code: def testGradientNumBodyCalls(self):
      counter = collections.Counter()
  
      dtype = np.float32
  
      def fn(x, y):
          counter["body_calls"] += 1
          return x**2 + y**2
  
      fn_args = [dtype(3), dtype(3)]
      # Convert function input to a list of tensors.
      fn_args = [tf.convert_to_tensor(value=arg) for arg in fn_args]
      util.maybe_call_fn_and_grads(fn, fn_args)
      expected_num_calls = (
          1 if JAX_MODE or not tf.executing_eagerly() else 2
      )
      self.assertEqual(expected_num_calls, counter["body_calls"])
  
imports: import collections
  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 mvn_tril
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.mcmc.internal import util
label_desc: Use image node_id 5 for calling the GradientTest obj's underlying member method code with example usage: obj.testGradientNumBodyCalls() and returns: unknown