1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
|
# 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
'';
# pip dependencies and optionally cudatoolkit. Note that cudatoolkit is
# necessary since jaxlib looks for "ptxas" in $PATH.
propagatedBuildInputs = [ absl-py flatbuffers scipy ] ++ lib.optional cudaSupport cudatoolkit_11;
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" ];
};
}
|