code: def test_placeholder_num_iters(self):
      iters = 10
      n = tf1.placeholder_with_default(np.int64(iters), shape=())
      counter = collections.Counter()
  
      def body(x):
          counter["body_calls"] += 1
          return [x + 1]
  
      result = loop_util.smart_for_loop(
          loop_num_iter=n,
          body_fn=body,
          initial_loop_vars=[tf.constant(1)],
      )
      if (
          tf.executing_eagerly() and not JAX_MODE
      ):  # JAX always traces loops
          self.assertEqual(iters, counter["body_calls"])
      else:
          self.assertEqual(1, counter["body_calls"])
      self.assertAllClose([11], self.evaluate(result))
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import collections
  from absl.testing import parameterized
  import numpy
  import tensorflow.compat.v1
  import tensorflow.compat.v2
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.internal import auto_composite_tensor
  from tensorflow_probability.python.internal import loop_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import samplers
  from tensorflow_probability.python.internal import tensorshape_util
  from tensorflow_probability.python.internal import test_util
  from tensorflow_probability.python.math import gradient
label_desc: Use image node_id 2 for calling the SmartForLoopTest obj's underlying member method code with example usage: obj.test_placeholder_num_iters() and returns: list