For your problem, Tensor returned by Session.run() or tf.eval() is already a NumPy array, except for Sparse tensor, they return Sparse value.
For example:
>>> print(type(tf.Session().run(tf.constant([1,2,3]))))
<class 'numpy.ndarray'>
Or
>>> sess = tf.InteractiveSession()
>>> print(type(tf.constant([1,2,3]).eval()))
<class 'numpy.ndarray'>
Or
>>> sess = tf.Session()
>>> with sess.as_default():
>>> print(type(tf.constant([1,2,3]).eval()))
<class 'numpy.ndarray'>
Hope this answer helps.
If you wish to learn more about Python, visit Python tutorial and Python course by Intellipaat.