temporary: Drop workarounds for previous upstream version
This commit is contained in:
Tyson Whitehead
@@ -17,10 +17,6 @@ self: super: pkgs: with pkgs; {
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];
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} );
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# tensorflow requires cudatoolkit90
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inherit (callPackages ./tf-cudatoolkit.nix { }) cudatoolkit90;
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inherit (callPackages ./tf-cudnn.nix { }) cudnn_cudatoolkit90;
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# https://github.com/NixOS/nixpkgs/issues/44426
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python27 = super.python27.override { packageOverrides = pythonOverrides; };
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python34 = super.python34.override { packageOverrides = pythonOverrides; };
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@@ -1,44 +1,3 @@
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pkgs: self: super: with self; {
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# Backport upstream master tensorflow (bazel build is failing)
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astunparse = callPackage ./tf-astunparse.nix { };
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gast = callPackage ./tf-gast.nix { };
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tensorflow-tensorboard = callPackage ./tf-tensorboard.nix {
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protobuf = protobuf3_5;
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};
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tensorflow = callPackage ./tf.nix {
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protobuf = protobuf3_5;
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cudaSupport = pkgs.config.cudaSupport or false;
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cudatoolkit = pkgs.cudatoolkit90;
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cudnn = pkgs.cudnn_cudatoolkit90;
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inherit (pkgs.linuxPackages) nvidia_x11;
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};
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# https://github.com/NixOS/nixpkgs/pull/26580 (Cuda definitions are backwards too)
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libgpuarray = callPackage ./theano-libgpuarray.nix {
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clblas = pkgs.clblas.override { inherit boost; };
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cudaSupport = pkgs.config.cudaSupport or false;
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inherit (pkgs.linuxPackages) nvidia_x11;
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};
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Theano = callPackage ./theano.nix rec {
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cudaSupport = pkgs.config.cudaSupport or false;
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cudnnSupport = cudaSupport;
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cudatoolkit = pkgs.cudatoolkit8;
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cudnn = pkgs.cudnn_cudatoolkit8;
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inherit (pkgs.linuxPackages) nvidia_x11;
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};
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TheanoWithoutCuda = super.TheanoWithoutCuda.override {
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cudaSupport = false;
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cudnnSupport = false;
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};
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TheanoWithCuda = super.TheanoWithCuda.override {
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cudaSupport = true;
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cudnnSupport = true;
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};
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}
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@@ -1,9 +1,3 @@
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pkgs: self: super: with self; {
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# OTRS 40979 (0.13.0 has issues locating libjulia.so)
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JuliaCall = super.JuliaCall.override {
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version = "0.14.0";
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sha256 = "1zrj1jn55qxxg95h1rfbfgzd7dn3hxm7gkwbin6zkcxi8qdc3690";
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depends = [R6 Rcpp];
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};
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}
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@@ -1,17 +0,0 @@
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{ stdenv, fetchPypi, buildPythonPackage, six }:
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buildPythonPackage rec {
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pname = "astunparse";
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version = "1.5.0";
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src = fetchPypi {
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inherit pname version;
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sha256 = "1kc9lm2jvfcip3z8snj04dar5a9jh857a704m6lvcv4xclm3rpsm";
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};
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propagatedBuildInputs = [ six ];
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doCheck = false; # no tests
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meta = with stdenv.lib; {
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description = "This is a factored out version of unparse found in the Python source distribution";
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license = licenses.bsd3;
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maintainers = with maintainers; [ jyp ];
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};
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}
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@@ -1,161 +0,0 @@
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{ lib, stdenv, makeWrapper, fetchurl, requireFile, patchelf, perl, ncurses, expat, python27, zlib
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, gcc6
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, xorg, gtk2, glib, fontconfig, freetype, unixODBC, alsaLib, glibc
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}:
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let
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common =
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args@{ gcc, version, sha256
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, url ? ""
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, name ? ""
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, developerProgram ? false
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, python ? python27
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, runPatches ? []
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}:
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stdenv.mkDerivation rec {
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name = "cudatoolkit-${version}";
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inherit version runPatches;
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dontPatchELF = true;
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dontStrip = true;
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src =
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if developerProgram then
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requireFile {
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message = ''
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This nix expression requires that ${args.name} is already part of the store.
