[Python] How does argmax work when given a 3d tensor - tensorflow

I was wondering how does argmax work when given a 3D tensor. I know what happens when it has a 2D tesnor but 3D is confusing me a lot.

Example:

import tensorflow as tf
import numpy as np

sess = tf.Session()

coordinates = np.random.randint(0, 100, size=(3, 3, 2))
coordinates
Out[20]:
array([[[15, 23],
[ 3, 1],
[80, 56]],
[[98, 95],
[97, 82],
[10, 37]],
[[65, 32],
[25, 39],
[54, 68]]])
sess.run([tf.argmax(coordinates, axis=1)])
Out[21]:
[array([[2, 2],
[0, 0],
[0, 2]], dtype=int64)]

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