How can I get the symbolic gradient [Tensorflow 2.x]

Question

I want to get the symbolic expression for gradient estimation. When I see the output it's quite difficult to understand what's going on.

import tensorflow as tf
@tf.function
def f_k(input_dat):
    y = tf.matmul(tf.sin(input_dat[0]), input_dat[1])
    grads = tf.gradients([y], input_dat)
    # grads = tape.gradient([y], input_dat)
    tf.print('tf >>', grads)
    print('print >>', grads)
    return y, grads


a = tf.Variable([[1., 3.0], [2., 6.0]])
b = tf.Variable([[1.], [2.]])
input_data = [a, b]
y, z = f_k(input_data)
print(y, z)

Output: inside the function

print >> [<tf.Tensor 'gradients/Sin_grad/mul:0' shape=(2, 2) dtype=float32>, <tf.Tensor 'gradients/MatMul_grad/MatMul_1:0' shape=(2, 1) dtype=float32>]
tf >> [[[0.540302277 -1.979985]
 [-0.416146845 1.92034054]], [[1.75076842]
 [-0.138295487]]

As the output, I want which is shown with print:

[<tf.Tensor 'gradients/Sin_grad/mul:0' shape=(2, 2) dtype=float32>, <tf.Tensor 'gradients/MatMul_grad/MatMul_1:0' shape=(2, 1) dtype=float32>]

However, the function always returns the numerical result. Could someone help me to get this symbolic representation of the gradient?