code: def testMean(self):
      samples = [
          [0, 1, 1, 2],
          [[0, 0, 0, 1], [0, 1, 1, 2]],
          [[[0, 0], [1, 1]], [[0, 1], [0, 2]]],
      ]
      expected_means = [1.0, [0.25, 1], [[0, 1], [0.5, 1]]]
  
      for sample, expected_mean in zip(samples, expected_means):
          input_ = tf.convert_to_tensor(value=sample, dtype=np.float32)
          input_ph = tf1.placeholder_with_default(
              input_, shape=input_.shape if self.static_shape else None
          )
          dist = empirical.Empirical(
              samples=input_ph, validate_args=True
          )
          self.assertAllClose(self.evaluate(dist.mean()), expected_mean)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import empirical
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 9 for calling the EmpiricalScalarTest obj's underlying member method code with example usage: obj.testMean() without return types