How the number of parameters associated with BatchNormalization layer is 2048? : <p>I have the following code.</p>

<pre><code>x = keras.layers.Input(batch_shape = (None, 4096))
hidden = keras.layers.Dense(512, activation = 'relu')(x)
hidden = keras.layers.BatchNormalization()(hidden)
hidden = keras.layers.Dropout(0.5)(hidden)
predictions = keras.layers.Dense(80, activation = 'sigmoid')(hidden)
mlp_model = keras.models.Model(input = [x], output = [predictions])
mlp_model.summary()
</code></pre>

<p>And this is the model summary:</p>

<pre><code>____________________________________________________________________________________________________
Layer (type)                     Output Shape          Param #     Connected to                     
====================================================================================================
input_3 (InputLayer)             (None, 4096)          0                                            
____________________________________________________________________________________________________
dense_1 (Dense)                  (None, 512)           2097664     input_3[0][0]                    
____________________________________________________________________________________________________
batchnormalization_1 (BatchNorma (None, 512)           2048        dense_1[0][0]                    
____________________________________________________________________________________________________
dropout_1 (Dropout)              (None, 512)           0           batchnormalization_1[0][0]       
____________________________________________________________________________________________________
dense_2 (Dense)                  (None, 80)            41040       dropout_1[0][0]                  
====================================================================================================
Total params: 2,140,752
Trainable params: 2,139,728
Non-trainable params: 1,024
____________________________________________________________________________________________________
</code></pre>

<p>The size of the input for the BatchNormalization (BN) layer is 512. According to <a href="https://keras.io/layers/normalization/" rel="noreferrer">Keras documentation</a>, shape of the output for BN layer is same as input which is 512.</p>

<p>Then how the number of parameters associated with BN layer is 2048?</p>
