140 lines
4.0 KiB
Nix
140 lines
4.0 KiB
Nix
{ stdenv
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, fetchurl
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, buildPythonPackage
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, isPy36, 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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, protobuf
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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 = ! (isPy36 || 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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py35 = {
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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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py36 = {
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url = tfurl "linux" "cpu" "cp36-cp36m-linux_x86_64";
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sha256 = "1a2cc8ihl94iqff76nxg6bq85vfb7sj5cvvi9sxy2f43k32fi4lv";
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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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py35 = {
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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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py36 = {
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url = tfurl "linux" "gpu" "cp36-cp36m-linux_x86_64";
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sha256 = "0lvbmfa87qzrajadpsf13gi3l71vryzkryzqfvkykivqrdjsvj8q";
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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 isPy27 then
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dls.darwin.cpu.py2
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else
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dls.darwin.cpu.py3
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else if isPy36 then
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if cudaSupport then
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dls.linux-x86_64.cuda.py36
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else dls.linux-x86_64.cpu.py36
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else if isPy35 then
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if cudaSupport then
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dls.linux-x86_64.cuda.py35
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else dls.linux-x86_64.cpu.py35
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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 protobuf 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; [ jyp ];
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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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