code: def testSamplingFullyReparameterized(self):
      df = self._input(2.0)
      loc = self._input([1.0, 2.0])
      diag = self._input([3.0, 4.0])
      _, [grad_df, grad_loc, grad_diag] = gradient.value_and_gradient(
          lambda d, l, s: mvst.MultivariateStudentTLinearOperator(  # pylint: disable=g-long-lambda
              loc=l,
              df=d,
              scale=tf.linalg.LinearOperatorDiag(
                  s, is_non_singular=True
              ),
              validate_args=True,
          ).sample(
              100, seed=test_util.test_seed()
          ),
          [df, loc, diag],
      )
      self.assertIsNotNone(grad_df)
      self.assertIsNotNone(grad_loc)
      self.assertIsNotNone(grad_diag)
  
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 19 for calling the MultivariateStudentTTestFloat32StaticShape obj's underlying member method code with example usage: obj.testSamplingFullyReparameterized() without return types