code: def testBadScaleDType(self):
      with self.assertRaisesRegexp(
          TypeError, "`scale` must have floating-point dtype."
      ):
          mvst.MultivariateStudentTLinearOperator(
              loc=[0.0],
              df=1.0,
              scale=tf.linalg.LinearOperatorIdentity(
                  num_rows=1, dtype=tf.int32, is_non_singular=True
              ),
          )
  
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 4 for calling the MultivariateStudentTTestFloat32StaticShape obj's underlying member method code with example usage: obj.testBadScaleDType() without return types