Speed up logic in ed.copy; distinguish reference tensor from tf.Variable

[dustinvtran]

This fixes the note in #471 (comment). As a minimal working example:

import edward as ed
import tensorflow as tf
from edward.models import WishartCholesky

W_prior = tf.Variable(tf.constant([[1., 0.], [0., 1.]]))
sigma = WishartCholesky(df=3.0, scale=W_prior)
ed.copy(sigma)

With this PR it succeeds; previously it fails (tf.__version__ == '1.0.1'). It was an issue where returning the reference tensor forces a downstream error when building WishartCholesky; returning the associated tf.Variable fixes it.

I also sped up some of the logic in ed.copy.