changing the second loss in the example to eval_loss to demonstrate the new ability to score models without gradients
@@ -177,7 +177,7 @@ def main():
#vis.image(sample[0].view(28, 28).data.numpy())
vis.image(sample_mu[0].view(28, 28).data.numpy())
print("epoch avg loss {}".format(epoch_loss / float(mnist_size)))
- print("epoch eval loss {}".format(epoch_loss / float(mnist_size)))
+ print("epoch eval loss {}".format(epoch_eval_loss / float(mnist_size)))
if __name__ == '__main__':
main()
