code: def testMode(self):
      samples = [
          [0, 1, 1, 2],
          [0, 1, 1, 1, 2, 2, 3, 4, 5, 9, 11, 11, 11, 11, 11],
          [[0, 0, 1], [0, 1, 1], [2, 2, 2]],
          [[[0, 0, 0, 0], [0, 0, 1, 1]], [[1, 1, 1, 2], [0, 1, 2, 2]]],
      ]
      expected_modes = [1, 11.0, [0, 1, 2], [[0, 0], [1, 2]]]
  
      for sample, expected_mode in zip(samples, expected_modes):
          input_ = tf.convert_to_tensor(value=sample, dtype=np.int32)
          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.mode()), expected_mode)
  
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 10 for calling the EmpiricalScalarTest obj's underlying member method code with example usage: obj.testMode() without return types