我在尝试训练模型时遇到此错误，Tensorflow ValueError: Unexpected result of `train_function`（空日志）

原文标题 ：I get this Error while trying to Train a Model, Tensorflow ValueError: Unexpected result of `train_function` (Empty logs)

我正在尝试训练我的模型来读取一些 X 射线图像，我正在使用 Jupyter Notebook，我导入了库，定义了图像属性，准备了数据集，创建了神经网络模型，定义了回调……和管理数据，但是在尝试训练我的模型时，这是我得到的错误：

ValueError: Unexpected result of `train_function` (Empty logs). Please use `Model.compile(..., run_eagerly=True)`, or `tf.config.run_functions_eagerly(True)` for more information of where went wrong, or file a issue/bug to `tf.keras`.

这是神经网络模型的创建：

model=Sequential()
model.add(Conv2D(32,(3,3),activation='relu',input_shape=(Image_Width,Image_Height,Image_Channels)))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.25))
model.add(Conv2D(64,(3,3),activation='relu'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.25))
model.add(Conv2D(128,(3,3),activation='relu'))
model.add(BatchNormalization())
model.add(MaxPooling2D(pool_size=(2,2)))
model.add(Dropout(0.25))
model.add(Flatten())
model.add(Dense(512,activation='relu'))
model.add(BatchNormalization())
model.add(Dropout(0.5))
model.add(Dense(2,activation='softmax'))
model.compile(loss='categorical_crossentropy',
  optimizer='rmsprop',metrics=['accuracy'])

以及数据生成器的训练和验证：

base_dir = "C:/Users/lenovo/PneumoniaClassification/chest_xray"
train_dir = os.path.join(base_dir, 'train')
test_dir = os.path.join(base_dir, 'test')
validation_dir = os.path.join(base_dir, 'val')


train_datagen = ImageDataGenerator(rotation_range=15,
                                    rescale=1./255,
                                    shear_range=0.1,
                                    zoom_range=0.2,
                                    horizontal_flip=True,
                                    width_shift_range=0.1,
                                    height_shift_range=0.1
                                    )
train_generator = train_datagen.flow_from_directory(
        train_dir,  # This is the source directory for training images
        target_size=Image_Size,  # All images will be resized 
        batch_size= 50,
        # Since we use binary_crossentropy loss, we need binary labels
        class_mode='binary')

test_datagen = ImageDataGenerator(rotation_range=15,
                                    rescale=1./255,
                                    shear_range=0.1,
                                    zoom_range=0.2,
                                    horizontal_flip=True,
                                    width_shift_range=0.1,
                                    height_shift_range=0.1)

test_generator = test_datagen.flow_from_directory(
        test_dir,
        target_size=Image_Size,
        batch_size= 50,
        class_mode='binary')

validation_datagen = ImageDataGenerator(rescale=1./255)

validation_generator = test_datagen.flow_from_directory(
        validation_dir,
        target_size=Image_Size,
        batch_size= 50,
        class_mode='binary')

但是在这里，当我尝试训练模型时，我得到错误 Unexpected result oftrain_function….. 使用此代码：

epochs=10
model.fit(
    train_generator, 
    epochs=epochs,
    validation_data=validation_generator,
    validation_steps=total_validate//batch_size,
    steps_per_epoch=total_train//batch_size,
    callbacks=callbacks
)

这是完整的错误：

ValueError                                Traceback (most recent call last)
Input In [33], in <cell line: 2>()
      1 epochs=10
----> 2 model.fit(
      3     train_generator, 
      4     epochs=epochs,
      5     validation_data=validation_generator,
      6     validation_steps=total_validate//batch_size,
      7     steps_per_epoch=total_train//batch_size,
      8     callbacks=callbacks
      9 )

File ~\AppData\Roaming\Python\Python39\site-packages\keras\utils\traceback_utils.py:67, in filter_traceback.<locals>.error_handler(*args, **kwargs)
     65 except Exception as e:  # pylint: disable=broad-except
     66   filtered_tb = _process_traceback_frames(e.__traceback__)
---> 67   raise e.with_traceback(filtered_tb) from None
     68 finally:
     69   del filtered_tb

File ~\AppData\Roaming\Python\Python39\site-packages\keras\engine\training.py:1395, in Model.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_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing)
   1393 logs = tf_utils.sync_to_numpy_or_python_type(logs)
   1394 if logs is None:
-> 1395   raise ValueError('Unexpected result of `train_function` '
   1396                    '(Empty logs). Please use '
   1397                    '`Model.compile(..., run_eagerly=True)`, or '
   1398                    '`tf.config.run_functions_eagerly(True)` for more '
   1399                    'information of where went wrong, or file a '
   1400                    'issue/bug to `tf.keras`.')
   1401 epoch_logs = copy.copy(logs)
   1403 # Run validation.

ValueError: Unexpected result of `train_function` (Empty logs). Please use `Model.compile(..., run_eagerly=True)`, or `tf.config.run_functions_eagerly(True)` for more information of where went wrong, or file a issue/bug to `tf.keras`.