Package Details: python-tensorrt 10.6.0.26-1

Git Clone URL: https://aur.archlinux.org/tensorrt.git (read-only, click to copy)
Package Base: tensorrt
Description: A platform for high-performance deep learning inference on NVIDIA hardware (python bindings and tools)
Upstream URL: https://developer.nvidia.com/tensorrt/
Keywords: ai artificial intelligence nvidia
Licenses: Apache-2.0, LicenseRef-custom
Provides: python-onnx-graphsurgeon, python-polygraphy, python-tensorflow-quantization
Submitter: dbermond
Maintainer: dbermond
Last Packager: dbermond
Votes: 20
Popularity: 0.98
First Submitted: 2018-07-29 16:17 (UTC)
Last Updated: 2024-11-08 22:21 (UTC)

Dependencies (18)

Sources (13)

Latest Comments

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dbermond commented on 2022-02-04 21:16 (UTC)

@Draghi Package updated. Thanks for the notice and for appreciating the package.

Draghi commented on 2022-01-18 15:49 (UTC)

trtexec does not work anymore because of a missing library: [E] [TRT] 6: [libLoader.h::DynamicLibrary::49] Error Code 6: Internal Error (Unable to load library: libnvinfer_builder_resource.so.8.2.1)

Please add it to PKGBUILD at package_tensorrt(): cp -dr --no-preserve='ownership' "TensorRT-${pkgver}/lib"/libnvinfer_builder_resource.so* "${pkgdir}/usr/lib"

Thanks for maintaining this package!

acxz commented on 2021-03-22 13:44 (UTC)

@nxxxx Take a look at the following issue: https://github.com/NVIDIA/TensorRT/issues/1064

tldr: if you want to manually install nvrtc for cuda 11.1 it works with cuda 11.2, but otherwise you need the nvrtc version provided in cuda 11.1, which means you need 11.1 for tensorrt as of now.

Homalozoa commented on 2021-03-19 07:35 (UTC)

tensorrt 7.2.3 is capable for cuda 11.2, could you remove the version constraint of cuda? thanks.

dbermond commented on 2021-02-11 15:17 (UTC)

@ilpanich As you could see, it does not build against cuda 11.2. The closed source components (downloaded from the nvidia website) strictly links to cuda 11.1 libraries and this cannot be changed, since the files are pre-compiled. So, the current source file for tensorrt 7.2.2.3 is not for cuda 11.2, but for 11.1 only. There is nothing to be fixed here, as the package is building fine. It just requires cuda11.1 from the AUR.

ilpanich commented on 2021-02-11 08:51 (UTC) (edited on 2021-02-11 08:52 (UTC) by ilpanich)

Despite NVIDIA says that the tarball is valid both for CUDA 11.1 & 11.2 ("TensorRT 7.2.2 for Linux and CUDA 11.1 & 11.2"), it seems not to build correctly with the latter. Will it be fixed?

collect2: error: ld returned 1 exit status make[2]: [parsers/onnx/CMakeFiles/getSupportedAPITest.dir/build.make:125: parsers/onnx/getSupportedAPITest] Error 1 make[1]: [CMakeFiles/Makefile2:1194: parsers/onnx/CMakeFiles/getSupportedAPITest.dir/all] Error 2

dbermond commented on 2020-10-06 18:14 (UTC)

@gsiolas cuda 11.1 broke this package. The nvidia pre-compiled binary files depends on libraries from cuda 11.0. Reverting to use only the pre-compiled files without without building the open source components (as it was made before) will not work because there would still be pre-compiled binary files linking to cuda 11.0 libraries. Workaround is to usa cuda 11.0 if you are willing to, or wait for nvidia to release a tensorrt version that supports cuda 11.1.

gsiolas commented on 2020-10-06 17:03 (UTC)

Hi, I am getting the following error:

/usr/bin/ld: /home/giorgos/Projects/tensorrt/src/TensorRT-7.2.0.14/lib/libnvinfer_plugin.so: undefined reference to `nvrtcAddNameExpression@libnvrtc.so.11.0' collect2: error: ld returned 1 exit status

any idea? thx

laudney commented on 2020-07-29 20:15 (UTC)

The package builds perfectly. It was completely amateurish mistake on my part. I had anaconda env activated which messed up all the PATHs. Thank you.

dbermond commented on 2020-07-29 18:47 (UTC)

@laudney I cannot see any reasons that may be causing your build failure. The package is building fine here, either by a normal makepkg command and also by building in a clean chroot with devtools. So everything is fine.

But by hearing you say that it cannot find libraries at the standard /usr/lib path (libcudnn.so) and that it cannot find headers at the standard /usr/include path, it looks like that something is really wrong with your system. These paths are standard ones for building on Arch Linux and do not need any additional configuration.

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