code: def testSamplingDeterministic(self):
      # pyformat: disable
      scale = tf.linalg.LinearOperatorFullMatrix(
          self._input([[2.0, -1.0], [-1.0, 2.0]]), is_non_singular=True
      )
      # pyformat: enable
      seed = test_util.test_seed()
      tf.random.set_seed(seed)
      dist1 = mvst.MultivariateStudentTLinearOperator(
          loc=[1.0, 2.0], df=5.0, scale=scale, validate_args=True
      )
      samples1 = self.evaluate(dist1.sample(100, seed=seed))
      tf.random.set_seed(seed)
      dist2 = mvst.MultivariateStudentTLinearOperator(
          loc=[1.0, 2.0], df=5.0, scale=scale, validate_args=True
      )
      samples2 = self.evaluate(dist2.sample(100, seed=seed))
      self.assertAllClose(samples1, samples2)
  
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 18 for calling the MultivariateStudentTTestFloat32StaticShape obj's underlying member method code with example usage: obj.testSamplingDeterministic() without return types