tf.batch_jacobian Unexpected Behavior

Question

import tensorflow as tf

with tf.GradientTape() as g:
  x = tf.constant([[1., 2.], [3., 4.]], dtype=tf.float32)
  z = tf.constant([[5., 6., 3.], [7., 8., 4.]], dtype=tf.float32)
  g.watch(x)
  g.watch(z)
  y1 = x * x
  y2 = z * z
  y = tf.concat([y1, y2], axis=1)

batch_jacobian = g.batch_jacobian(y, z[:,0:1],unconnected_gradients=tf.UnconnectedGradients.NONE)

The output is zero. If the slicing breaks the graph, then I should get None instead of zero. I am attaching the output here in image form

batch_jacobian = [[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]]