code: def testTwoObservations(self):
      concentration = 16.0
      scale = 4.0
      distribution = inverse_gamma.InverseGamma(
          concentration=concentration, scale=scale
      )
      posterior_distribution = sample_parameters.normal_scale_posterior_inverse_gamma_conjugate(
          distribution, observations=tf.constant([10.0, 4.0])
      )
      self.assertAllEqual(
          concentration + 1,  # Add half the number of observations
          posterior_distribution.distribution.concentration,
      )
      self.assertAllEqual(
          scale + 58,  # Add half the square of observations sum.
          posterior_distribution.distribution.scale,
      )
  
file_path: probability/tensorflow_probability/python/experimental/sts_gibbs/sample_parameters_test.py
imports: import tensorflow
  from tensorflow_probability.python.bijectors import invert
  from tensorflow_probability.python.bijectors import square
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.distributions import transformed_distribution
  from tensorflow_probability.python.experimental.sts_gibbs import sample_parameters
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 3 for calling the NormalScalePosteriorInverseGammaConjugate obj's underlying member method code with example usage: obj.testTwoObservations() without return types