mirror of
https://github.com/NixOS/nixpkgs.git
synced 2024-11-29 17:10:48 +00:00
127 lines
3.4 KiB
Nix
127 lines
3.4 KiB
Nix
{ stdenv
|
|
, fetchurl
|
|
, buildPythonPackage
|
|
, isPy35, isPy27
|
|
, cudaSupport ? false
|
|
, cudatoolkit ? null
|
|
, cudnn ? null
|
|
, gcc49 ? null
|
|
, linuxPackages ? null
|
|
, numpy
|
|
, six
|
|
, protobuf3_2
|
|
, swig
|
|
, mock
|
|
, gcc
|
|
, zlib
|
|
}:
|
|
|
|
assert cudaSupport -> cudatoolkit != null
|
|
&& cudnn != null
|
|
&& gcc49 != null
|
|
&& linuxPackages != null;
|
|
|
|
# unsupported combination
|
|
assert ! (stdenv.isDarwin && cudaSupport);
|
|
|
|
# tensorflow is built from a downloaded wheel, because the upstream
|
|
# project's build system is an arcane beast based on
|
|
# bazel. Untangling it and building the wheel from source is an open
|
|
# problem.
|
|
|
|
buildPythonPackage rec {
|
|
pname = "tensorflow";
|
|
version = "1.0.0";
|
|
name = "${pname}-${version}";
|
|
format = "wheel";
|
|
disabled = ! (isPy35 || isPy27);
|
|
|
|
src = let
|
|
tfurl = sys: proc: pykind:
|
|
let
|
|
tfpref = if proc == "gpu"
|
|
then "gpu/tensorflow_gpu"
|
|
else "cpu/tensorflow";
|
|
in
|
|
"https://storage.googleapis.com/tensorflow/${sys}/${tfpref}-${version}-${pykind}.whl";
|
|
dls =
|
|
{
|
|
darwin.cpu = {
|
|
py2 = {
|
|
url = tfurl "mac" "cpu" "py2-none-any" ;
|
|
sha256 = "15ayil28p20wkgpwkr4mz0imjxnf049xx4117jspg1qkjg2bn1b2";
|
|
};
|
|
py3 = {
|
|
url = tfurl "mac" "cpu" "py3-none-any" ;
|
|
sha256 = "1ynyhbm7yrp421364s49a1r3p83zxy74iiy5c4hx2xm5c4gs29an";
|
|
};
|
|
};
|
|
linux-x86_64.cpu = {
|
|
py2 = {
|
|
url = tfurl "linux" "cpu" "cp27-none-linux_x86_64";
|
|
sha256 = "1hwhq1qhjrfkqfkxpsrq6mdmdibnqr3n7xvzkxp6gaqj73vn5ch2";
|
|
};
|
|
py3 = {
|
|
url = tfurl "linux" "cpu" "cp35-cp35m-linux_x86_64";
|
|
sha256 = "0jx2mmlw0nxah9l25r46i7diqiv31qcz7855n250lsxfwcppy7y3";
|
|
};
|
|
};
|
|
linux-x86_64.cuda = {
|
|
py2 = {
|
|
url = tfurl "linux" "gpu" "cp27-none-linux_x86_64";
|
|
sha256 = "0l8f71x3ama5a6idj05jrswlmp4yg37fxhz8lx2xmgk14aszbcy5";
|
|
};
|
|
py3 = {
|
|
url = tfurl "linux" "gpu" "cp35-cp35m-linux_x86_64";
|
|
sha256 = "12q7s0yk0h3r4glh0fhl1fcdx7jl8xikwwp04a1lcagasr51s36m";
|
|
};
|
|
};
|
|
};
|
|
in
|
|
fetchurl (
|
|
if stdenv.isDarwin then
|
|
if isPy35 then
|
|
dls.darwin.cpu.py3
|
|
else
|
|
dls.darwin.cpu.py2
|
|
else if isPy35 then
|
|
if cudaSupport then
|
|
dls.linux-x86_64.cuda.py3
|
|
else dls.linux-x86_64.cpu.py3
|
|
else
|
|
if cudaSupport then
|
|
dls.linux-x86_64.cuda.py2
|
|
else
|
|
dls.linux-x86_64.cpu.py2
|
|
);
|
|
|
|
propagatedBuildInputs = with stdenv.lib;
|
|
[ numpy six protobuf3_2 swig mock ]
|
|
++ optionals cudaSupport [ cudatoolkit cudnn gcc49 ];
|
|
|
|
# Note that we need to run *after* the fixup phase because the
|
|
# libraries are loaded at runtime. If we run in preFixup then
|
|
# patchelf --shrink-rpath will remove the cuda libraries.
|
|
postFixup = let
|
|
rpath = stdenv.lib.makeLibraryPath
|
|
(if cudaSupport then
|
|
[ gcc49.cc.lib zlib cudatoolkit cudnn
|
|
linuxPackages.nvidia_x11 ]
|
|
else
|
|
[ gcc.cc.lib zlib ]
|
|
);
|
|
in
|
|
''
|
|
find $out -name '*.so' -exec patchelf --set-rpath "${rpath}" {} \;
|
|
'';
|
|
|
|
doCheck = false;
|
|
|
|
meta = with stdenv.lib; {
|
|
description = "TensorFlow helps the tensors flow";
|
|
homepage = http://tensorflow.org;
|
|
license = licenses.asl20;
|
|
platforms = with platforms; if cudaSupport then linux else linux ++ darwin;
|
|
};
|
|
}
|