title: How the number of parameters associated with BatchNormalization layer is 2048?
body: <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>