code: def test_unroll_threshold(self):
      iters = 50
      counter = collections.Counter()
  
      def body(x):
          counter["body_calls"] += 1
          return [x + 1]
  
      result = loop_util.smart_for_loop(
          loop_num_iter=iters,
          body_fn=body,
          initial_loop_vars=[tf.constant(1)],
          unroll_threshold=iters,
      )
      if JAX_MODE:  # JAX always traces loop bodies exactly once
          self.assertEqual(1, counter["body_calls"])
      else:
          self.assertEqual(iters, counter["body_calls"])
      self.assertAllClose([iters + 1], 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 3 for calling the SmartForLoopTest obj's underlying member method code with example usage: obj.test_unroll_threshold() and returns: list