code: def make_test_function(self, force=False):
      if self.test_function is not None and not force:
          return self.test_function
  
      @tf.autograph.experimental.do_not_convert
      def one_step_on_data(data):
          """Runs a single test step on a batch of data."""
          return self.test_step(data)
  
      if not self.run_eagerly and self.jit_compile:
          kwargs = {"jit_compile": True}
          if self._supports_reduce_retracing:
              kwargs.update({"reduce_retracing": True})
          one_step_on_data = tf.function(one_step_on_data, **kwargs)
  
      @tf.autograph.experimental.do_not_convert
      def one_step_on_iterator(iterator):
          """Runs a single test step given a Dataset iterator."""
          data = next(iterator)
          outputs = self.distribute_strategy.run(
              one_step_on_data, args=(data,)
          )
          outputs = reduce_per_replica(
              outputs,
              self.distribute_strategy,
              reduction=self.distribute_reduction_method,
          )
          return outputs
  
      @tf.autograph.experimental.do_not_convert
      def multi_step_on_iterator(iterator):
          for _ in range(self.steps_per_execution):
              outputs = one_step_on_iterator(iterator)
          return outputs
  
      if self.steps_per_execution > 1:
          test_function = multi_step_on_iterator
      else:
          test_function = one_step_on_iterator
  
      if not self.run_eagerly:
          kwargs = {}
          if self._supports_reduce_retracing:
              kwargs.update({"reduce_retracing": True})
          test_function = tf.function(test_function, **kwargs)
  
      self.test_function = test_function
  
imports: import contextlib
  import warnings
  import numpy
  import tensorflow
  import tree
  from packaging.version import Version
  from tensorflow.python.eager import context
  from keras import callbacks
  from keras import metrics
  from keras import optimizers
  from keras.trainers import trainer
  from keras.trainers.data_adapters import data_adapter_utils
  from keras.trainers.epoch_iterator import EpochIterator
  from keras.utils import traceback_utils
label_desc: Use image node_id 9 for calling the TensorFlowTrainer obj's underlying member method code with example usage: obj.make_test_function(force) and returns: self, self, outputs, outputs