title: How add scalar to tensor in Keras or create tensor from scalar?
body: <p>I need to somehow run someting like that:</p>
  
  <pre><code>x = Input(shape=(img_height, img_width, img_channels))
  x1 = Add()([x, 127.5])
  x2 = Multiply()(x1, -127.5])
  </code></pre>
  
  <p>But, error emerges:<br>
  <code>ValueError: Layer add_1 was called with an input that isn't a symbolic tensor. Received type: &lt;class 'float'&gt;. Full input: [&lt;tf.Tensor 'input_1:0' shape=(?, 400, 300, 3) dtype=float32&gt;, 0.00784313725490196]. All inputs to the layer should be tensors.</code></p>
  
  <p>I can't use <code>Lambda()</code> layer, because I need to convert final model into CoreML and I'll be unable to rewrite them in swift.</p>
  
  <p>Is there any way to create Keras tensor from float?<br>
  Maybe there is a different solution for this problem?</p>
  
  <p>UPD: backend is TensorFlow</p>