code: def testCauchySample(self):
      loc = tf.constant(3.0)
      scale = tf.constant(1.0)
      loc_v = 3.0
      n = tf.constant(100000)
      dist = cauchy.Cauchy(loc=loc, scale=scale, validate_args=True)
      samples = dist.sample(n, seed=test_util.test_seed())
      sample_values = self.evaluate(samples)
  
      self.assertEqual(sample_values.shape, (100000,))
      self.assertAllClose(np.median(sample_values), loc_v, atol=1e-1)
  
      expected_shape = tf.TensorShape([self.evaluate(n)]).concatenate(
          tf.TensorShape(self.evaluate(dist.batch_shape_tensor()))
      )
  
      self.assertAllEqual(expected_shape, samples.shape)
      self.assertAllEqual(expected_shape, sample_values.shape)
  
      expected_shape = tf.TensorShape([self.evaluate(n)]).concatenate(
          dist.batch_shape
      )
  
      self.assertAllEqual(expected_shape, samples.shape)
      self.assertAllEqual(expected_shape, sample_values.shape)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import cauchy
  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 23 for calling the CauchyTest obj's underlying member method code with example usage: obj.testCauchySample() without return types