cudaPackages.tensorrt: use package expression from nixos-cuda/cuda-legacy
Signed-off-by: Connor Baker <ConnorBaker01@gmail.com>
This commit is contained in:
@@ -3,24 +3,33 @@
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backendStdenv,
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buildRedist,
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cuda_cudart,
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cudnn,
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cuda_nvrtc,
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cudaAtLeast,
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cudaMajorMinorVersion,
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lib,
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libcudla, # only for Jetson
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patchelf,
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}:
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let
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inherit (_cuda.lib) majorMinorPatch;
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inherit (backendStdenv) hasJetsonCudaCapability;
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inherit (lib.attrsets) getLib;
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inherit (backendStdenv) cudaCapabilities hostRedistSystem;
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inherit (lib.lists) optionals;
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inherit (lib.strings) concatStringsSep;
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in
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buildRedist (
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finalAttrs:
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let
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majorMinorPatchVersion = majorMinorPatch finalAttrs.version;
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majorVersion = lib.versions.major finalAttrs.version;
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tensorrtAtLeast = lib.versionAtLeast finalAttrs.version;
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tensorrtOlder = lib.versionOlder finalAttrs.version;
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# Create variables and use logical OR to allow short-circuiting.
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tensorrtAtLeast105 = tensorrtAtLeast "10.5.0";
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tensorrtAtLeast100 = tensorrtAtLeast105 || tensorrtAtLeast "10.0.0";
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allCCNewerThan75 = lib.all (lib.flip lib.versionAtLeast "7.5") cudaCapabilities;
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allCCNewerThan70 = allCCNewerThan75 || lib.all (lib.flip lib.versionAtLeast "7.0") cudaCapabilities;
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cudaCapabilitiesJSON = builtins.toJSON cudaCapabilities;
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in
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{
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redistName = "tensorrt";
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@@ -32,7 +41,12 @@ buildRedist (
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"dev"
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"include"
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"lib"
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]
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# From 10.14.1, TensorRT samples are distributed through the TensorRT GitHub repository.
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++ optionals (tensorrtOlder "10.14.1") [
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"samples"
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]
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++ [
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"static"
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# "stubs" removed in postInstall
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];
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@@ -42,8 +56,6 @@ buildRedist (
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nativeBuildInputs = [ patchelf ];
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buildInputs = [
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(getLib cudnn)
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(getLib cuda_nvrtc)
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cuda_cudart
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]
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++ optionals libcudla.meta.available [ libcudla ];
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@@ -62,38 +74,44 @@ buildRedist (
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''
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for dir in bin lib; do
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[[ -L "$dir" ]] || continue
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nixLog "replacing symlink $NIX_BUILD_TOP/$sourceRoot/$dir with $NIX_BUILD_TOP/$sourceRoot/targets/${targetString}/$dir"
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rm --verbose "$NIX_BUILD_TOP/$sourceRoot/$dir"
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mv --verbose --no-clobber "$NIX_BUILD_TOP/$sourceRoot/targets/${targetString}/$dir" "$NIX_BUILD_TOP/$sourceRoot/$dir"
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nixLog "replacing symlink $PWD/$dir with $PWD/targets/${targetString}/$dir"
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rm --verbose "$PWD/$dir"
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mv --verbose --no-clobber "$PWD/targets/${targetString}/$dir" "$PWD/$dir"
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done
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unset -v dir
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''
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# Remove symlinks if they exist
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+ ''
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for dir in include samples; do
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if [[ -L "$NIX_BUILD_TOP/$sourceRoot/targets/${targetString}/$dir" ]]; then
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nixLog "removing symlink $NIX_BUILD_TOP/$sourceRoot/targets/${targetString}/$dir"
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rm --verbose "$NIX_BUILD_TOP/$sourceRoot/targets/${targetString}/$dir"
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if [[ -L "$PWD/targets/${targetString}/$dir" ]]; then
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nixLog "removing symlink $PWD/targets/${targetString}/$dir"
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rm --verbose "$PWD/targets/${targetString}/$dir"
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fi
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done
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unset -v dir
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if [[ -d "$NIX_BUILD_TOP/$sourceRoot/targets" ]]; then
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if [[ -d "$PWD/targets" ]]; then
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nixLog "removing targets directory"
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rm --recursive --verbose "$NIX_BUILD_TOP/$sourceRoot/targets" || {
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nixErrorLog "could not delete $NIX_BUILD_TOP/$sourceRoot/targets: $(ls -laR "$NIX_BUILD_TOP/$sourceRoot/targets")"
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rm --recursive --verbose "$PWD/targets" || {
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nixErrorLog "could not delete $PWD/targets: $(ls -laR "$PWD/targets")"
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exit 1
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}
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fi
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'';
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autoPatchelfIgnoreMissingDeps = optionals hasJetsonCudaCapability [
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"libnvdla_compiler.so"
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];
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autoPatchelfIgnoreMissingDeps =
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optionals (hostRedistSystem == "linux-aarch64") [
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"libnvdla_compiler.so"
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]
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++ optionals (tensorrtAtLeast "10.13.3") [
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"libcuda.so.1"
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];
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# Create a symlink for the Onnx header files in include/onnx
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# NOTE(@connorbaker): This is shared with the tensorrt-oss package, with the `out` output swapped with `include`.
