预期activation_24具有形状2，，但具有形状1，的数组

如何解决预期activation_24具有形状2，，但具有形状1，的数组

所以，我是一个初学者，正在从事一个基础项目。我正在尝试使用Keras，但遇到了一个奇怪的错误。尝试阅读其他类似的帖子，但理解不多。我正在使用Jupyter笔记本，并且一切正常，直到出现错误的代码的最后一行为止。请让我知道可以做什么。详细的说明会很有帮助。预先感谢

代码如下：

model = Sequential()
model.add(Conv2D(100,(3,3),input_shape=(150,150,3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2,2)))

model.add(Conv2D(100,2)))

model.add(Flatten())
model.add(Dropout(0.5))
model.add(Dense(50))
model.add(Activation('relu'))
model.add(Dense(2))
model.add(Activation('softmax'))

model.compile(loss='binary_crossentropy',optimizer='adam',metrics=['accuracy'])
model.summary()

TRAINING_DIR = r"C:\Users\harsh\Downloads\face-mask-dataset\Dataset\train"
train_datagen = ImageDataGenerator(rescale=1.0/255,rotation_range=40,width_shift_range=0.2,height_shift_range=0.2,shear_range=0.2,zoom_range=0.2,horizontal_flip=True,fill_mode='nearest')
train_generator = train_datagen.flow_from_directory(TRAINING_DIR,batch_size=10,target_size=(150,150))

VALIDATION_DIR = r"C:\Users\harsh\Downloads\face-mask-dataset\Dataset\test"
validation_datagen = ImageDataGenerator(rescale=1.0/255)
validation_generator = validation_datagen.flow_from_directory(VALIDATION_DIR,150))

checkpoint = ModelCheckpoint('model2-{epoch:03d}.model',monitor='val_loss',verbose=0,save_best_only=True,mode='auto')

model.fit_generator(train_generator,epochs=10,validation_data=validation_generator,callbacks=[checkpoint])

这是错误：

Epoch 1/10
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-34-cd0a4d0d4c86> in <module>
----> 1 model.fit_generator(train_generator,callbacks=[checkpoint])

~\Miniconda3\envs\tensorflow\lib\site-packages\keras\legacy\interfaces.py in wrapper(*args,**kwargs)
     89                 warnings.warn('Update your `' + object_name + '` call to the ' +
     90                               'Keras 2 API: ' + signature,stacklevel=2)
---> 91             return func(*args,**kwargs)
     92         wrapper._original_function = func
     93         return wrapper

~\Miniconda3\envs\tensorflow\lib\site-packages\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)
   1730             use_multiprocessing=use_multiprocessing,1731             shuffle=shuffle,-> 1732             initial_epoch=initial_epoch)
   1733 
   1734     @interfaces.legacy_generator_methods_support

~\Miniconda3\envs\tensorflow\lib\site-packages\keras\engine\training_generator.py in fit_generator(model,initial_epoch)
    218                                             sample_weight=sample_weight,219                                             class_weight=class_weight,--> 220                                             reset_metrics=False)
    221 
    222                 outs = to_list(outs)

~\Miniconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in train_on_batch(self,x,y,sample_weight,reset_metrics)
   1506             x,1507             sample_weight=sample_weight,-> 1508             class_weight=class_weight)
   1509         if self._uses_dynamic_learning_phase():
   1510             ins = x + y + sample_weights + [1]

~\Miniconda3\envs\tensorflow\lib\site-packages\keras\engine\training.py in _standardize_user_data(self,check_array_lengths,batch_size)
    619                 feed_output_shapes,620                 check_batch_axis=False,# Don't enforce the batch size.
--> 621                 exception_prefix='target')
    622 
    623             # Generate sample-wise weight values given the `sample_weight` and

~\Miniconda3\envs\tensorflow\lib\site-packages\keras\engine\training_utils.py in standardize_input_data(data,names,shapes,check_batch_axis,exception_prefix)
    143                             ': expected ' + names[i] + ' to have shape ' +
    144                             str(shape) + ' but got array with shape ' +
--> 145                             str(data_shape))
    146     return data
    147 

ValueError: Error when checking target: expected activation_24 to have shape (2,) but got array with shape (1,)