code: def testVariableDfAssertions(self):
      df = tf.Variable(1.0)
      loc = tf.constant([[1.0, 1.0]])
      scale_row = tf.linalg.LinearOperatorLowerTriangular(
          tf.eye(1), is_non_singular=True
      )
      scale_column = tf.linalg.LinearOperatorLowerTriangular(
          tf.eye(2), is_non_singular=True
      )
      d = mtlo.MatrixTLinearOperator(
          df, loc, scale_row, scale_column, validate_args=True
      )
      self.evaluate(df.initializer)
      with self.assertRaises(Exception):
          with tf.control_dependencies([df.assign(-1.0)]):
              self.evaluate(d.sample(seed=test_util.test_seed()))
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import shift
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.bijectors import transform_diagonal
  from tensorflow_probability.python.distributions import matrix_t_linear_operator
  from tensorflow_probability.python.distributions import multivariate_student_t
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 10 for calling the _MatrixTTest obj's underlying member method code with example usage: obj.testVariableDfAssertions() without return types