我創建了一個DataGenerator(Sequence)定義batch_size,batch_x和 的類batch_y。batch_x是一批圖像（來自x_set，圖像的文件路徑列表），由 讀入imread，調整大小resize并除以 255 以獲得 0 到 1 之間的值。batch_y這些圖像的標簽來自y_set，a包含所有標簽的列表。class DataGenerator(Sequence):    def __init__(self, x_set, y_set, batch_size):        self.x, self.y = x_set, y_set        self.batch_size = batch_size    def __len__(self):        return math.ceil(len(self.x) / self.batch_size)    def __getitem__(self, idx):        batch_x = self.x[idx*self.batch_size : (idx + 1)*self.batch_size]        batch_x = np.array([resize(imread(file_name), (64, 128)) for file_name in batch_x])        batch_x = batch_x * 1./255        batch_y = self.y[idx*self.batch_size : (idx + 1)*self.batch_size]        batch_y = np.array(batch_y)        return batch_x, batch_y因為這個生成器可以工作但在 Colab 上需要很長時間，所以我之前調整了圖像的大小。因此，這不再是必需的，我現在想修改DataGenerator并保留該resize功能。這是我的代碼DataGenerator_withoutresize(Sequence)：class DataGenerator_withoutresize(Sequence):    def __init__(self, x_set, y_set, batch_size):        self.x, self.y = x_set, y_set        self.batch_size = batch_size    def __len__(self):        return math.ceil(len(self.x) / self.batch_size)    def __getitem__(self, idx):        batch_x = self.x[idx*self.batch_size : (idx + 1)*self.batch_size]        batch_x = np.array([(imread(file_name) for file_name in batch_x])        batch_x = batch_x * 1./255        batch_y = self.y[idx*self.batch_size : (idx + 1)*self.batch_size]        batch_y = np.array(batch_y)        return batch_x, batch_y這段代碼正確嗎？