requirements.txt failure of TensorRT 10.3 when running simple_progress_monitor on Jetson Orin Nano in Conda env #4727
Description
Description
I am trying to run the the simple_progress_monitor.py example provided in TensorRT 10.3.
The problem is with the requirements.txt file. Jetpack 6.2.1 comes with Python 3.10.12. Therefore there is no suitable version of cuda-python that cane be install since it lies between 3.10 and 3.11.
This is the error that is shown
(simple_tensorrt) jetson@jetson-desktop:/usr/src/tensorrt/samples/python/simple_progress_monitor$ conda install --yes --file requirements.txt
2 channel Terms of Service accepted
InvalidMatchSpec: Invalid spec 'cuda-python ==12.2.0;python_version<="3.10"': Invalid version '12.2.0;python_version<="3.10"': invalid character(s)
Additionally, there is a line to install pywin32 which is unparseable on the Ubuntu 22.04 system that the Jetson Orin Nano runs off.
CondaValueError: could not parse 'pywin32; platform_system == "Windows"' in: requirements.txt
Given that:
- TensorRT support of the Jetson ecosystem is a major product feature
- Jetson Orin Nano and TensorRT products are both developed by NVIDIA
- Neither the Jetson Orin Nano nor TensorRT 10.3 are retired
- Jetpack 6.2.1 is the latest officially supported version supported by NVIDIA
I would appreciate how I can run a simple TensorRT example with the Jetson Orin Nano in a smooth manner. Thanks!
Environment
TensorRT Version: 10.3.0
NVIDIA GPU: Jetson Orin Nano (Ampere)
NVIDIA Driver Version: 540.4.0 (Jetpack 6.2.1)
CUDA Version: 12.6
CUDNN Version:
Operating System: Ubuntu 22.04
Python Version (if applicable): 3.10.12
Tensorflow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if so, version): Miniconda
jetson@jetson-desktop:/usr/src/tensorrt/samples/python/simple_progress_monitor$ dpkg -l | grep tensorrt
ii nv-tensorrt-local-tegra-repo-ubuntu2204-10.3.0-cuda-12.5 1.0-1 arm64 nv-tensorrt-local-tegra repository configuration files
ii nvidia-tensorrt 6.2.1+b38 arm64 NVIDIA TensorRT Meta Package
ii nvidia-tensorrt-dev 6.2.1+b38 arm64 NVIDIA TensorRT dev Meta Package
ii tensorrt 10.3.0.30-1+cuda12.5 arm64 Meta package for TensorRT
ii tensorrt-libs 10.3.0.30-1+cuda12.5 arm64 Meta package for TensorRT runtime libraries
jetson@jetson-desktop:/usr/src/tensorrt/samples/python/simple_progress_monitor$ sudo apt-cache show nvidia-jetpack
[sudo] password for jetson:
Package: nvidia-jetpack
Source: nvidia-jetpack (6.2.1)
Version: 6.2.1+b38
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-jetpack-runtime (= 6.2.1+b38), nvidia-jetpack-dev (= 6.2.1+b38)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_6.2.1+b38_arm64.deb
Size: 29300
SHA256: dd9cb893fbe7f80d2c2348b268f17c8140b18b9dbb674fa8d79facfaa2050c53
SHA1: dc630f213f9afcb6f67c65234df7ad5c019edb9c
MD5sum: 9c8dc61bdab2b816dcc7cd253bcf6482
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Source: nvidia-jetpack (6.2)
Version: 6.2+b77
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-jetpack-runtime (= 6.2+b77), nvidia-jetpack-dev (= 6.2+b77)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_6.2+b77_arm64.deb
Size: 29298
SHA256: 70553d4b5a802057f9436677ef8ce255db386fd3b5d24ff2c0a8ec0e485c59cd
SHA1: 9deab64d12eef0e788471e05856c84bf2a0cf6e6
MD5sum: 4db65dc36434fe1f84176843384aee23
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Package: nvidia-jetpack
Source: nvidia-jetpack (6.1)
Version: 6.1+b123
Architecture: arm64
Maintainer: NVIDIA Corporation
Installed-Size: 194
Depends: nvidia-jetpack-runtime (= 6.1+b123), nvidia-jetpack-dev (= 6.1+b123)
Homepage: http://developer.nvidia.com/jetson
Priority: standard
Section: metapackages
Filename: pool/main/n/nvidia-jetpack/nvidia-jetpack_6.1+b123_arm64.deb
Size: 29312
SHA256: b6475a6108aeabc5b16af7c102162b7c46c36361239fef6293535d05ee2c2929
SHA1: f0984a6272c8f3a70ae14cb2ca6716b8c1a09543
MD5sum: a167745e1d88a8d7597454c8003fa9a4
Description: NVIDIA Jetpack Meta Package
Description-md5: ad1462289bdbc54909ae109d1d32c0a8
Relevant Files
Model link: N/A
Steps To Reproduce
- Make sure that the Jetson Orin Nano is running Jetpack 6.2.1.
- Install Miniconda
- Create a new environment
conda create --name simple_tensorrt - Set the Python environment to 3.10.12 (same as the base installation)
conda activate simple_tensorrt \ conda install python=3.10.12 - Go to location of the example
cd /usr/src/tensorrt/samples/python/simple_progress_monitor - Attempt to install the packages in the
requirements.txtfile.conda install --yes --file requirements.txt - Comment out the lines as shown below, in order for the packages to be installed.
cuda-python 12.2.0is not present on the default anaconda channel and it has to be installed separately from the NVIDIA channel.conda install nvidia::cuda-python==12.2.0
Commands or scripts: Mentioned in steps to reproduce section above.
Have you tried the latest release?:
TensorRT and Jetpack 6.2.1 do not play well together. Sticking to the official stable versions included. Dependency hell is sadly a challenge with the Jetson ecosystem which I am trying to avoid.
Attach the captured .json and .bin files from TensorRT's API Capture tool if you're on an x86_64 Unix system
N/A
Can this model run on other frameworks? For example run ONNX model with ONNXRuntime (polygraphy run <model.onnx> --onnxrt):
N/A