title: Is it possible to use a Conv2D layer without a model or a running Session?
body: <p>I'm writing an article about Conv2D nets and I want to preview the effect of a Conv2D net on an image, I could get this using a simple keras model and getting the output of first layer (which is the conv), but I wanted a simpler way.</p>
  
  <p>So I did this:</p>
  
  <pre><code>layer = Conv2D(10, (3, 3), input_shape=[1080, 1080, 3])
  tensor_in = tf.convert_to_tensor(img, dtype="float")
  tensor_out = layer(tensor_in)
  </code></pre>
  
  <p>The code above works fine and I end up with a tensor <code>tensor_out</code>.
  <strong>The problem is</strong> I couldn't manage to read the data from this tensor. 
  is there anyway to do it without having to use the <code>.eval()</code> function that requires a running session?</p>