我试图拟合（）我的CNN模型，但我遇到了层协同工作的问题。

from keras.engine import input_layer
from keras.models import Sequential
from keras.layers import Dense , Activation , Dropout ,Flatten, BatchNormalization
from keras.layers.convolutional import Conv2D
from keras.layers.convolutional import MaxPooling2D

# The model is as follows...

face_model = Sequential()
input_shape_face = (48, 48, 1)
face_model.add(Conv2D(8, kernel_size= (3, 3), input_shape = input_shape_face, padding= 'same', activation = 'LeakyReLU'))
face_model.add(MaxPooling2D(pool_size = (2, 2), padding= 'same'))
face_model.add(Conv2D(16, kernel_size= (3, 3), padding= 'same', activation = 'LeakyReLU'))
face_model.add(MaxPooling2D(pool_size = (2, 2), padding= 'same'))
face_model.add(Conv2D(32, kernel_size= (3, 3), padding= 'same', activation = 'LeakyReLU'))
face_model.add(MaxPooling2D(pool_size = (2, 2),  padding= 'same'))
face_model.add(Conv2D(64, kernel_size= (3, 3), padding= 'same', activation = 'LeakyReLU'))
face_model.add(Flatten())
face_model.add(Dense(128, activation = 'LeakyReLU'))
face_model.add(Dense(6, activation = 'softmax'))

face_model.summary()

我的图层汇总：

Model: "sequential_34"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_92 (Conv2D)          (None, 48, 48, 8)         80        
                                                                 
 max_pooling2d_69 (MaxPoolin  (None, 24, 24, 8)        0         
 g2D)                                                            
                                                                 
 conv2d_93 (Conv2D)          (None, 24, 24, 16)        1168      
                                                                 
 max_pooling2d_70 (MaxPoolin  (None, 12, 12, 16)       0         
 g2D)                                                            
                                                                 
 conv2d_94 (Conv2D)          (None, 12, 12, 32)        4640      
                                                                 
 max_pooling2d_71 (MaxPoolin  (None, 6, 6, 32)         0         
 g2D)                                                            
                                                                 
 conv2d_95 (Conv2D)          (None, 6, 6, 64)          18496     
                                                                 
 flatten_8 (Flatten)         (None, 2304)              0         
                                                                 
 dense_57 (Dense)            (None, 128)               295040    
                                                                 
 dense_58 (Dense)            (None, 6)                 774       
                                                                 
=================================================================
Total params: 320,198
Trainable params: 320,198
Non-trainable params: 0
_________________________________________________________________

# Compiling the model

face_model.compile(loss= 'categorical_crossentropy', optimizer= 'adam', metrics= ['accuracy'])

face_model.fit(facial_training_set, batch_size= batch_size, epochs= epochs, verbose= 1, validation_data= facial_testing_set)

收到的错误：

/usr/local/lib/python3.9/dist-packages/keras/engine/training.pyin tf__train_function（iterator）13 try：14 do_return = True ---〉15 retval_ = ag__.converted_call（ag__.ld（step_function），（ag__.ld（self），ag__.ld（iterator）），None，fscope）16除了：17 do_return = False
用户代码中的ValueError：

File "/usr/local/lib/python3.9/dist-packages/keras/engine/training.py",

第1284行，在train_function * return step_function（self，iterator）文件“/usr/local/lib/python3.9/dist-packages/keras/engine/training.py“，第1268行，在step_functionoutputs = model.distribute_strategy.run（run_step，args=（data，））文件“/usr/local/lib/python3.9/dist-packages/keras/engine/training.py“，第1249行，in run_stepoutputs = model.train_step（data）File“/usr/local/lib/python3.9/dist-packages/keras/engine/training.py“，line 1050，in train_step y_pred = self（x，training=True）File“/usr/local/lib/python3.9/dist-packages/keras/utils/traceback_utils.py”，line 70，在error_handler中，从None文件“/usr/local/lib/python3.9/dist-packages/keras/engine/input_spec.py”，第280行中引发e.with_traceback（filtered_tb），在assert_input_compatibility中，引发ValueError（

ValueError: Exception encountered when calling layer 'sequential_34' (type Sequential).

Input 0 of layer "dense_57" is incompatible with the layer: expected axis -1 of input shape to have value 2304, but received input

形状（48，384）

Call arguments received by layer 'sequential_34' (type Sequential):
  • inputs=tf.Tensor(shape=(48, 48, 1), dtype=float32)
  • training=True
  • mask=None