into the model
  train_images = train_images.reshape(train_images.shape[0], 28, 28, 1)
  test_images = test_images.reshape(test_images.shape[0], 28, 28, 1)

  class_names = ['T-shirt/top', 'Trouser', 'Pullover', 'Dress', 'Coat',
                'Sandal', 'Shirt', 'Sneaker', 'Bag', 'Ankle boot']

  print('\ntrain_images.shape: {}, of {}'.format(train_images.shape, train_images.dtype))
  print('test_images.shape: {}, of {}'.format(test_images.shape, test_images.dtype))

  return train_images, train_labels, test_images, test_labels