anchor.diff:    postFixup = let
       rpath = stdenv.lib.makeLibraryPath
         (if cudaSupport then
  -        [ stdenv.cc.cc.lib zlib cudatoolkit cudnn
  +        [ stdenv.cc.cc.lib zlib cudatoolkit_joined cudnn
             linuxPackages.nvidia_x11 ]
         else
           [ stdenv.cc.cc.lib zlib ]
  
positive.code:   propagatedBuildInputs =
      [ numpy six protobuf mock backports_weakref ]
      ++ lib.optional (!isPy36) tensorflow-tensorboard
      ++ lib.optionals cudaSupport [ cudatoolkit cudnn stdenv.cc ];
  
    # tensorflow-gpu depends on tensorflow_tensorboard, which cannot be
    # built at the moment (some of its dependencies do not build
  
negative.code:   name = "${pname}-${version}";
    format = "wheel";
    disabled = ! (isPy35 || isPy36 || isPy27);
  
    # cudatoolkit is split (see https://github.com/NixOS/nixpkgs/commit/bb1c9b027d343f2ce263496582d6b56af8af92e6)
    # However this means that libcusolver is not loadable by tensor flow. So we undo the split here.
    cudatoolkit_joined = symlinkJoin {
      name = "unsplit_cudatoolkit";
      paths = [ cudatoolkit.out
                cudatoolkit.lib ];};
  
    src = let
        tfurl = sys: proc: pykind:
  