如何正确使用keras fit_generator

from keras.models import Sequential
from keras.layers import Dense
from keras.preprocessing.image import ImageDataGenerator

# 准备数据生成器
train_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(
        'train_data_directory',
        target_size=(150, 150),
        batch_size=32,
        class_mode='binary')

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

# 编译模型
model.compile(optimizer='rmsprop',
              loss='binary_crossentropy',
              metrics=['accuracy'])

# 调用fit_generator函数进行训练
model.fit_generator(
        train_generator,
        steps_per_epoch=2000,
        epochs=50,
        validation_data=validation_generator,
        validation_steps=800)