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Register yourself to NVIDIA Accelerated Computing Developer Program, retrieve the CUDA toolkit
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at https://developer.nvidia.com/cuda-toolkit, and run the following command in the download directory:
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nix-prefetch-url file://\$PWD/${args.name}
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'';
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inherit (args) name sha256;
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}
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else
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fetchurl {
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inherit (args) url sha256;
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};
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outputs = [ "out" "lib" "doc" ];
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nativeBuildInputs = [ perl makeWrapper ];
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runtimeDependencies = [
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ncurses expat python zlib glibc
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xorg.libX11 xorg.libXext xorg.libXrender xorg.libXt xorg.libXtst xorg.libXi xorg.libXext
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gtk2 glib fontconfig freetype unixODBC alsaLib
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];
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rpath = "${stdenv.lib.makeLibraryPath runtimeDependencies}:${stdenv.cc.cc.lib}/lib64";
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phases = [ "unpackPhase" "installPhase" "fixupPhase" ];
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unpackPhase = ''
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sh $src --keep --noexec
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cd pkg/run_files
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sh cuda-linux*.run --keep --noexec
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sh cuda-samples*.run --keep --noexec
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mv pkg ../../$(basename $src)
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cd ../..
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rm -rf pkg
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for patch in $runPatches; do
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sh $patch --keep --noexec
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mv pkg $(basename $patch)
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done
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'';
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installPhase = ''
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mkdir $out
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cd $(basename $src)
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perl ./install-linux.pl --prefix="$out"
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cd ..
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for patch in $runPatches; do
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cd $(basename $patch)
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perl ./install_patch.pl --silent --accept-eula --installdir="$out"
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cd ..
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done
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rm $out/tools/CUDA_Occupancy_Calculator.xls # FIXME: why?
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# let's remove the 32-bit libraries, they confuse the lib64->lib mover
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rm -rf $out/lib
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# Remove some cruft.
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rm $out/bin/uninstall*
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# Fixup path to samples (needed for cuda 6.5 or else nsight will not find them)
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if [ -d "$out"/cuda-samples ]; then
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mv "$out"/cuda-samples "$out"/samples
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fi
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# Change the #error on GCC > 4.9 to a #warning.
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sed -i $out/include/host_config.h -e 's/#error\(.*unsupported GNU version\)/#warning\1/'
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# Fix builds with newer glibc version
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sed -i "1 i#define _BITS_FLOATN_H" "$out/include/host_defines.h"
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# Ensure that cmake can find CUDA.
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mkdir -p $out/nix-support
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echo "cmakeFlags+=' -DCUDA_TOOLKIT_ROOT_DIR=$out'" >> $out/nix-support/setup-hook
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# Move some libraries to the lib output so that programs that
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# depend on them don't pull in this entire monstrosity.
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mkdir -p $lib/lib
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mv -v $out/lib64/libcudart* $lib/lib/
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# Remove OpenCL libraries as they are provided by ocl-icd and driver.
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rm -f $out/lib64/libOpenCL*
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# Set compiler for NVCC.
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wrapProgram $out/bin/nvcc \
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--prefix PATH : ${gcc}/bin
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'' + lib.optionalString (lib.versionOlder version "8.0") ''
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# Hack to fix building against recent Glibc/GCC.
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echo "NIX_CFLAGS_COMPILE+=' -D_FORCE_INLINES'" >> $out/nix-support/setup-hook
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'';
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preFixup = ''
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while IFS= read -r -d ''$'\0' i; do
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if ! isELF "$i"; then continue; fi
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echo "patching $i..."
