paths = cuda-common-redist; }; in <del> stdenv.mkDerivation (finalAttrs: { name = "tiny-cuda-nn"; version = "1.6"; format = strings.optionalString pythonSupport "setuptools"; src = fetchFromGitHub { owner = "NVlabs"; repo = finalAttrs.name; rev = "v${finalAttrs.version}"; fetchSubmodules = true; hash = "sha256-qW6Fk2GB71fvZSsfu+mykabSxEKvaikZ/pQQZUycOy0="; }; nativeBuildInputs = [ cmake cuda-native-redist ninja which ] ++ lists.optionals pythonSupport (with python3Packages; [ pip setuptools wheel ]); buildInputs = [ cuda-redist ] ++ lib.optionals pythonSupport ( with python3Packages; [ pybind11 python ] ); propagatedBuildInputs = lib.optionals pythonSupport ( with python3Packages; [ torch ] ); # NOTE: We cannot use pythonImportsCheck for this module because it uses torch to immediately #   initailize CUDA and GPU access is not allowed in the nix build environment. # NOTE: There are no tests for the C++ library or the python bindings, so we just skip the check #   phase -- we're not missing anything. doCheck = false; preConfigure = '' export TCNN_CUDA_ARCHITECTURES=${ strings.concatStringsSep ";" (lists.map cudaFlags.dropDot cudaFlags.cudaCapabilities) } export CUDA_HOME=${cuda-native-redist} export LIBRARY_PATH=${cuda-native-redist}/lib/stubs:$LIBRARY_PATH export CC=${backendStdenv.cc}/bin/cc export CXX=${backendStdenv.cc}/bin/c++ ''; # When building the python bindings, we cannot re-use the artifacts from the C++ build so we # skip the CMake confurePhase and the buildPhase. dontUseCmakeConfigure = pythonSupport; # The configurePhase usually puts you in the build directory, so for the python bindings we # need to change directories to the source directory. configurePhase = strings.optionalString pythonSupport '' runHook preConfigure mkdir -p $NIX_BUILD_TOP/build cd $NIX_BUILD_TOP/build runHook postConfigure ''; buildPhase = strings.optionalString pythonSupport '' runHook preBuild python -m pip wheel  --no-build-isolation  --no-clean  --no-deps  --no-index  --verbose  --wheel-dir $NIX_BUILD_TOP/build  $NIX_BUILD_TOP/source/bindings/torch runHook postBuild ''; installPhase = '' runHook preInstall mkdir -p $out/lib '' # Installing the C++ library just requires copying the static library to the output directory + strings.optionalString (!pythonSupport) '' cp libtiny-cuda-nn.a $out/lib/ '' # Installing the python bindings requires building the wheel and installing it + strings.optionalString pythonSupport '' python -m pip install  --no-build-isolation  --no-cache-dir  --no-deps  --no-index  --no-warn-script-location  --prefix="$out"  --verbose  ./*.whl '' + '' runHook postInstall ''; passthru = { inherit cudaPackages; }; meta = with lib; { description = "Lightning fast C++/CUDA neural network framework"; homepage = "https://github.com/NVlabs/tiny-cuda-nn"; license = licenses.bsd3; maintainers = with maintainers; [ connorbaker ]; platforms = platforms.linux; }; }) </del> <ins> stdenv.mkDerivation (finalAttrs: { pname = "tiny-cuda-nn"; version = "1.6"; strictDeps = true; format = strings.optionalString pythonSupport "setuptools"; src = fetchFromGitHub { owner = "NVlabs"; repo = finalAttrs.pname; rev = "v${finalAttrs.version}"; fetchSubmodules = true; hash = "sha256-qW6Fk2GB71fvZSsfu+mykabSxEKvaikZ/pQQZUycOy0="; }; nativeBuildInputs = [ cmake cuda-native-redist ninja which ] ++ lists.optionals pythonSupport (with python3Packages; [ pip setuptools wheel ]); buildInputs = [ cuda-redist ] ++ lib.optionals pythonSupport ( with python3Packages; [ pybind11 python ] ); propagatedBuildInputs = lib.optionals pythonSupport ( with python3Packages; [ torch ] ); # NOTE: We cannot use pythonImportsCheck for this module because it uses torch to immediately #   initailize CUDA and GPU access is not allowed in the nix build environment. # NOTE: There are no tests for the C++ library or the python bindings, so we just skip the check #   phase -- we're not missing anything. doCheck = false; preConfigure = '' export TCNN_CUDA_ARCHITECTURES="${ strings.concatStringsSep ";" (lists.map cudaFlags.dropDot cudaFlags.cudaCapabilities) }" export CUDA_HOME="${cuda-native-redist}" export LIBRARY_PATH="${cuda-native-redist}/lib/stubs:$LIBRARY_PATH" export CC="${backendStdenv.cc}/bin/cc" export CXX="${backendStdenv.cc}/bin/c++" ''; # When building the python bindings, we cannot re-use the artifacts from the C++ build so we # skip the CMake confurePhase and the buildPhase. dontUseCmakeConfigure = pythonSupport; # The configurePhase usually puts you in the build directory, so for the python bindings we # need to change directories to the source directory. configurePhase = strings.optionalString pythonSupport '' runHook preConfigure mkdir -p "$NIX_BUILD_TOP/build" cd "$NIX_BUILD_TOP/build" runHook postConfigure ''; buildPhase = strings.optionalString pythonSupport '' runHook preBuild python -m pip wheel  --no-build-isolation  --no-clean  --no-deps  --no-index  --verbose  --wheel-dir "$NIX_BUILD_TOP/build"  "$NIX_BUILD_TOP/source/bindings/torch" runHook postBuild ''; installPhase = '' runHook preInstall mkdir -p "$out/lib" '' # Installing the C++ library just requires copying the static library to the output directory + strings.optionalString (!pythonSupport) '' cp libtiny-cuda-nn.a "$out/lib/" '' # Installing the python bindings requires building the wheel and installing it + strings.optionalString pythonSupport '' python -m pip install  --no-build-isolation  --no-cache-dir  --no-deps  --no-index  --no-warn-script-location  --prefix="$out"  --verbose  ./*.whl '' + '' runHook postInstall ''; passthru = { inherit cudaPackages; }; meta = with lib; { description = "Lightning fast C++/CUDA neural network framework"; homepage = "https://github.com/NVlabs/tiny-cuda-nn"; license = licenses.bsd3; maintainers = with maintainers; [connorbaker]; platforms = platforms.linux; }; }) </ins>