code: def _testParamShapes(self, sample_shape, expected):
      param_shapes = johnson_su.JohnsonSU.param_shapes(sample_shape)
      skewness_shape, tailweight_shape, mu_shape, sigma_shape = (
          param_shapes["skewness"],
          param_shapes["tailweight"],
          param_shapes["loc"],
          param_shapes["scale"],
      )
      self.assertAllEqual(expected, self.evaluate(skewness_shape))
      self.assertAllEqual(expected, self.evaluate(tailweight_shape))
      self.assertAllEqual(expected, self.evaluate(mu_shape))
      self.assertAllEqual(expected, self.evaluate(sigma_shape))
      skewness = tf.zeros(skewness_shape)
      tailweight = tf.ones(tailweight_shape)
      mu = tf.zeros(mu_shape)
      sigma = tf.ones(sigma_shape)
      self.assertAllEqual(
          expected,
          self.evaluate(
              tf.shape(
                  johnson_su.JohnsonSU(
                      skewness,
                      tailweight,
                      mu,
                      sigma,
                      validate_args=True,
                  ).sample(seed=test_util.test_seed())
              )
          ),
      )
  
imports: import math
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import johnson_su
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the JohnsonSUTest obj's underlying member method code with example usage: obj._testParamShapes(sample_shape, expected) without return types