# Writing pytorch layers in julia

**URL:** https://discourse.julialang.org/t/writing-pytorch-layers-in-julia/65064
**Category:** Machine Learning
**Created:** [July 21, 2021, 7:26pm UTC](https://discourse.julialang.org/t/writing-pytorch-layers-in-julia/65064 "2021-07-21T19:26:02Z")
**Posts on this page:** 1
**Page:** 1

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### Author: ![Tomas\_Pevny](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/tomas_pevny/32/25466_2.png) [@Tomas\_Pevny](https://discourse.julialang.org/u/Tomas_Pevny)
#### Post date: [July 21, 2021, 7:26pm UTC](https://discourse.julialang.org/t/writing-pytorch-layers-in-julia/65064/1 "2021-07-21T19:26:02Z")

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Hi All,

From time to time, I am pushed to rewrite Mill.jl (multi-instance learning library) in pytorch. While that might be possible, i would like to avoid it, as we made heavy use of custom written gradients to help us deal with missing values and with a flexibility of input data, which can be json files in general. I wonder, if I can create a wrapper in pytorch that would behave to pytorch as a normal layer and people can combine mill models with other pytorch modules. I expect it to be possible, but i would like to ask first, if someone tried something like this. I know some people did it other way around, using pytorch from Julia, but that is not what I want.

Thanks for answers in advance. Explaining possible roadblocks is welcomed.