code: def _pre_processing(self, x, validation_data=None):
      long_term, short_term = self._reshape_input_x(x)
      if validation_data:
          val_x, val_y = validation_data
          long_val, short_val = self._reshape_input_x(val_x)
          validation_data = ([long_val, short_val], val_y)
      return [long_term, short_term], validation_data
  
imports: import pickle
  import numpy
  import time
  from tensorflow.keras.models import Model
  from tensorflow.keras.layers import Reshape, Dense, Dropout, Add, Permute, RNN, GRUCell
  from tensorflow.keras.layers import Input, InputSpec, Wrapper, Lambda, Conv2D, multiply, Softmax
  from tensorflow.keras.initializers import TruncatedNormal, Constant
  import tensorflow.keras.backend
  import tensorflow
  from bigdl.chronos.metric.forecast_metrics import Evaluator
label_desc: Use image node_id 7 for calling the MTNetKeras obj's underlying member method code with example usage: obj._pre_processing(x, validation_data) and returns: list,  validation_data