code: def testAInvUpdateEmptyObservations(self, batch_size, context_dim):
      del batch_size  # unused
      a_array = 2 * np.eye(context_dim) + np.array(
          range(context_dim * context_dim)
      ).reshape((context_dim, context_dim))
      a_array = a_array + a_array.T
      a_inv_array = np.linalg.inv(a_array)
      expected_a_inv_update_array = np.zeros(
          [context_dim, context_dim], dtype=np.float32
      )
  
      a_inv = tf.constant(
          a_inv_array,
          dtype=tf.float32,
          shape=[context_dim, context_dim],
      )
      x = tf.constant([], dtype=tf.float32, shape=[0, context_dim])
      a_inv_update = linalg.update_inverse(a_inv, x)
      self.assertAllClose(
          expected_a_inv_update_array, self.evaluate(a_inv_update)
      )
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.bandits.policies import linalg
label_desc: Use image node_id 2 for calling the LinalgTest obj's underlying member method code with example usage: obj.testAInvUpdateEmptyObservations(batch_size, context_dim) without return types