Why does it take so long to train a model on 10,000 samples?

[PhyCoe]

My operating environment is tensorflow 2.15.1 , tfra 0.7.0. I have one question about why is the model training so slow? Is it because dynamic embedding only supports eager mode training?

the following below is the notebook links：
https://drive.google.com/file/d/1WGPhL2MOKCVnrF9dG59kKWi2efXcTwkN/view?usp=sharing

@jq @martinwicke @hxfxjun @zhangyafeikimi @acmore

[PhyCoe]

In addition, I found that the training was very slow only in the first epoch. Is it because of the initialization parameters? The training speed of the second epoch was very fast.

[MoFHeka]

dynamic embedding supports graph mode training. However, please refer to the implementation in the demo to concatenate all inputs and perform a one-time lookup; otherwise, the overhead of kernel launch will be very large.
If you want to lookup IDs without concatenate directly, please wait for the new version I developed.