我正在自定义一个层来使用我的模型。核心部分是“调用”功能，

class Custom_Layer(Layer):
// some code

def call(self, inputs, **kwargs):
  kernel = mul(self.base, self.diag_start - self.diag_end) 
  outputs = matmul(a=inputs, b=kernel)

  if self.use_bias:
    outputs = tf.nn.bias_add(outputs, self.bias)

  if self.activation is not None:
    outputs = self.activation(outputs)

  return outputs    
// some code

并在一个简单的模型中得到了应用。

inputs = tf.keras.layers.Input(shape=(784,),dtype='float32') 
layer1 = Custom_layer(2000, **Custom_layer_config, activation='tanh')(inputs)
layer2 = Custom_layer(200, **Custom_layer_config, activation='tanh')(layer1)
output_lay = Custom_layer(10, **Custom_layer_config, activation='softmax')(layer2)

model = tf.keras.models.Model(inputs=inputs, outputs=output_lay)

opt = tf.keras.optimizers.Adamax(learning_rate=0.02)
model.compile(optimizer=opt,
     loss='sparse_categorical_crossentropy',
     metrics=['accuracy'])
model.summary()

它应该打印如下：

Model: "functional_13"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
input_8 (InputLayer)         [(None, 784)]             0         
_________________________________________________________________
CustomLayer_18 (Custom_Layer)       (None, 2000)              1570784   
_________________________________________________________________
CustomLayer_19 (Custom_Layer)       (None, 200)               402200    
_________________________________________________________________
CustomLayer_20 (Custom_Layer)       (None, 10)                2210      
=================================================================
Total params: 1,975,194
Trainable params: 5,194
Non-trainable params: 1,970,000
_________________________________________________________________

但打印以下内容：

Model: "model_1"
_________________________________________________________________
 Layer (type)                Output Shape              Param #   
=================================================================
 input_2 (InputLayer)        [(None, 784)]             0         
                                                                 
 tf.linalg.matmul_3 (TFOpLam  (None, 2000)             0         
 bda)                                                            
                                                                 
 tf.math.tanh_2 (TFOpLambda)  (None, 2000)             0         
                                                                 
 tf.linalg.matmul_4 (TFOpLam  (None, 200)              0         
 bda)                                                            
                                                                 
 tf.math.tanh_3 (TFOpLambda)  (None, 200)              0         
                                                                 
 tf.linalg.matmul_5 (TFOpLam  (None, 10)               0         
 bda)                                                            
                                                                 
 tf.compat.v1.nn.softmax_1 (  (None, 10)               0         
 TFOpLambda)                                                     
                                                                 
=================================================================
Total params: 0
Trainable params: 0
Non-trainable params: 0

第一个摘要是我从作者的存储库中得到的，第二个摘要是我运行相同的代码时没有更改任何内容。
代码并不复杂，但奇怪的是为什么没有参数。我的问题是这里出了什么问题。