{
  cmake,
  cudaPackages,
  fetchFromGitHub,
  lib,
  ninja,
  python3Packages ? {},
  pythonSupport ? false,
  stdenv,
  symlinkJoin,
  which,
}: let
  inherit (lib) lists strings;
  inherit (cudaPackages) backendStdenv flags;

  cuda-common-redist = with cudaPackages; [
    cuda_cudart.dev # cuda_runtime.h
    cuda_cudart.lib
    cuda_cccl.dev # <nv/target>
    libcublas.dev # cublas_v2.h
    libcublas.lib
    libcusolver.dev # cusolverDn.h
    libcusolver.lib
    libcusparse.dev # cusparse.h
    libcusparse.lib
  ];

  cuda-native-redist = symlinkJoin {
    name = "cuda-redist";
    paths = with cudaPackages;
      [cuda_nvcc]
      ++ cuda-common-redist;
  };

  cuda-redist = symlinkJoin {
    name = "cuda-redist";
    paths = cuda-common-redist;
  };
in
  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="${flags.cmakeCudaArchitecturesString}"
      export CUDA_HOME="${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;
    };
  })