개 고양이 분류에서 model.fit 부분 오류 문의

model = tf.keras.models.Sequential([
    tf.keras.layers.Conv2D( 32, (3, 3), padding="same", activation="relu", input_shape=(64, 64, 3) ),# 컨볼루셔널 레이어 1
    tf.keras.layers.MaxPooling2D( (2, 2) ),
    tf.keras.layers.Conv2D( 64, (3, 3), padding="same", activation="relu"),# 컨볼루셔널 레이어 2
    tf.keras.layers.MaxPooling2D( (2, 2) ),
    tf.keras.layers.Dropout(0.2), #노드 20% 지우기, overfitting 예방
    tf.keras.layers.Conv2D( 128, (3, 3), padding="same", activation="relu"),# 컨볼루셔널 레이어 3
    tf.keras.layers.MaxPooling2D( (2, 2) ),
    tf.keras.layers.Flatten(),
    tf.keras.layers.Dense(128, activation="relu"),
    tf.keras.layers.Dense(1, activation="sigmoid"),  
])

model.summary()

model.compile(loss='binary_crossentropy',  optimizer='adam', metrics=['accuracy'])
model.fit(train_ds, validation_data=val_ds, epochs=5 )

-->

Model: "sequential_13"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 conv2d_39 (Conv2D)          (None, 64, 64, 32)        896       
                                                                 
 max_pooling2d_39 (MaxPooli  (None, 32, 32, 32)        0         
 ng2D)                                                           
                                                                 
 conv2d_40 (Conv2D)          (None, 32, 32, 64)        18496     
                                                                 
 max_pooling2d_40 (MaxPooli  (None, 16, 16, 64)        0         
 ng2D)                                                           
                                                                 
 dropout_13 (Dropout)        (None, 16, 16, 64)        0         
                                                                 
 conv2d_41 (Conv2D)          (None, 16, 16, 128)       73856     
                                                                 
 max_pooling2d_41 (MaxPooli  (None, 8, 8, 128)         0         
 ng2D)                                                           
                                                                 
 flatten_13 (Flatten)        (None, 8192)              0         
                                                                 
 dense_26 (Dense)            (None, 128)               1048704   
                                                                 
 dense_27 (Dense)            (None, 1)                 129       
                                                                 
=================================================================
Total params: 1142081 (4.36 MB)
Trainable params: 1142081 (4.36 MB)
Non-trainable params: 0 (0.00 Byte)
_________________________________________________________________
Epoch 1/5

---------------------------------------------------------------------------

ValueError                                Traceback (most recent call last)

<ipython-input-30-afe8aae220b5> in <cell line: 18>()
     16 
     17 model.compile(loss='binary_crossentropy',  optimizer='adam', metrics=['accuracy'])
---> 18 model.fit(train_ds, validation_data=(val_ds), epochs=5 )

 
1 frames 
/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py in 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                 except:
     17                     do_return = False

ValueError: in user code:

    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1338, in train_function  *
        return step_function(self, iterator)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1322, in step_function  **
        outputs = model.distribute_strategy.run(run_step, args=(data,))
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1303, in run_step  **
        outputs = model.train_step(data)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py", line 1080, in train_step
        y_pred = self(x, training=True)
    File "/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py", line 70, in error_handler
        raise e.with_traceback(filtered_tb) from None
    File "/usr/local/lib/python3.10/dist-packages/keras/src/engine/input_spec.py", line 253, in assert_input_compatibility
        raise ValueError(

    ValueError: Exception encountered when calling layer 'sequential_13' (type Sequential).
    
    Input 0 of layer "conv2d_39" is incompatible with the layer: expected min_ndim=4, found ndim=0. Full shape received: ()
    
    Call arguments received by layer 'sequential_13' (type Sequential):
      • inputs=tf.Tensor(shape=(), dtype=float32)
      • training=True
      • mask=None
라고 오류가 나오는데 어떻게 해야 할까요?