| 24 Dec 2024 |
 matthewcroughan | Amen, you are not being well enough supported financially to solve tough issues, most people in this community are not. | 14:38:25 |
| matthewcroughan | The polish is a matter of resources | 14:38:58 |
| matthewcroughan | I did some postfixups, etc and worked around it | 14:39:15 |
| matthewcroughan | But yes I also landed on the same PRs as you, and I'm not sure why it is still an issue despite those PR's having been merged | 14:39:32 |
|  Collin Arnett joined the room. | 21:10:15 |
| Collin Arnett | Hello, are there any packages in the hackellPackage set that setup cudaSupport that I can use as an example to add cuda support for hasktorch? The author submitted a PR to bump the version here and has marked it as broken so I figured it would be good to get first class cuda support implemented here as well.
https://github.com/NixOS/nixpkgs/pull/367998/ | 21:16:42 |
| 25 Dec 2024 |
 SomeoneSerge (matrix works sometimes) | Oooooh that's a really great question, not least because, afaik, the haskell package set is its own thing with slightly different override patterns than elsewhere? | 00:04:12 |
| SomeoneSerge (matrix works sometimes) | I imagine haskell packages are auto-generated? If so, there must be some customization examples for other native/ffi libraries that might use dlopen at runtime or pkg-config at build time, e.g. wrappers for opengl or vulkan | 00:07:08 |
 connor (burnt/out) (UTC-8) | If accelerate is working or supported, check that out. Not sure it’s still supported given it relies on LLVM 12 (or earlier) for LLVM-HS.
Outside of that, not sure what people use for GPU stuff with Haskell | 00:14:03 |
| Collin Arnett | * Hello, are there any packages in the hackellPackage set that setup cudaSupport that I can use as an example to add cuda support for hasktorch? The author submitted a PR to bump the version here and has marked it as unbroken so I figured it would be good to get first class cuda support implemented here as well.
https://github.com/NixOS/nixpkgs/pull/367998/ | 03:28:32 |
| Collin Arnett | He ended up doing this in the hackage-packages.nix file:
"libtorch-ffi" = callPackage
({ mkDerivation, async, base, bytestring, c10, containers, hspec
, inline-c, inline-c-cpp, lib, libtorch-ffi-helper
, optparse-applicative, safe-exceptions, sysinfo, template-haskell
, text, torch, torch_cpu, torch_cuda ? null } :
mkDerivation {
pname = "libtorch-ffi";
version = "2.0.1.1";
sha256 = "0m6gg0z6dc67rxijqycyza197365xf1p71s74a8p4pkc2m2yl6p3";
libraryHaskellDepends = [
async base bytestring containers inline-c inline-c-cpp
libtorch-ffi-helper optparse-applicative safe-exceptions sysinfo
template-haskell text
];
librarySystemDepends = [ c10 torch torch_cpu ];
testHaskellDepends = [ base hspec safe-exceptions ];
homepage = "https://github.com/hasktorch/hasktorch#readme";
description = "Haskell bindings for PyTorch";
license = lib.licenses.bsd3;
configureFlags = [
"--extra-include-dirs=${lib.getDev pkgs.libtorch-bin}/include/torch/csrc/api/include"
] ++ lib.optionals pkgs.config.cudaSupport [ "-f cuda" ];
}) ({
c10 = pkgs.libtorch-bin;
torch_cpu = pkgs.libtorch-bin;
torch = pkgs.libtorch-bin;
} // lib.optionalAttrs (pkgs.config.cudaSupport) {
torch_cuda = pkgs.libtorch-bin;
});
| 11:39:48 |
| SomeoneSerge (matrix works sometimes) | I'll follow up on github | 17:19:13 |
| 26 Dec 2024 |
 Jesse | Does anyone have any configuration files for deep learning on nixos? I want to use cuda to train pytorch models on nixos, but I can't install cuda and cudnn correctly. I tried some but failed. Can anyone share the configuration files with me? I use a 4090 graphics card. | 10:43:05 |
 Gaétan Lepage | Have you set cudaSupport = true in your nixpkgs config ? | 10:43:54 |
| Gaétan Lepage | This enables cuda support for all packages that support it in nixpkgs | 10:44:08 |
