code: def testMatmul(self):
      a = tf.linalg.LinearOperatorDiag([1.0, 2.0, 3.0])
      b = tf.linalg.LinearOperatorFullMatrix(
          [[2.0, 1.0], [3.0, 2.0], [4.0, 5.0]]
      )
      block = lorb.LinearOperatorRowBlock([a, b])
      c = np.array(
          [
              [1.0, -1.0],
              [2.0, -2.0],
              [3.0, -3.0],
              [4.0, -4.0],
              [5.0, -5.0],
          ]
      ).astype(np.float32)
      expected = self.evaluate(block.matmul(c))
      actual = self.evaluate(
          a.matmul(c[:3, ...]) + b.matmul(c[3:, ...])
      )
      self.assertAllClose(expected, actual)
  
file_path: probability/tensorflow_probability/python/experimental/linalg/linear_operator_row_block_test.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.experimental.linalg import linear_operator_row_block
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 2 for calling the LinearOperatorRowBlockTest obj's underlying member method code with example usage: obj.testMatmul() without return types