forked from mirrors/nixpkgs
1fdf42d461
When using cuda, the rpath was set to include GCC lib version 4.9. I am not sure what this was attempting to do, but an effect was to prevent certain python libraries to find the correct (newer) version of the std lib. Also avoid mentions of any specifc version in the propagatedBuildInputs
126 lines
3.5 KiB
Nix
126 lines
3.5 KiB
Nix
{ stdenv
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, fetchurl
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, buildPythonPackage
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, isPy35, isPy27
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, cudaSupport ? false
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, cudatoolkit ? null
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, cudnn ? null
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, linuxPackages ? null
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, numpy
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, six
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, protobuf3_2
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, swig
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, werkzeug
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, mock
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, zlib
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}:
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assert cudaSupport -> cudatoolkit != null
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&& cudnn != null
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&& linuxPackages != null;
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# unsupported combination
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assert ! (stdenv.isDarwin && cudaSupport);
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# tensorflow is built from a downloaded wheel, because the upstream
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# project's build system is an arcane beast based on
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# bazel. Untangling it and building the wheel from source is an open
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# problem.
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buildPythonPackage rec {
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pname = "tensorflow";
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version = "1.1.0";
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name = "${pname}-${version}";
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format = "wheel";
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disabled = ! (isPy35 || isPy27);
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src = let
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tfurl = sys: proc: pykind:
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let
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tfpref = if proc == "gpu"
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then "gpu/tensorflow_gpu"
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else "cpu/tensorflow";
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in
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"https://storage.googleapis.com/tensorflow/${sys}/${tfpref}-${version}-${pykind}.whl";
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dls =
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{
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darwin.cpu = {
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py2 = {
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url = tfurl "mac" "cpu" "py2-none-any" ;
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sha256 = "1fgf26lw0liqxc9pywc8y2mj8l1mv48nhkav0pag9vavdacb9mqr";
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};
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py3 = {
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url = tfurl "mac" "cpu" "py3-none-any" ;
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sha256 = "0z5p1fra7bih0vqn618i2w3vyy8d1rkc72k7bmjq0rw8msl717ia";
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};
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};
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linux-x86_64.cpu = {
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py2 = {
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url = tfurl "linux" "cpu" "cp27-none-linux_x86_64";
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sha256 = "0ld3hqx3idxk0zcrvn3p9yqnmx09zsj3mw66jlfw6fkv5hznx8j2";
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};
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py3 = {
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url = tfurl "linux" "cpu" "cp35-cp35m-linux_x86_64";
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sha256 = "0ahz9222rzqrk43lb9w4m351klkm6mlnnvw8xfqip28vbmymw90b";
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};
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};
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linux-x86_64.cuda = {
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py2 = {
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url = tfurl "linux" "gpu" "cp27-none-linux_x86_64";
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sha256 = "1baa9jwr6f8f62dyx6isbw8yyrd0pi1dz1srjblfqsyk1x3pnfvh";
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};
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py3 = {
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url = tfurl "linux" "gpu" "cp35-cp35m-linux_x86_64";
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sha256 = "0606m2awy0ifhniy8lsyhd0xc388dgrwksn87989xlgy90wpxi92";
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};
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};
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};
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in
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fetchurl (
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if stdenv.isDarwin then
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if isPy35 then
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dls.darwin.cpu.py3
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else
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dls.darwin.cpu.py2
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else if isPy35 then
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if cudaSupport then
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dls.linux-x86_64.cuda.py3
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else dls.linux-x86_64.cpu.py3
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else
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if cudaSupport then
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dls.linux-x86_64.cuda.py2
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else
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dls.linux-x86_64.cpu.py2
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);
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propagatedBuildInputs = with stdenv.lib;
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[ numpy six protobuf3_2 swig werkzeug mock ]
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++ optionals cudaSupport [ cudatoolkit cudnn stdenv.cc ];
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# Note that we need to run *after* the fixup phase because the
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# libraries are loaded at runtime. If we run in preFixup then
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# patchelf --shrink-rpath will remove the cuda libraries.
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postFixup = let
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rpath = stdenv.lib.makeLibraryPath
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(if cudaSupport then
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[ stdenv.cc.cc.lib zlib cudatoolkit cudnn
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linuxPackages.nvidia_x11 ]
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else
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[ stdenv.cc.cc.lib zlib ]
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);
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in
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''
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find $out -name '*.so' -exec patchelf --set-rpath "${rpath}" {} \;
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'';
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doCheck = false;
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meta = with stdenv.lib; {
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description = "TensorFlow helps the tensors flow";
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homepage = http://tensorflow.org;
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license = licenses.asl20;
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maintainers = with maintainers; [ jpbernardy ];
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platforms = with platforms; if cudaSupport then linux else linux ++ darwin;
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};
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}
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