code: def testHalfCauchyShape(self):
      batch_size = 6
      loc = self._create_placeholder_with_default(
          [0.0] * batch_size, name="loc"
      )
      scale = self._create_placeholder_with_default(
          [1.0] * batch_size, name="scale"
      )
      dist = half_cauchy.HalfCauchy(loc, scale, validate_args=True)
  
      if self.use_static_shape or tf.executing_eagerly():
          expected_batch_shape = tf.TensorShape([batch_size])
      else:
          expected_batch_shape = tf.TensorShape(None)
  
      self.assertEqual(
          self.evaluate(dist.batch_shape_tensor()), (batch_size,)
      )
      self.assertEqual(dist.batch_shape, expected_batch_shape)
      self.assertAllEqual(self.evaluate(dist.event_shape_tensor()), [])
      self.assertEqual(dist.event_shape, tf.TensorShape([]))
  
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 6 for calling the _HalfCauchyTest obj's underlying member method code with example usage: obj.testHalfCauchyShape() without return types