如何在keras/tensorflow中使用多线程来拟合模型？

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
from tensorflow.keras.optimizers import Adam
from tensorflow.keras.utils import multi_gpu_model
from tensorflow.keras.preprocessing.image import ImageDataGenerator

model = Sequential()
model.add(Dense(64, activation='relu', input_dim=100))
model.add(Dense(64, activation='relu'))
model.add(Dense(1, activation='sigmoid'))

model.compile(optimizer=Adam(), loss='binary_crossentropy', metrics=['accuracy'])

datagen = ImageDataGenerator(rescale=1./255)
train_generator = datagen.flow_from_directory(
        'train_data_directory',
        target_size=(150, 150),
        batch_size=32,
        class_mode='binary')

model.fit_generator(
        train_generator,
        steps_per_epoch=2000,
        epochs=50,
        workers=4,
        use_multiprocessing=True)