code: def _test_param_shapes(self, sample_shape, expected):
      param_shapes = half_cauchy.HalfCauchy.param_shapes(sample_shape)
      loc_shape, scale_shape = (
          param_shapes["loc"],
          param_shapes["scale"],
      )
      self.assertAllEqual(expected, self.evaluate(loc_shape))
      self.assertAllEqual(expected, self.evaluate(scale_shape))
      loc = tf.zeros(loc_shape)
      scale = tf.ones(scale_shape)
      self.assertAllEqual(
          expected,
          self.evaluate(
              tf.shape(
                  half_cauchy.HalfCauchy(
                      loc, scale, validate_args=True
                  ).sample(seed=test_util.test_seed())
              )
          ),
      )
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import half_cauchy
  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 _HalfCauchyTest obj's underlying member method code with example usage: obj._test_param_shapes(sample_shape, expected) without return types