code: def predict_on_batch(self, x):
      self.make_predict_function()
      batch_outputs = self.predict_function([(x,)])
      batch_outputs = tree.map_structure(
          backend.convert_to_numpy, batch_outputs
      )
      return batch_outputs
  
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 12 for calling the NumpyTrainer obj's underlying member method code with example usage: obj.predict_on_batch(x) and returns: batch_outputs