code: def test_empirical_quantiles(self):
      samples = [
          [1, 1, 1, 2, 3, 3, 3],
          [[1.0, 1.1, 1.2, 1.3, 1.4], [2.0, 2.1, 2.2, 2.3, 2.4]],
      ]
  
      expected_quantiles = {0.5: [2, [1.2, 2.2]], 0.75: [3, [1.3, 2.3]]}
  
      for q, q_vals in expected_quantiles.items():
          for sample, q_val in zip(samples, q_vals):
              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 for _ in input_.shape],
              )
              dist = empirical.Empirical(
                  samples=input_ph, validate_args=True
              )
              self.assertAllClose(
                  self.evaluate(dist.quantile(q)), q_val
              )
  
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 12 for calling the EmpiricalScalarTest obj's underlying member method code with example usage: obj.test_empirical_quantiles() without return types