### Saved graphs and checkpoints

When loading untrusted serialized computation graphs (in form of a `GraphDef`,
`SavedModel`, or equivalent on-disk format), the set of computation primitives
available to TensorFlow is powerful enough that you should assume that the
TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you

    *   Make graph name scope thread local so that they work correctly in
        multi-threaded environments.
    *   Update nsync synchronization library to avoid slow primitives on Linux.
    *   Removed need to put nsync/public on C include path when building custom
        ops.
    *   Add `tf.image.psnr`, `tf.image.ssim`, `tf.image.ssim_multiscale`,