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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def multilayer_fully_connected(images, labels):
 """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. """

  # 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))