forked from mirrors/nixpkgs
1d63f89caa
There are many different versions of the `cudatoolkit` and related cuda packages, and it can be tricky to ensure they remain compatible. - `cudaPackages` is now a package set with `cudatoolkit`, `cudnn`, `cutensor`, `nccl`, as well as `cudatoolkit` split into smaller packages ("redist"); - expressions should now use `cudaPackages` as parameter instead of the individual cuda packages; - `makeScope` is now used, so it is possible to use `.overrideScope'` to set e.g. a different `cudnn` version; - `release-cuda.nix` is introduced to easily evaluate cuda packages using hydra.
147 lines
5.7 KiB
Nix
147 lines
5.7 KiB
Nix
# For the moment we only support the CPU and GPU backends of jaxlib. The TPU
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# backend will require some additional work. Those wheels are located here:
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# https://storage.googleapis.com/jax-releases/libtpu_releases.html.
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# For future reference, the easiest way to test the GPU backend is to run
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# NIX_PATH=.. nix-shell -p python3 python3Packages.jax "python3Packages.jaxlib.override { cudaSupport = true; }"
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# export XLA_FLAGS=--xla_gpu_force_compilation_parallelism=1
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# python -c "from jax.lib import xla_bridge; assert xla_bridge.get_backend().platform == 'gpu'"
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# python -c "from jax import random; random.PRNGKey(0)"
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# python -c "from jax import random; x = random.normal(random.PRNGKey(0), (100, 100)); x @ x"
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# There's no convenient way to test the GPU backend in the derivation since the
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# nix build environment blocks access to the GPU. See also:
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# * https://github.com/google/jax/issues/971#issuecomment-508216439
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# * https://github.com/google/jax/issues/5723#issuecomment-913038780
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{ absl-py
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, addOpenGLRunpath
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, autoPatchelfHook
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, buildPythonPackage
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, config
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, cudnn
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, fetchurl
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, flatbuffers
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, isPy39
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, lib
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, python
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, scipy
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, stdenv
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# Options:
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, cudaSupport ? config.cudaSupport or false
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, cudaPackages ? {}
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}:
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let
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inherit (cudaPackages) cudatoolkit cudnn;
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in
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# There are no jaxlib wheels targeting cudnn <8.0.5, and although there are
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# wheels for cudatoolkit <11.1, we don't support them.
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assert cudaSupport -> lib.versionAtLeast cudatoolkit.version "11.1";
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assert cudaSupport -> lib.versionAtLeast cudnn.version "8.0.5";
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let
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version = "0.3.0";
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pythonVersion = python.pythonVersion;
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# Find new releases at https://storage.googleapis.com/jax-releases. When
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# upgrading, you can get these hashes from prefetch.sh.
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cpuSrcs = {
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"3.9" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/nocuda/jaxlib-${version}-cp39-none-manylinux2010_x86_64.whl";
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hash = "sha256-AfBVqoqChEXlEC5PgbtQ5rQzcbwo558fjqCjSPEmN5Q=";
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};
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"3.10" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/nocuda/jaxlib-${version}-cp310-none-manylinux2010_x86_64.whl";
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hash = "sha256-9uBkFOO8LlRpO6AP+S8XK9/d2yRdyHxQGlbAjShqHRQ=";
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};
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};
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gpuSrcs = {
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"3.9-805" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/cuda11/jaxlib-${version}+cuda11.cudnn805-cp39-none-manylinux2010_x86_64.whl";
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hash = "sha256-CArIhzM5FrQi3TkdqpUqCeDQYyDMVXlzKFgjNXjLJXw=";
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};
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"3.9-82" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/cuda11/jaxlib-${version}+cuda11.cudnn82-cp39-none-manylinux2010_x86_64.whl";
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hash = "sha256-Q0plVnA9pUNQ+gCHSXiLNs4i24xCg8gBGfgfYe3bot4=";
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};
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"3.10-805" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/cuda11/jaxlib-${version}+cuda11.cudnn805-cp310-none-manylinux2010_x86_64.whl";
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hash = "sha256-JopevCEAs0hgDngIId6NqbLam5YfcS8Lr9cEffBKp1U=";
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};
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"3.10-82" = fetchurl {
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url = "https://storage.googleapis.com/jax-releases/cuda11/jaxlib-${version}+cuda11.cudnn82-cp310-none-manylinux2010_x86_64.whl";
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hash = "sha256-2f5TwbdP7EfQNRM3ZcJXCAkS2VXBwNYH6gwT9pdu3Go=";
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};
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};
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in
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buildPythonPackage rec {
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pname = "jaxlib";
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inherit version;
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format = "wheel";
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# At the time of writing (2022-03-03), there are releases for <=3.10.
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# Supporting all of them is a pain, so we focus on 3.9, the current nixpkgs
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# python3 version, and 3.10.
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disabled = !(pythonVersion == "3.9" || pythonVersion == "3.10");
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src =
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if !cudaSupport then cpuSrcs."${pythonVersion}" else
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let
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# jaxlib wheels are currently provided for cudnn versions at least 8.0.5 and
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# 8.2. Try to use 8.2 whenever possible.
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cudnnVersion = if (lib.versionAtLeast cudnn.version "8.2") then "82" else "805";
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in
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gpuSrcs."${pythonVersion}-${cudnnVersion}";
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# Prebuilt wheels are dynamically linked against things that nix can't find.
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# Run `autoPatchelfHook` to automagically fix them.
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nativeBuildInputs = [ autoPatchelfHook ] ++ lib.optional cudaSupport addOpenGLRunpath;
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# Dynamic link dependencies
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buildInputs = [ stdenv.cc.cc ];
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# jaxlib contains shared libraries that open other shared libraries via dlopen
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# and these implicit dependencies are not recognized by ldd or
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# autoPatchelfHook. That means we need to sneak them into rpath. This step
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# must be done after autoPatchelfHook and the automatic stripping of
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# artifacts. autoPatchelfHook runs in postFixup and auto-stripping runs in the
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# patchPhase. Dependencies:
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# * libcudart.so.11.0 -> cudatoolkit_11.lib
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# * libcublas.so.11 -> cudatoolkit_11
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# * libcuda.so.1 -> opengl driver in /run/opengl-driver/lib
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preInstallCheck = lib.optional cudaSupport ''
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shopt -s globstar
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addOpenGLRunpath $out/**/*.so
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for file in $out/**/*.so; do
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rpath=$(patchelf --print-rpath $file)
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# For some reason `makeLibraryPath` on `cudatoolkit_11` maps to
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# <cudatoolkit_11.lib>/lib which is different from <cudatoolkit_11>/lib.
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patchelf --set-rpath "$rpath:${cudatoolkit}/lib:${lib.makeLibraryPath [ cudatoolkit.lib cudnn ]}" $file
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done
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'';
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propagatedBuildInputs = [ absl-py flatbuffers scipy ];
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# Note that cudatoolkit is snecessary since jaxlib looks for "ptxas" in $PATH.
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# See https://github.com/NixOS/nixpkgs/pull/164176#discussion_r828801621 for
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# more info.
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postInstall = lib.optional cudaSupport ''
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mkdir -p $out/bin
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ln -s ${cudatoolkit}/bin/ptxas $out/bin/ptxas
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'';
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pythonImportsCheck = [ "jaxlib" ];
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meta = with lib; {
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description = "XLA library for JAX";
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homepage = "https://github.com/google/jax";
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license = licenses.asl20;
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maintainers = with maintainers; [ samuela ];
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platforms = [ "x86_64-linux" ];
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};
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}
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