以下代碼允許訓練集的圖像在每個時期結束時旋轉 90°。from skimage.io import imreadfrom skimage.transform import resize, rotateimport numpy as npimport tensorflow as tffrom tensorflow import kerasfrom tensorflow.keras import layersfrom keras.utils import Sequence from keras.models import Sequentialfrom keras.layers import Conv2D, Activation, Flatten, Dense# Model architecture  (dummy)model = Sequential()model.add(Conv2D(32, (3, 3), input_shape=(15, 15, 4)))model.add(Activation('relu'))model.add(Flatten())modl.add(Dense(1))model.add(Activation('sigmoid'))model.compile(loss='binary_crossentropy',              optimizer='rmsprop',              metrics=['accuracy'])# Data iterator class CIFAR10Sequence(Sequence):    def __init__(self, filenames, labels, batch_size):        self.filenames, self.labels = filenames, labels        self.batch_size = batch_size        self.angles = [0,90,180,270]        self.current_angle_idx = 0    # Method to loop throught the available angles    def change_angle(self):      self.current_angle_idx += 1      if self.current_angle_idx >= len(self.angles):        self.current_angle_idx = 0      def __len__(self):        return int(np.ceil(len(self.filenames) / float(self.batch_size)))    # read, resize and rotate the image and return a batch of images    def __getitem__(self, idx):        angle = self.angles[self.current_angle_idx]        print (f"Rotating Angle: {angle}")        batch_x = self.filenames[idx * self.batch_size:(idx + 1) * self.batch_size]        batch_y = self.labels[idx * self.batch_size:(idx + 1) * self.batch_size]        return np.array([            rotate(resize(imread(filename), (15, 15)), angle)               for filename in batch_x]), np.array(batch_y)如何修改代碼以便在每個紀元期間發生圖像的旋轉？換句話說，我如何編寫一個在紀元“結束”時運行的回調，該回調會更改角度值并繼續在同一紀元上進行訓練（而不更改到下一個紀元）？