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.

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