x_train = x_train.reshape(-1, 28, 28, 1)
x_test = x_test.reshape(-1, 28, 28, 1)
x_train = x_train / 255
x_test = x_test /255

from keras.preprocessing.image import ImageDataGenerator
img_gen = ImageDataGenerator(
    rescale=1./255,
    horizontal_flip=False
    )

x_train = x_train.reshape(-1, 28, 28, 1)
x_test = x_test.reshape(-1, 28, 28, 1)


from keras.preprocessing.image import ImageDataGenerator
img_gen = ImageDataGenerator(
    rescale=1./255,
    horizontal_flip=False
    )

History = Resnet34_model.fit_generator(img_gen.flow(x_train*255, y_train, batch_size = 16),
                                      steps_per_epoch = len(x_train)/16, validation_data = (x_test,y_test), epochs = 5 )