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# When updating one, check if the other should be updated.
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# TODO(@connorbaker): It seems like recent versions of TensorRT have separate libs for separate capabilities;
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# we should remove libraries older than those necessary to support requested capabilities.
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postInstall = ''
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mkdir "''${!outputInclude:?}/include/onnx"
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pushd "''${!outputInclude:?}/include" >/dev/null
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@@ -102,6 +120,7 @@ buildRedist (
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popd >/dev/null
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''
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# Move the python directory, which contains header files, to the include output.
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# NOTE: Python wheels should be built from source using the TensorRT GitHub repo.
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+ ''
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nixLog "moving python directory to include output"
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moveToOutput python "''${!outputInclude:?}"
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@@ -115,10 +134,11 @@ buildRedist (
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''
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# Remove the Windows library used for cross-compilation if it exists.
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+ ''
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if [[ -e "''${!outputLib:?}/lib/libnvinfer_builder_resource_win.so.${majorMinorPatchVersion}" ]]; then
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nixLog "removing Windows library"
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rm --verbose "''${!outputLib:?}/lib/libnvinfer_builder_resource_win.so.${majorMinorPatchVersion}"
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fi
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nixLog "removing any Windows libraries"
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for winLib in "''${!outputLib:?}/lib/"*_win*; do
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rm --verbose "$winLib"
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done
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unset -v winLib
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''
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# Remove the stub libraries.
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+ ''
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@@ -137,10 +157,35 @@ buildRedist (
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--add-needed libnvinfer_plugin.so.${majorVersion}
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'';
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passthru = {
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# The CUDNN used with TensorRT.
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inherit cudnn;
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};
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# NOTE: Like cuDNN, NVIDIA offers forward compatibility within a major releases of CUDA.
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platformAssertions = [
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{
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message =
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"tensorrt releases since 10.0.0 (found ${finalAttrs.version})"
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+ " support CUDA compute capabilities 7.0 and newer (found ${cudaCapabilitiesJSON})";
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assertion = tensorrtAtLeast100 -> allCCNewerThan70;
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}
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{
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message =
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"tensorrt releases since 10.0.0 (found ${finalAttrs.version})"
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+ " support only CUDA compute capability 8.7 (Jetson Orin) for pre-Thor Jetson devices"
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+ " (found ${cudaCapabilitiesJSON})";
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assertion =
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tensorrtAtLeast100 && hostRedistSystem == "linux-aarch64" -> cudaCapabilities == [ "8.7" ];
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}
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{
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message =
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"tensorrt releases since 10.0.0 (found ${finalAttrs.version})"
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+ " support CUDA 12.4 and newer for pre-Thor Jetson devices (found ${cudaMajorMinorVersion})";
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assertion = tensorrtAtLeast100 && hostRedistSystem == "linux-aarch64" -> cudaAtLeast "12.4";
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}
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{
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message =
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"tensorrt releases since 10.5.0 (found ${finalAttrs.version})"
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+ " support CUDA compute capabilities 7.5 and newer (found ${cudaCapabilitiesJSON})";
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assertion = tensorrtAtLeast105 -> allCCNewerThan75;
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}
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];
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meta = {
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description = "SDK that facilitates high-performance machine learning inference";
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