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if [[ ! $i =~ \.so ]]; then
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patchelf \
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--set-interpreter "''$(cat $NIX_CC/nix-support/dynamic-linker)" $i
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fi
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if [[ $i =~ libcudart ]]; then
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rpath2=
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else
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rpath2=$rpath:$lib/lib:$out/jre/lib/amd64/jli:$out/lib:$out/lib64:$out/nvvm/lib:$out/nvvm/lib64
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fi
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patchelf --set-rpath $rpath2 --force-rpath $i
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done < <(find $out $lib $doc -type f -print0)
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'';
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passthru = {
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cc = gcc;
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majorVersion =
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let versionParts = lib.splitString "." version;
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in "${lib.elemAt versionParts 0}.${lib.elemAt versionParts 1}";
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};
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meta = with stdenv.lib; {
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description = "A compiler for NVIDIA GPUs, math libraries, and tools";
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homepage = "https://developer.nvidia.com/cuda-toolkit";
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platforms = [ "x86_64-linux" ];
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license = licenses.unfree;
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};
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};
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in {
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cudatoolkit90 = common {
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version = "9.0.176.1";
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url = "https://developer.nvidia.com/compute/cuda/9.0/Prod/local_installers/cuda_9.0.176_384.81_linux-run";
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sha256 = "0308rmmychxfa4inb1ird9bpgfppgr9yrfg1qp0val5azqik91ln";
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gcc = gcc6;
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};
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}
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@@ -1,56 +0,0 @@
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{ version
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, srcName
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, sha256
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}:
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{ stdenv
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, lib
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, requireFile
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, cudatoolkit
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}:
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stdenv.mkDerivation rec {
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name = "cudatoolkit-${cudatoolkit.majorVersion}-cudnn-${version}";
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inherit version;
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src = requireFile rec {
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name = srcName;
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inherit sha256;
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message = ''
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This nix expression requires that ${name} is already part of the store.
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Register yourself to NVIDIA Accelerated Computing Developer Program, retrieve the cuDNN library
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at https://developer.nvidia.com/cudnn, and run the following command in the download directory:
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nix-prefetch-url file://\$PWD/${name}
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'';
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};
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installPhase = ''
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function fixRunPath {
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p=$(patchelf --print-rpath $1)
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patchelf --set-rpath "$p:${lib.makeLibraryPath [ stdenv.cc.cc ]}" $1
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}
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fixRunPath lib64/libcudnn.so
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mkdir -p $out
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cp -a include $out/include
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cp -a lib64 $out/lib64
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'';
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propagatedBuildInputs = [
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cudatoolkit
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];
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passthru = {
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inherit cudatoolkit;
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majorVersion = lib.head (lib.splitString "." version);
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};
