title: How to use tf.losses.sigmoid_cross_entropy with label smoothing in keras
body: <p>I want to use label smoothing in keras model.fit, but it give error. 
  If I try</p>
  
  <pre><code>model = tf.keras.Model(inputs=inputs, outputs=predictions)
  optimizer = tf.keras.optimizers.Adam(0.001)
  model.compile(optimizer=optimizer, loss=tf.losses.sigmoid_cross_entropy(label_smoothing=0.1))
  </code></pre>
  
  <p>It gives error</p>
  
  <pre><code> TypeError: sigmoid_cross_entropy() missing 2 required positional arguments: 'multi_class_labels' and 'logits'
  </code></pre>
  
  <p>If i add </p>
  
  <pre><code>loss=tf.losses.sigmoid_cross_entropy(y_true, y_pred, label_smoothing=0.1))
  </code></pre>
  
  <p>It gives </p>
  
  <pre><code>NameError: name 'y_true' is not defined
  </code></pre>
  
  <p>How can i use this loss function?</p>