class DNNModel(tf.keras.Model):
def __init__(self, num_classes):
super(DNNModel, self).__init__()
## 코드 시작 ##
self.dense1 = tf.keras.layers.Dense(512,input_shape=(28,28))
self.bn1 = tf.keras.layers.BatchNormalization()
self.relu1 = tf.keras.layers.Activation(tf.keras.activations.relu)
self.dense2 = tf.keras.layers.Dense(num_classes)
## 코드 종료 ##

def call(self, inputs, training=False):
"""Run the model."""
## 코드 시작 ##
dense1_out = self.dense1(inputs)
bn1_out = self.bn1(dense1_out)
relu1_out = self.relu1(bn1_out)
dense2_out = self.dense2(relu1_out)
## 코드 종료 ##
return dense2_out

모델 테스트 하니, 아래와 같이 나오는데 오류가 뭔지 모르겠네요ㅠ 

[지문의 지시보다 더 많거나 적은 Relu 함수가 설계되었습니다. 지문을 다시 확인하시기 바랍니다]

predictions:  tf.Tensor(
[[ 5.3379560e-01 -2.3761180e-01  1.3999850e+00 -3.1324694e-01
  -8.1787622e-01  1.1721934e+00 -2.9624808e-01 -4.2776041e-02
   1.4625961e-01  3.6068922e-01]
 [ 2.8527328e-01 -1.4177586e-01  5.9206277e-01 -2.7118844e-01
  -8.1278700e-01  8.6498630e-01 -1.0841914e-01 -9.7464770e-05
  -3.0442119e-01  7.3610984e-02]
 [ 1.9408071e-01  8.3620876e-02  6.0621786e-01 -2.8606656e-01
  -1.3437253e-01  4.6336082e-01 -5.0032622e-01  3.5316363e-01
   3.4358054e-02 -7.6938719e-02]], shape=(3, 10), dtype=float32)
Model: "dnn_model_17"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
dense_43 (Dense)             multiple                  401920    
_________________________________________________________________
batch_normalization_22 (Batc multiple                  2048      
_________________________________________________________________
activation_18 (Activation)   multiple                  0         
_________________________________________________________________
dense_44 (Dense)             multiple                  5130      
=================================================================
Total params: 409,098
Trainable params: 408,074
Non-trainable params: 1,024