depot/third_party/nixpkgs/pkgs/development/python-modules/jaxlib/bin.nix
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GitOrigin-RevId: 710fed5a2483f945b14f4a58af2cd3676b42d8c8
2022-03-30 11:31:56 +02:00

142 lines
5.6 KiB
Nix

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