Question

我正在尝试使用model.fit_generator()与数据生成器一起运行CNN。但是，我在Jupyter Notebook中收到一条错误消息：

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-36-e983628b2ed9> in <module>
     22     validation_data=vg, validation_steps=1,
     23     epochs=epochs, verbose=1,
---> 24     callbacks=[ReduceLROnPlateau, ModelCheckpoint, TensorBoard]
     25   )
     26 

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\util\deprecation.py in new_func(*args, **kwargs)
    322               'in a future version' if date is None else ('after %s' % date),
    323               instructions)
--> 324       return func(*args, **kwargs)
    325     return tf_decorator.make_decorator(
    326         func, new_func, 'deprecated',

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit_generator(self, generator, steps_per_epoch, epochs, verbose, callbacks, validation_data, validation_steps, validation_freq, class_weight, max_queue_size, workers, use_multiprocessing, shuffle, initial_epoch)
   1304         use_multiprocessing=use_multiprocessing,
   1305         shuffle=shuffle,
-> 1306         initial_epoch=initial_epoch)
   1307 
   1308   @deprecation.deprecated(

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\keras\engine\training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
    817         max_queue_size=max_queue_size,
    818         workers=workers,
--> 819         use_multiprocessing=use_multiprocessing)
    820 
    821   def evaluate(self,

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in fit(self, model, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_freq, max_queue_size, workers, use_multiprocessing, **kwargs)
    233           max_queue_size=max_queue_size,
    234           workers=workers,
--> 235           use_multiprocessing=use_multiprocessing)
    236 
    237       total_samples = _get_total_number_of_samples(training_data_adapter)

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\keras\engine\training_v2.py in _process_training_inputs(model, x, y, batch_size, epochs, sample_weights, class_weights, steps_per_epoch, validation_split, validation_data, validation_steps, shuffle, distribution_strategy, max_queue_size, workers, use_multiprocessing)
    531                      'at same time.')
    532 
--> 533   adapter_cls = data_adapter.select_data_adapter(x, y)
    534 
    535   # Handle validation_split, we want to split the data and get the training

~\Anaconda3\envs\py36\lib\site-packages\tensorflow_core\python\keras\engine\data_adapter.py in select_data_adapter(x, y)
    996         "Failed to find data adapter that can handle "
    997         "input: {}, {}".format(
--> 998             _type_name(x), _type_name(y)))
    999   elif len(adapter_cls) > 1:
   1000     raise RuntimeError(

ValueError: Failed to find data adapter that can handle input: <class '__main__.ProteinDataGenerator'>, <class 'NoneType'>

为了使所有内容都清晰可见，我有一个输入形状为（channels_last）--->（512、512、4）的CNN。红色，绿色，蓝色，黄色的4个通道。但是，我收到错误消息，说没有“适配器”来处理来自数据生成器的输入。该模型将使用图像分类模型对人体中蛋白质的位置进行分类。

尝试使用图像数据生成器训练CNN时收到ValueError

0 个答案: