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SciML / DiffEqGPU.jl

GPU-acceleration routines for DifferentialEquations.jl and the broader SciML scientific machine learning ecosystem
https://docs.sciml.ai/DiffEqGPU/stable/
MIT License
272 stars 27 forks source link

CompatHelper: bump compat for AMDGPU in [weakdeps] to 0.9, (keep existing compat) #329

Closed github-actions[bot] closed 1 month ago

github-actions[bot] commented 1 month ago

This pull request changes the compat entry for the AMDGPU package from 0.5, 0.6, 0.7, 0.8 to 0.5, 0.6, 0.7, 0.8, 0.9. This keeps the compat entries for earlier versions.

Note: I have not tested your package with this new compat entry. It is your responsibility to make sure that your package tests pass before you merge this pull request.

ChrisRackauckas commented 1 month ago

@DhairyaLGandhi do you know what this might be? https://buildkite.com/julialang/diffeqgpu-dot-jl/builds/1025#018fabca-cf1c-430e-9770-cdc03bbf4148/950-2172

DhairyaLGandhi commented 1 month ago

Yes, it's the literal_getproperty returning an ODESolution instead of Tangent. I'm surprised it hasn't been happening more often. I understand some code paths within SciML are written to handle the return type.

ChrisRackauckas commented 1 month ago

What's required to fix this?

DhairyaLGandhi commented 1 month ago

It should go away with removing that rule. I can take a look