Validation keras在每N个训练周期后运行验证

Validation keras在每N个训练周期后运行验证,validation,tensorflow,deep-learning,keras,Validation,Tensorflow,Deep Learning,Keras,我正在使用以下功能培训/验证我的模型: model.fit_generator( train_generator, steps_per_epoch=nb_train_samples // batch_size, epochs=epochs, validation_data=validation_generator, validation_steps=nb_validation_samples // batch_size, verbose=2, wo

我正在使用以下功能培训/验证我的模型:

model.fit_generator(
    train_generator,
    steps_per_epoch=nb_train_samples // batch_size,
    epochs=epochs,
    validation_data=validation_generator,
    validation_steps=nb_validation_samples // batch_size,
    verbose=2, workers=12)

上述函数在每个历元运行验证。我的验证数据非常大,所以我希望每N个时代运行一次。我该怎么做?

看起来keras已经用一个新的输入参数
validation\u freq
更新了他们的fit/fit\u生成器,该参数可用于设置评估验证数据的频率。根据文件(自版本2.2.4起):


如果您使用的是TensorFlow:Keras 2.2.4是TensorFlow r1.14的一部分。
fit(x=None, y=None, batch_size=None, epochs=1, verbose=1, callbacks=None, validation_split=0.0, validation_data=None, shuffle=True, class_weight=None, sample_weight=None, initial_epoch=0, steps_per_epoch=None, validation_steps=None, validation_freq=1)
fit_generator(generator, steps_per_epoch=None, epochs=1, verbose=1, callbacks=None, validation_data=None, validation_steps=None, validation_freq=1, class_weight=None, max_queue_size=10, workers=1, use_multiprocessing=False, shuffle=True, initial_epoch=0)