code: def _testParamShapes(self, sample_shape, expected):
      param_shapes = half_normal.HalfNormal.param_shapes(sample_shape)
      scale_shape = param_shapes["scale"]
      self.assertAllEqual(expected, self.evaluate(scale_shape))
      scale = tf.ones(scale_shape)
      self.assertAllEqual(
          expected,
          self.evaluate(
              tf.shape(
                  half_normal.HalfNormal(
                      scale, validate_args=True
                  ).sample(seed=test_util.test_seed())
              )
          ),
      )
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import half_normal
  from tensorflow_probability.python.distributions import kullback_leibler
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 4 for calling the HalfNormalTest obj's underlying member method code with example usage: obj._testParamShapes(sample_shape, expected) without return types