code: def testPmfNoBatch(self):
      sample = [
          [[0, 0], [0, 1]],
          [[0, 1], [1, 2]],
          [[0, 1], [1, 2]],
          [[0, 2], [2, 4]],
      ]
      events = [[[0, 0], [0, 1]], [[[0, 1], [1, 2]], [[0, 2], [2, 4]]]]
      expected_pmfs = [0.25, [0.5, 0.25]]
  
      for event, expected_pmf in zip(events, expected_pmfs):
          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, event_ndims=2, validate_args=True
          )
          self.assertAllClose(
              self.evaluate(dist.prob(event)), expected_pmf
          )
          self.assertAllClose(
              self.evaluate(dist.log_prob(event)), np.log(expected_pmf)
          )
  
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 5 for calling the EmpiricalNdTest obj's underlying member method code with example usage: obj.testPmfNoBatch() without return types