train_generator.py

from keras.utils import Sequence
import numpy as np

class MySequence(Sequence):
    """Custom Sequence"""
    def __init__(self, x, y, batch_size):
        self.x, self.y = x, y
        self.batch_size = batch_size

    def __len__(self):
        return int(np.ceil(len(self.x) / float(self.batch_size)))

    def __getitem__(self, idx):
        batch_x = self.x[idx * self.batch_size:(idx + 1) * self.batch_size]
        batch_y = self.y[idx * self.batch_size:(idx + 1) * self.batch_size]

        return batch_x, batch_y
       
training_generator = MySequence(train_images, train_labels, batch_size=128)
validation_generator = MySequence(val_images, val_labels, batch_size=128)

network.fit_generator(generator=training_generator, epochs=5, validation_data=validation_generator)