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meta = with stdenv.lib; {
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description = "NVIDIA CUDA Deep Neural Network library (cuDNN)";
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homepage = "https://developer.nvidia.com/cudnn";
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license = licenses.unfree;
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platforms = [ "x86_64-linux" ];
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maintainers = with maintainers; [ mdaiter ];
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||||
};
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}
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@@ -1,17 +0,0 @@
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{ callPackage, cudatoolkit90 }:
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let
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generic = args: callPackage (import ./tf-cudnn-generic.nix (removeAttrs args ["cudatoolkit"])) {
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inherit (args) cudatoolkit;
|
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};
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|
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in
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|
||||
{
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cudnn_cudatoolkit90 = generic rec {
|
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version = "7.0.5";
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cudatoolkit = cudatoolkit90;
|
||||
srcName = "cudnn-${cudatoolkit.majorVersion}-linux-x64-v7.tgz";
|
||||
sha256 = "03mbv4m5lhwnc181xz8li067pjzzhxqbxgnrfc68dffm8xj0fghs";
|
||||
};
|
||||
}
|
||||
@@ -1,16 +0,0 @@
|
||||
{ stdenv, fetchPypi, buildPythonPackage, astunparse }:
|
||||
|
||||
buildPythonPackage rec {
|
||||
pname = "gast";
|
||||
version = "0.2.0";
|
||||
src = fetchPypi {
|
||||
inherit pname version;
|
||||
sha256 = "0c296xm1vz9x4w4inmdl0k8mnc0i9arw94si2i7pglpc461r0s3h";
|
||||
};
|
||||
checkInputs = [ astunparse ] ;
|
||||
meta = with stdenv.lib; {
|
||||
description = "GAST provides a compatibility layer between the AST of various Python versions, as produced by ast.parse from the standard ast module.";
|
||||
license = licenses.bsd3;
|
||||
maintainers = with maintainers; [ jyp ];
|
||||
};
|
||||
}
|
||||
@@ -1,34 +0,0 @@
|
||||
{
|
||||
linux_py_27_cpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.9.0-cp27-none-linux_x86_64.whl";
|
||||
sha256 = "1dvmajv5ddgzrazdnxpfhk9dkj0lfiviw4jmvk00d4q5v68z6ihg";
|
||||
};
|
||||
linux_py_35_cpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.9.0-cp35-cp35m-linux_x86_64.whl";
|
||||
sha256 = "07ilrxbhz9p3xwqhl2p8c40y1gsq68x10f34pzayrvcg2i52bvpv";
|
||||
};
|
||||
linux_py_36_cpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/cpu/tensorflow-1.9.0-cp36-cp36m-linux_x86_64.whl";
|
||||
sha256 = "0x2l64ab7i8nr0dzvsryblhn869qyjb85xkhy69nwahqswb68hxl";
|
||||
};
|
||||
linux_py_27_gpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.9.0-cp27-none-linux_x86_64.whl";
|
||||
sha256 = "0q7i82jgy0mzn2mw8i1z0pvv7ssi6m7zqkkjg2i4zxpk8djg8k6z";
|
||||
};
|
||||
linux_py_35_gpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.9.0-cp35-cp35m-linux_x86_64.whl";
|
||||
sha256 = "0nhq2s8fanm095x1sc9h40dvqcv9bc2aj47crv3c2sajbj7dn43g";
|
||||
};
|
||||
linux_py_36_gpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-1.9.0-cp36-cp36m-linux_x86_64.whl";
|
||||
sha256 = "1m4b9cd8ghghqxaqrlzq7j9499ddidgr78bx0c20pgyrzg38jiz1";
|
||||
};
|
||||
mac_py_2_cpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.9.0-py2-none-any.whl";
|
||||
sha256 = "1djj0xahzrmxhfc6kyjx1lkyfh7jhq3ix0gz9j3iq4smb3ca9z01";
|
||||
};
|
||||
mac_py_3_cpu = {
|
||||
url = "https://storage.googleapis.com/tensorflow/mac/cpu/tensorflow-1.9.0-py3-none-any.whl";
|
||||
sha256 = "0igffy7r0d8mhkn4pybp19jmc25alfpfl4k4fxh2s3rvgii8gk22";
|
||||
};
|
||||
}
|
||||
@@ -1,39 +0,0 @@
|
||||
{ stdenv, lib, fetchPypi, buildPythonPackage, isPy3k
|
||||
, numpy
|
||||
, werkzeug
|
||||
, protobuf
|
||||
, grpcio
|
||||
, markdown
|
||||
, futures
|
||||
}:
|
||||
|
||||
# tensorflow/tensorboard is built from a downloaded wheel, because
|
||||
# https://github.com/tensorflow/tensorboard/issues/719 blocks
|
||||
# buildBazelPackage.
|
||||
|
||||
buildPythonPackage rec {
|
||||
pname = "tensorflow-tensorboard";
|
||||
version = "1.9.0";
|
||||
format = "wheel";
|
||||
|
||||
src = fetchPypi ({
|
||||
pname = "tensorboard";
|
||||
inherit version;
|
||||
format = "wheel";
|
||||
} // (if isPy3k then {
|
||||
python = "py3";
|
||||
sha256 = "42a04637a636e16054b065907c81396b83a9702948ecd14218f19dc5cf85de98";
|
||||
} else {
|
||||
python = "py2";
|
||||
sha256 = "97661706fbe857c372405e0f5bd7c3db2197b5e70cec88f6924b726fde65c2c1";
|
||||
}));
|
||||
|
||||
propagatedBuildInputs = [ numpy werkzeug protobuf markdown grpcio ] ++ lib.optional (!isPy3k) futures;
|
||||
|
||||
meta = with stdenv.lib; {
|
||||
description = "TensorFlow's Visualization Toolkit";
|
||||
homepage = http://tensorflow.org;
|
||||
license = licenses.asl20;
|
||||
maintainers = with maintainers; [ abbradar ];
|
||||
};
|
||||
}
|
||||
@@ -1,91 +0,0 @@
|
||||
{ stdenv
|
||||
, lib
|
||||
, fetchurl
|
||||
, buildPythonPackage
|
||||
, isPy3k, isPy36, pythonOlder
|
||||
, astor
|
||||
, gast
|
||||
, numpy
|
||||
, six
|
||||
, termcolor
|
||||
, protobuf
|
||||
, absl-py
|
||||
, grpcio
|
||||
, mock
|
||||
, backports_weakref
|
||||
, enum34
|
||||
, tensorflow-tensorboard
|
||||
, cudaSupport ? false
|
||||
, cudatoolkit ? null
|
||||
, cudnn ? null
|
||||
, nvidia_x11 ? null
|
||||
, zlib
|
||||
, python
|
||||
, symlinkJoin
|
||||
}:
