# End-to-end gradients with Enzyme when training ODE parameters

**URL:** <https://discourse.julialang.org/t/end-to-end-gradients-with-enzyme-when-training-ode-parameters/89062>\
**Category:** General Usage\
**Tags:** diffeq, autodiff, enzyme\
**Created:** [October 21, 2022, 1:28pm UTC](https://discourse.julialang.org/t/end-to-end-gradients-with-enzyme-when-training-ode-parameters/89062 "2022-10-21T13:28:39Z")\
**Posts on this page:** 2\
**Page:** 1

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**Author:** ![nrontsis](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/nrontsis/32/38535_2.png) [@nrontsis](https://discourse.julialang.org/u/nrontsis)\
**Post date:** [October 21, 2022, 1:28pm UTC](https://discourse.julialang.org/t/end-to-end-gradients-with-enzyme-when-training-ode-parameters/89062/1 "2022-10-21T13:28:39Z")

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When reading the [SciMLSensitivity docs](https://sensitivity.sciml.ai/stable/ad_examples/differentiating_ode/) I am somewhat surprised that Enzyme.jl is only mentioned as an option for JVPs.

Why is doing e.g. end to end gradient computations with Enzyme (e.g. much like ForwardDiff.jl does) not a more prominent option?

I suspect that this might not be very user friendly or might limit us to certain solvers due to Enzyme supporting only a subset of Julia, but I wonder if this is regardless a promising option for certain scenarios?

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [October 21, 2022, 5:19pm UTC](https://discourse.julialang.org/t/end-to-end-gradients-with-enzyme-when-training-ode-parameters/89062/2 "2022-10-21T17:19:03Z")

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> [@nrontsis](#):
>
> Why is doing e.g. end to end gradient computations with Enzyme (e.g. much like ForwardDiff.jl does) not a more prominent option?

It only supports a subset of Julia which doesn’t include the ODE solvers at this time. But it’s growing, and that’s one our goals.