code: def testLogProbSameFor1D(self):
      # 1D MVT is exactly a regular Student's T distribution.
      t_dist = student_t.StudentT(
          df=self._input(5.0),
          loc=self._input(2.0),
          scale=self._input(3.0),
          validate_args=True,
      )
      scale = tf.linalg.LinearOperatorDiag(
          self._input([3.0]), is_non_singular=True
      )
      mvt_dist = mvst.MultivariateStudentTLinearOperator(
          loc=self._input([2.0]),
          df=self._input(5.0),
          scale=scale,
          validate_args=True,
      )
  
      test_points = tf.cast(tf.linspace(-10.0, 10.0, 100), self.dtype)
  
      t_log_probs = self.evaluate(t_dist.log_prob(test_points))
      mvt_log_probs = self.evaluate(
          mvt_dist.log_prob(test_points[..., tf.newaxis])
      )
  
      self.assertAllClose(t_log_probs, mvt_log_probs)
  
imports: from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import exp
  from tensorflow_probability.python.distributions import multivariate_student_t
  from tensorflow_probability.python.distributions import student_t
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
  from tensorflow_probability.python.util import deferred_tensor
label_desc: Use image node_id 23 for calling the MultivariateStudentTTestFloat32StaticShape obj's underlying member method code with example usage: obj.testLogProbSameFor1D() without return types