title: Can TensorFlow cache (sub-)graph computations?
body: <p>Can TensorFlow automatically cache computations if they involve
  multiple calls to the same computation (sub-)graph?</p>
  
  <p>For example, I have a matrix <code>F</code> in which each entry represents a
  computation based on trainable variables <code>W</code>. My objective function
  multiplies this matrix several times with different vectors (each
  time with unchanged W).</p>
  
  <p>Will TensorFlow recompute, for example, <code>F[1,2]</code> whenever I access
  it, or will it cache that value?</p>
  
  <p>In theory, one could precompute the matrix <code>F</code> given a fixed <code>W</code>,
  such that each entry in <code>F</code> is a <code>tf.constant</code>. But that would
  prevent the correct computation of the gradients of <code>W</code>.</p>