altosaar commented on issue #10508: MXNet much slower than TensorFlow URL: https://github.com/apache/incubator-mxnet/issues/10508#issuecomment-380738642 Dang, I knew it was a silly bug on my end–thanks for catching that @ThomasDelteil :) I just pushed the [fix](https://github.com/altosaar/variational-autoencoder/commit/ab76990a616afdc9aec25e0995e90db962a2ffc7). You're right, should have caught that by realizing that millions of iterations/s is very unreasonable. Here are the new timings I get: TensorFlow 1.7.0 CPU: ``` Iteration: 1000 ELBO: -131.288 s/iter: 5.380e-03 Iteration: 2000 ELBO: -122.167 s/iter: 5.253e-03 ``` TensorFlow 1.7.0 GPU: ``` Iteration: 1000 ELBO: -142.142 s/iter: 3.681e-03 Iteration: 2000 ELBO: -114.007 s/iter: 3.725e-03 ``` This matches the MXNet timings on GPU 👍 :) and it's awesome that it's a lot faster on CPU! P.S. I agree examples/s is good in some cases. For generative models, I find time/iteration more informative (the convergence of the objective should be measured in number of parameter updates, not epochs, so this is what I focus on).
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