Can I add my own cost/likelihood function in the ‘optimizer’ and pass it to the ‘inference’ in edward?
suppose I have,
loss = … # my custome cost
inference = ed.KLqp(…) # the kl inference from edward
then I choose a optimizer from tf,
optimizer = tf.train.RMSPropOptimizer(learning_rate).minimize(loss)
what happen after,
will the information from my ‘loss’ actually past to the ‘inference’ when I run ‘inference.update’?
apologize if it is a non-trival question, since I did not read the source code very carefully!