|
||||
|
||||
# We keep this binary build for two reasons:
|
||||
# - the source build doesn't work on Darwin.
|
||||
# - the source build is currently brittle and not easy to maintain
|
||||
|
||||
assert cudaSupport -> cudatoolkit != null
|
||||
&& cudnn != null
|
||||
&& nvidia_x11 != null;
|
||||
let
|
||||
cudatoolkit_joined = symlinkJoin {
|
||||
name = "unsplit_cudatoolkit";
|
||||
paths = [ cudatoolkit.out
|
||||
cudatoolkit.lib ];};
|
||||
|
||||
in buildPythonPackage rec {
|
||||
pname = "tensorflow";
|
||||
version = "1.9.0";
|
||||
format = "wheel";
|
||||
|
||||
src = let
|
||||
pyVerNoDot = lib.strings.stringAsChars (x: if x == "." then "" else x) "${python.majorVersion}";
|
||||
pyver = if stdenv.isDarwin then builtins.substring 0 1 pyVerNoDot else pyVerNoDot;
|
||||
platform = if stdenv.isDarwin then "mac" else "linux";
|
||||
unit = if cudaSupport then "gpu" else "cpu";
|
||||
key = "${platform}_py_${pyver}_${unit}";
|
||||
dls = import ./tf-hashes-1.9.0.nix;
|
||||
in fetchurl dls.${key};
|
||||
|
||||
propagatedBuildInputs = [ protobuf numpy termcolor grpcio six astor absl-py gast tensorflow-tensorboard ]
|
||||
++ lib.optional (!isPy3k) mock
|
||||
++ lib.optionals (pythonOlder "3.4") [ backports_weakref enum34 ];
|
||||
|
||||
# Upstream has a pip hack that results in bin/tensorboard being in both tensorflow
|
||||
# and the propageted input tensorflow-tensorboard which causes environment collisions.
|
||||
# another possibility would be to have tensorboard only in the buildInputs
|
||||
# https://github.com/tensorflow/tensorflow/blob/v1.7.1/tensorflow/tools/pip_package/setup.py#L79
|
||||
postInstall = ''
|
||||
rm $out/bin/tensorboard
|
||||
'';
|
||||
|
||||
installFlags = "--no-dependencies"; # tensorflow wants setuptools 39, can't allow that.
|
||||
# Note that we need to run *after* the fixup phase because the
|
||||
# libraries are loaded at runtime. If we run in preFixup then
|
||||
# patchelf --shrink-rpath will remove the cuda libraries.
|
||||
postFixup = let
|
||||
rpath = stdenv.lib.makeLibraryPath
|
||||
([ stdenv.cc.cc.lib zlib ] ++ lib.optionals cudaSupport [ cudatoolkit_joined cudnn nvidia_x11 ]);
|
||||
in
|
||||
lib.optionalString (stdenv.isLinux) ''
|
||||
rrPath="$out/${python.sitePackages}/tensorflow/:${rpath}"
|
||||
internalLibPath="$out/${python.sitePackages}/tensorflow/python/_pywrap_tensorflow_internal.so"
|
||||
find $out -name '*${stdenv.hostPlatform.extensions.sharedLibrary}' -exec patchelf --set-rpath "$rrPath" {} \;
|
||||
'';
|
||||
|
||||
|
||||
meta = with stdenv.lib; {
|
||||
description = "Computation using data flow graphs for scalable machine learning";
|
||||
homepage = http://tensorflow.org;
|
||||
license = licenses.asl20;
|
||||
maintainers = with maintainers; [ jyp abbradar ];
|
||||
platforms = with platforms; linux ++ lib.optionals (!cudaSupport) darwin;
