code: def multilayer_fully_connected(images, labels):
    
    # Pretty Tensor is a thin wrapper on Tensors.
    # Change this method to experiment with other architectures
    images = pt.wrap(images)
    with pt.defaults_scope(activation_fn=tf.nn.relu, l2loss=0.00001):
      return (images.flatten().fully_connected(100).fully_connected(100)
              .softmax_classifier(10, labels))
docs: Creates a multi layer network of fully_connected layers.
  
    Each layer is 100 neurons.  Please change this to experiment with
    architectures.
  
    Args:
      images: The input images.
      labels: The labels as dense one-hot vectors.
    Returns:
      A softmax result.