Keras ImageDataGenerator验证数据

Question

在这里无法真正发现错误。 关键要求： extendeded_images和val_data_gen是keras.preprocessing.image.ImageDataGenerator函数。

model = Sequential()
model.add(Conv2D(filters=64, kernel_size=(3,3), strides=(1,1), activation='relu', input_shape=(32,32,3)))
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Conv2D(filters=64, kernel_size=(3,3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Conv2D(filters=64, kernel_size=(3,3), strides=(1,1), activation='relu'))
model.add(MaxPooling2D(pool_size=(2,2)))

#model.add(Dropout(rate=0.5))
model.add(Flatten())

model.add(Dense(units=64, activation='relu'))
model.add(Dense(2, activation='sigmoid'))

model.compile(optimizer=tf.keras.optimizers.SGD(learning_rate=0.05),
              loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
              metrics=['accuracy'])

model.summary()

history = model.fit(x=augmented_images,
                    validation_data=val_data_gen,
                    epochs=10,
                    steps_per_epoch=2000,
                    validation_steps=1000)

ValueError: Layer sequential_10 expects 1 inputs, but it received 5 input tensors.