code: def data():
      (x_train, y_train), (x_test, y_test) = mnist.load_data()
      x_train = x_train.reshape(60000, 784)
      x_test = x_test.reshape(10000, 784)
      x_train = x_train.astype("float32")
      x_test = x_test.astype("float32")
      x_train /= 255
      x_test /= 255
      nb_classes = 10
      y_train = np_utils.to_categorical(y_train, nb_classes)
      y_test = np_utils.to_categorical(y_test, nb_classes)
      return x_train, y_train, x_test, y_test
  
file_path: hyperas/tests/test_lr_plateau.py
imports: from __future__ import print_function
  from hyperopt import Trials, STATUS_OK, tpe
  from hyperas import optim
  from hyperas.distributions import choice
  from keras.models import Sequential
  from keras.layers import Dense, Activation
  from keras.datasets import mnist
  from keras.utils import np_utils
  from keras.callbacks import ReduceLROnPlateau, EarlyStopping
label_desc: Use image node_id 1 for calling a global function with example usage: data() and returns: x_train,  y_train,  x_test,  y_test