|
||||
# Python 2.7 build uses different string encoding.
|
||||
# See https://github.com/NixOS/nixpkgs/pull/37044#issuecomment-373452253
|
||||
broken = stdenv.isDarwin && !isPy3k;
|
||||
};
|
||||
}
|
||||
@@ -1,83 +0,0 @@
|
||||
{ stdenv
|
||||
, lib
|
||||
, buildPythonPackage
|
||||
, fetchFromGitHub
|
||||
, cmake
|
||||
, cython
|
||||
, numpy
|
||||
, six
|
||||
, nose
|
||||
, Mako
|
||||
, cudaSupport ? false, cudatoolkit , nvidia_x11
|
||||
, openclSupport ? true, ocl-icd, clblas
|
||||
}:
|
||||
|
||||
assert cudaSupport -> nvidia_x11 != null
|
||||
&& cudatoolkit != null;
|
||||
|
||||
buildPythonPackage rec {
|
||||
pname = "libgpuarray";
|
||||
version = "0.7.5";
|
||||
name = pname + "-" + version;
|
||||
|
||||
src = fetchFromGitHub {
|
||||
owner = "Theano";
|
||||
repo = "libgpuarray";
|
||||
rev = "v${version}";
|
||||
sha256 = "0zkdwjq3k6ciiyf8y5w663fbsnmzhgy27yvpxfhkpxazw9vg3l5v";
|
||||
};
|
||||
|
||||
# requires a GPU
|
||||
doCheck = false;
|
||||
|
||||
configurePhase = "cmakeConfigurePhase";
|
||||
|
||||
libraryPath = lib.makeLibraryPath (
|
||||
[]
|
||||
++ lib.optionals cudaSupport [ cudatoolkit.lib cudatoolkit.out nvidia_x11 ]
|
||||
++ lib.optionals openclSupport ([ clblas ] ++ lib.optional (!stdenv.isDarwin) ocl-icd)
|
||||
);
|
||||
|
||||
preBuild = ''
|
||||
make -j$NIX_BUILD_CORES
|
||||
make install
|
||||
|
||||
export NIX_CFLAGS_COMPILE="-L $out/lib -I $out/include $NIX_CFLAGS_COMPILE"
|
||||
|
||||
cd ..
|
||||
'';
|
||||
|
||||
postFixup = ''
|
||||
rm $out/lib/libgpuarray-static.a
|
||||
'' + stdenv.lib.optionalString (!stdenv.isDarwin) ''
|
||||
function fixRunPath {
|
||||
p=$(patchelf --print-rpath $1)
|
||||
patchelf --set-rpath "$p:$libraryPath" $1
|
||||
}
|
||||
|
||||
fixRunPath $out/lib/libgpuarray.so
|
||||
'';
|
||||
|
||||
propagatedBuildInputs = [
|
||||
numpy
|
||||
six
|
||||
Mako
|
||||
];
|
||||
|
||||
enableParallelBuilding = true;
|
||||
|
||||
buildInputs = [
|
||||
cmake
|
||||
cython
|
||||
nose
|
||||
];
|
||||
|
||||
meta = with stdenv.lib; {
|
||||
homepage = "https://github.com/Theano/libgpuarray";
|
||||
description = "Library to manipulate tensors on GPU.";
|
||||
license = licenses.free;
|
||||
maintainers = with maintainers; [ artuuge ];
|
||||
platforms = platforms.unix;
|
||||
};
|
||||
|
||||
}
|
||||
@@ -1,88 +0,0 @@
|
||||
{ stdenv
|
||||
, runCommandCC
|
||||
, lib
|
||||
, fetchPypi
|
||||
, gcc
|
||||
, buildPythonPackage
|
||||
, isPyPy
|
||||
, pythonOlder
|
||||
, isPy3k
|
||||
, nose
|
||||
, numpy
|
||||
, scipy
|
||||
, six
|
||||
, libgpuarray
|
||||
, cudaSupport ? false, cudatoolkit
|
||||
, cudnnSupport ? false, cudnn
|
||||
, nvidia_x11
|
||||
}:
|
||||
|
||||
assert cudnnSupport -> cudaSupport;
|
||||
|
||||
assert cudaSupport -> nvidia_x11 != null
