code: def test_can_call_with_variable_number_of_args(self):
      def scalar_sum(*args):
          return sum([tf.reshape(x, []) for x in args])
  
      vectorized_sum = vectorization_util.make_rank_polymorphic(
          scalar_sum, core_ndims=0
      )
  
      xs = [
          1.0,
          np.array([3.0, 2.0]).astype(np.float32),
          np.array([[1.0, 2.0], [-4.0, 3.0]]).astype(np.float32),
      ]
      self.assertAllEqual(self.evaluate(vectorized_sum(*xs)), sum(xs))
  
imports: import warnings
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.distributions import poisson
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.internal import vectorization_util
label_desc: Use image node_id 6 for calling the VectorizationTest obj's underlying member method code with example usage: obj.test_can_call_with_variable_number_of_args() and returns: sum