How to Create High Dimension Matrix Multiplication in TensorFlow

We often do 2 demensions matrix multiplication, such as

A: 2*3
B: 3*4
C = AB
C: 2*4

If

A: 2 * 2 * 3
B: 2 * 3 * 2
C = AB
C: ?

Here is an example:

import tensorflow as tf
import numpy as np

a = tf.constant(np.arange(1,13), shape=[2, 2, 3],dtype=tf.float32)
b = tf.constant(np.arange(13,25), shape=[2, 3, 2],dtype=tf.float32)
c = tf.matmul(a, b)

init = tf.global_variables_initializer()
with tf.Session() as sess:
    sess.run(init)
 
    print('a=', a.eval())
    print('b=', b.eval())
    print('c=', c.eval())

the reuslt is:

('a=', array([[[ 1.,  2.,  3.],
        [ 4.,  5.,  6.]],

       [[ 7.,  8.,  9.],
        [10., 11., 12.]]], dtype=float32))
('b=', array([[[13., 14.],
        [15., 16.],
        [17., 18.]],

       [[19., 20.],
        [21., 22.],
        [23., 24.]]], dtype=float32))
('c=', array([[[ 94., 100.],
        [229., 244.]],

       [[508., 532.],
        [697., 730.]]], dtype=float32))

,