# Looking for a Flux RNN tutorial

**URL:** <https://discourse.julialang.org/t/looking-for-a-flux-rnn-tutorial/50743>\
**Category:** Teaching & Outreach\
**Created:** [November 25, 2020, 11:34am UTC](https://discourse.julialang.org/t/looking-for-a-flux-rnn-tutorial/50743 "2020-11-25T11:34:29Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![HenriDeh](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/henrideh/32/8316_2.png) [@HenriDeh](https://discourse.julialang.org/u/HenriDeh)\
**Post date:** [November 25, 2020, 11:34am UTC](https://discourse.julialang.org/t/looking-for-a-flux-rnn-tutorial/50743/1 "2020-11-25T11:34:29Z")

</div>

Hello,

I’m following a DL reading seminar with some PhD students. We follow the book Dive into Deep Learning but the code is written in Python. As a good exercise, and since I’m a julia user, I’m moving all the implementations to Julia. We are at the RNN chapter and I just can’t get a simple RNN to work on the basic time machine dataset The run-time is awfully slow. My model has \< 30000 parameters. I think I may be miss-using the Flux API.

I am looking for text prediction implementations of RNN in Flux or a full tutorial. I only found the model zoo with the char-rnn but it’s only iterating once over the data (I don’t understand when I must use `reset!`) and the dataloader is not working properly. Moving this model and data to CUDA also gives scalar indexing warnings.

Any good material you can recommend ?

Thanks.