code: def testInverseGammaCDF(self):
      batch_size = 6
      alpha_v = 2.0
      beta_v = 3.0
      alpha = tf.constant([alpha_v] * batch_size)
      beta = tf.constant([beta_v] * batch_size)
      x = np.array([2.5, 2.5, 4.0, 0.1, 1.0, 2.0], dtype=np.float32)
  
      inv_gamma = inverse_gamma.InverseGamma(
          concentration=alpha, scale=beta, validate_args=True
      )
      expected_cdf = stats.invgamma.cdf(x, alpha_v, scale=beta_v)
  
      cdf = inv_gamma.cdf(x)
      self.assertEqual(cdf.shape, (batch_size,))
      self.assertAllClose(self.evaluate(cdf), expected_cdf)
  
imports: import numpy
  from scipy import stats
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import inverse_gamma
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 5 for calling the InverseGammaTest obj's underlying member method code with example usage: obj.testInverseGammaCDF() without return types