code: def test_noncentral_chi2_log_pdf(self):
      batch_size = 7
      df_v = 2.0
      nc_v = 3.0
      df = tf.constant([df_v] * batch_size, dtype=tf.float64)
      nc = tf.constant([nc_v] * batch_size, dtype=tf.float64)
  
      x = np.array(
          [2.5, 2.5, 4.0, 0.1, 1.0, 2.0, 10.0], dtype=np.float64
      )
  
      nc_chi2 = noncentral_chi2.NoncentralChi2(df, nc)
  
      expected_log_pdf = stats.ncx2.logpdf(x, df=df_v, nc=nc_v)
  
      log_pdf = nc_chi2.log_prob(x)
  
      self.assertEqual(log_pdf.shape, (7,))
      self.assertAllClose(self.evaluate(log_pdf), expected_log_pdf)
  
      pdf = nc_chi2.prob(x)
      self.assertEqual(pdf.shape, (7,))
      self.assertAllClose(self.evaluate(pdf), np.exp(expected_log_pdf))
  
imports: from absl.testing import parameterized
  import numpy
  from scipy import stats
  import tensorflow
  from tensorflow_probability.python.distributions import noncentral_chi2
  from tensorflow_probability.python.distributions.internal import statistical_testing
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the NoncentralChi2Test obj's underlying member method code with example usage: obj.test_noncentral_chi2_log_pdf() without return types