code: def make_test_function(self, force=False):
      if self.test_function is not None and not force:
          return self.test_function
  
      def one_test_step(data):
          data = data[0]
          return self.test_step(data)
  
      def multi_test_steps(data):
          for single_step_data in data:
              logs = one_test_step([single_step_data])
          return logs
  
      if self.steps_per_execution > 1:
          test_step = multi_test_steps
      else:
          test_step = one_test_step
  
      self.test_function = test_step
  
imports: import numpy
  import tree
  from keras import backend
  from keras import callbacks
  from keras.backend.common import standardize_dtype
  from keras.backend.common.keras_tensor import KerasTensor
  from keras.backend.numpy.core import is_tensor
  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 4 for calling the NumpyTrainer obj's underlying member method code with example usage: obj.make_test_function(force) and returns: self, self, logs