|
||||
&& cudatoolkit != null
|
||||
&& cudnn != null;
|
||||
|
||||
let
|
||||
wrapped = command: buildTop: buildInputs:
|
||||
runCommandCC "${command}-wrapped" { inherit buildInputs; } ''
|
||||
type -P '${command}' || { echo '${command}: not found'; exit 1; }
|
||||
cat > "$out" <<EOF
|
||||
#!$(type -P bash)
|
||||
$(declare -xp | sed -e '/^[^=]\+="\('"''${NIX_STORE//\//\\/}"'\|[^\/]\)/!d')
|
||||
declare -x NIX_BUILD_TOP="${buildTop}"
|
||||
$(type -P '${command}') "\$@"
|
||||
EOF
|
||||
chmod +x "$out"
|
||||
'';
|
||||
|
||||
# Theano spews warnings and disabled flags if the compiler isn't named g++
|
||||
cxx_compiler = wrapped "g++" "\\$HOME/.theano"
|
||||
( stdenv.lib.optional cudaSupport libgpuarray_
|
||||
++ stdenv.lib.optional cudnnSupport cudnn );
|
||||
|
||||
libgpuarray_ = libgpuarray.override { inherit cudaSupport cudatoolkit; };
|
||||
|
||||
in buildPythonPackage rec {
|
||||
pname = "Theano";
|
||||
version = "1.0.2";
|
||||
|
||||
disabled = isPyPy || pythonOlder "2.6" || (isPy3k && pythonOlder "3.3");
|
||||
|
||||
src = fetchPypi {
|
||||
inherit pname version;
|
||||
sha256 = "6768e003d328a17011e6fca9126fbb8a6ffd3bb13cb21c450f3e724cca29abde";
|
||||
};
|
||||
|
||||
postPatch = ''
|
||||
substituteInPlace theano/configdefaults.py \
|
||||
--replace 'StrParam(param, is_valid=warn_cxx)' 'StrParam('\'''${cxx_compiler}'\''', is_valid=warn_cxx)' \
|
||||
--replace 'rc == 0 and config.cxx != ""' 'config.cxx != ""'
|
||||
'' + stdenv.lib.optionalString cudaSupport ''
|
||||
substituteInPlace theano/configdefaults.py \
|
||||
--replace 'StrParam(get_cuda_root)' 'StrParam('\'''${cudatoolkit}'\''')'
|
||||
'' + stdenv.lib.optionalString cudnnSupport ''
|
||||
substituteInPlace theano/configdefaults.py \
|
||||
--replace 'StrParam(default_dnn_base_path)' 'StrParam('\'''${cudnn}'\''')'
|
||||
'';
|
||||
|
||||
preCheck = ''
|
||||
mkdir -p check-phase
|
||||
export HOME=$(pwd)/check-phase
|
||||
'';
|
||||
doCheck = false;
|
||||
# takes far too long, also throws "TypeError: sort() missing 1 required positional argument: 'a'"
|
||||
# when run from the installer, and testing with Python 3.5 hits github.com/Theano/Theano/issues/4276,
|
||||
# the fix for which hasn't been merged yet.
|
||||
|
||||
# keep Nose around since running the tests by hand is possible from Python or bash
|
||||
checkInputs = [ nose ];
|
||||
propagatedBuildInputs = [ numpy numpy.blas scipy six libgpuarray_ ];
|
||||
|
||||
meta = with stdenv.lib; {
|
||||
homepage = http://deeplearning.net/software/theano/;
|
||||
description = "A Python library for large-scale array computation";
|
||||
license = licenses.bsd3;
|
||||
maintainers = with maintainers; [ maintainers.bcdarwin ];
|
||||
};
|
||||
}
|
||||
Reference in New Issue
Block a user