自动编码器训练后使用编码器模型进行预测时出错

Question

我想在自动编码器模型训练完成后仅使用编码器模型来使用编码器模型提取编码。训练完成后，我在使用编码器进行预测时遇到问题 model.I 已使用以下代码训练自动编码器模型

x = Conv2D(32, (3, 3), activation='relu', padding='same')(input_img)
x = MaxPooling2D((2, 2), padding='same')(x)
x = Conv2D(32, (3, 3), activation='relu', padding='same')(x)
x = MaxPooling2D((2, 2), padding='same')(x)
x = Conv2D(16, (3, 3), activation='relu', padding='same')(x)
x = Conv2D(8, (3, 3), activation='relu', padding='same')(x)
x = MaxPooling2D((2, 2), padding='same')(x)
x = Conv2D(8, (3, 3), activation='relu', padding='same')(x)
encoded = MaxPooling2D((2, 2), padding='same')(x)

x = Conv2D(8, (3, 3), activation='relu', padding='same')(encoded)
x = UpSampling2D((2, 2))(x)
x = Conv2D(8, (3, 3), activation='relu', padding='same')(x)
x = Conv2D(16, (3, 3), activation='relu',padding='same')(x)
x = UpSampling2D((2, 2))(x)
x = Conv2D(32, (3, 3), activation='relu',padding='same')(x)
x = UpSampling2D((2, 2))(x)
x = Conv2D(32, (3, 3), activation='relu',padding='same')(x)
x = UpSampling2D((2, 2))(x)
decoded = Conv2D(img_channel, (3, 3), activation='sigmoid', padding='same')(x) # example from documentaton

autoencoder = Model(input_img, decoded)
autoencoder.summary() # show model data

# create an encoder for debugging purposes later
encoder = Model(input_img, encoded)
# encoder = Model(autoencoder.input,autoencoder.layers[-10].output)

autoencoder.compile(optimizer='sgd',loss='mean_squared_error',metrics=[metrics.mae, metrics.categorical_accuracy])

# do not run forever but stop if model does not get better
stopper = EarlyStopping(monitor='mean_absolute_error', min_delta=0.0001, patience=5, mode='auto', verbose=1)

# do the actual fitting
autoencoder_train = autoencoder.fit_generator(
        train_generator,
        #validation_data=validation_generator,
        epochs=epochs,
        shuffle=False,
        callbacks=[stopper])
# Find out encoding of train data
train_encoding = encoder.predict(train_generator)

自动编码器训练完成后，我在使用编码器模型提取图像编码时遇到以下错误

~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in predict(self, x, batch_size, verbose, steps, max_queue_size, workers, use_multiprocessing)
   1838           max_queue_size=max_queue_size,
   1839           workers=workers,
-> 1840           use_multiprocessing=use_multiprocessing)
   1841
   1842     # Backwards compatibility.

~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in predict_generator(self, generator, steps, max_queue_size, workers, use_multiprocessing, verbose)
   2296         workers=workers,
   2297         use_multiprocessing=use_multiprocessing,
-> 2298         verbose=verbose)
   2299
   2300   def _get_callback_model(self):

~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training_generator.py in predict_generator(model, generator, steps, max_queue_size, workers, use_multiprocessing, verbose)
    352   """See docstring for `Model.predict_generator`."""
    353   if not context.executing_eagerly():
--> 354     model._make_test_function()
    355
    356   steps_done = 0

~/.local/lib/python3.6/site-packages/tensorflow/python/keras/engine/training.py in _make_test_function(self)
    714   def _make_test_function(self):
    715     if not hasattr(self, 'test_function'):
--> 716       raise RuntimeError('You must compile your model before using it.')
    717     if self.test_function is None:
    718       inputs = (self._feed_inputs +

RuntimeError: You must compile your model before using it.

这有什么问题吗？要是有人帮帮我就好了

Answer 1

这好像是tensorflow的版本问题。发生此错误时，早些时候我使用的是tensorflow 2.2。当我将它降级到 1.12 时，错误就解决了。

自动编码器训练后使用编码器模型进行预测时出错

Error while making prediction using encoder model after training of autoencoder

python-3.x

autoencoder