From 7b802966fc9707b4c3c7482f24b655a8620d2efe Mon Sep 17 00:00:00 2001 From: Fritz Obermeyer Date: Mon, 15 Oct 2018 10:36:48 -0700 Subject: [PATCH] Fix jit arg error in hmm example --- examples/hmm.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/examples/hmm.py b/examples/hmm.py index 33404cb1f9..3104ba1d25 100644 --- a/examples/hmm.py +++ b/examples/hmm.py @@ -253,7 +253,7 @@ def main(args): # We'll train on small minibatches. logging.info('Step\tLoss') for step in range(args.num_steps): - loss = svi.step(sequences, lengths, args, batch_size=args.batch_size) + loss = svi.step(sequences, lengths, args=args, batch_size=args.batch_size) logging.info('{: >5d}\t{}'.format(step, loss / num_observations)) # We evaluate on the entire training dataset, @@ -269,7 +269,7 @@ def main(args): if args.truncate: lengths.clamp_(max=args.truncate) num_observations = float(lengths.sum()) - test_loss = elbo.loss(model, guide, sequences, lengths, args, include_prior=False) + test_loss = elbo.loss(model, guide, sequences, lengths, args=args, include_prior=False) logging.info('test loss = {}'.format(test_loss / num_observations)) # We expect models with higher capacity to perform better,