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 👍 :)
   
   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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