code: def test_on_batch(
      self,
      x,
      y=None,
      sample_weight=None,
      return_dict=False,
  ):
      self._assert_compile_called("test_on_batch")
  
      data = (x, y, sample_weight)
  
      # Maybe build model
      self._symbolic_build(data)
      self.make_test_function()
  
      logs = self.test_function([data])
      logs = tree.map_structure(lambda x: np.array(x), logs)
      if return_dict:
          return logs
      return self._flatten_metrics_in_order(logs)
  
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 11 for calling the NumpyTrainer obj's underlying member method code with example usage: obj.test_on_batch(x, y, sample_weight, return_dict) and returns: self, logs