keras 报错---`validation_steps=None` is only valid for a generator based on the `keras.utils.Sequence

ValueError: `validation_steps=None` is only valid for a generator based on the `keras.utils.Sequence` class. Please specify `validation_steps` or use the `keras.utils.Sequence` class.

提示validation_steps=None is only valid 

说明要赋值给validation_steps

history = model_vgg.fit_generator(
train_generator,
steps_per_epoch=1000,
epochs=epochs,
validation_data=validation_generator,
validation_steps=200,
# 这一句不能省略，否则报错
callbacks=[checkpointer]
)

同样，如果报如下的错误

ValueError: `steps_per_epoch=None` is only valid for a generator based on the `keras.utils.Sequence` class. Please specify `steps_per_epoch` or use the `keras.utils.Sequence` class.
根据提示，需要给steps_per_epoch给一个明确的值

下面有使用fit_generator的例子

from keras.preprocessing.image import ImageDataGenerator
train_datagen = ImageDataGenerator(
rescale=1./255,
shear_range=0.2,
zoom_range=0.2,
horizontal_flip=True)
test_datagen = ImageDataGenerator(rescale=1./255)
train_generator = train_datagen.flow_from_directory(
'data/train',
target_size=(150, 150),
batch_size=32,
class_mode='binary')
validation_generator = test_datagen.flow_from_directory(
'data/validation',
target_size=(150, 150),
batch_size=32,
class_mode='binary')
model.fit_generator(
train_generator,
steps_per_epoch=2000,
epochs=50,
validation_data=validation_generator,
validation_steps=800)

上面的例子来自keras中文社区文档

最后

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