§2025-01-29
¶ verify jetpack6.2 installation using python
- conda activate
(base) alexlai@jetson:~$ conda activate RStudio
(RStudio) alexlai@jetson:~$ python --version
Python 3.10.16
(RStudio) alexlai@jetson:~$ R --version
R version 4.2.2 (2022-10-31) -- "Innocent and Trusting"
Copyright (C) 2022 The R Foundation for Statistical Computing
Platform: aarch64-conda-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under the terms of the
GNU General Public License versions 2 or 3.
For more information about these matters see
https://www.gnu.org/licenses/.
- veify install
(RStudio) alexlai@jetson:~$ dpkg -l | grep nvidia
ii libnvidia-container-tools 1.16.2-1 arm64 NVIDIA container runtime library (command-line tools)
ii libnvidia-container1:arm64 1.16.2-1 arm64 NVIDIA container runtime library
ii nvidia-container-toolkit 1.16.2-1 arm64 NVIDIA Container toolkit
ii nvidia-container-toolkit-base 1.16.2-1 arm64 NVIDIA Container Toolkit Base
ii nvidia-jetson-services 2.0.0 arm64 NVIDIA Jetson Package
ii nvidia-l4t-3d-core 36.4.3-20250107174145 arm64 NVIDIA GL EGL Package
ii nvidia-l4t-apt-source 36.4.3-20250107174145 arm64 NVIDIA L4T apt source list debian package
ii nvidia-l4t-bootloader 36.4.3-20250107174145 arm64 NVIDIA Bootloader Package
ii nvidia-l4t-camera 36.4.3-20250107174145 arm64 NVIDIA Camera Package
ii nvidia-l4t-configs 36.4.3-20250107174145 arm64 NVIDIA configs debian package
ii nvidia-l4t-core 36.4.3-20250107174145 arm64 NVIDIA Core Package
ii nvidia-l4t-cuda 36.4.3-20250107174145 arm64 NVIDIA CUDA Package
ii nvidia-l4t-cuda-utils 36.4.3-20250107174145 arm64 NVIDIA CUDA utilities
ii nvidia-l4t-cudadebuggingsupport 12.6-34622040.0 arm64 NVIDIA CUDA Debugger Support Package
ii nvidia-l4t-display-kernel 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA Display Kernel Modules Package
ii nvidia-l4t-dla-compiler 36.4.3-20250107174145 arm64 NVIDIA DLA Compiler Package
ii nvidia-l4t-firmware 36.4.3-20250107174145 arm64 NVIDIA Firmware Package
ii nvidia-l4t-gbm 36.4.3-20250107174145 arm64 NVIDIA GBM Package
ii nvidia-l4t-graphics-demos 36.4.3-20250107174145 arm64 NVIDIA graphics demo applications
ii nvidia-l4t-gstreamer 36.4.3-20250107174145 arm64 NVIDIA GST Application files
ii nvidia-l4t-init 36.4.3-20250107174145 arm64 NVIDIA Init debian package
ii nvidia-l4t-initrd 36.4.3-20250107174145 arm64 NVIDIA initrd debian package
ii nvidia-l4t-jetson-io 36.4.3-20250107174145 arm64 NVIDIA Jetson.IO debian package
ii nvidia-l4t-jetson-multimedia-api 36.4.3-20250107174145 arm64 NVIDIA Jetson Multimedia API is a collection of lower-level APIs that support flexible application development.
ii nvidia-l4t-jetsonpower-gui-tools 36.4.3-20250107174145 arm64 NVIDIA Jetson Power GUI Tools debian package
ii nvidia-l4t-kernel 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA Kernel Package
ii nvidia-l4t-kernel-dtbs 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA Kernel DTB Package
ii nvidia-l4t-kernel-headers 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA Linux Tegra Kernel Headers Package
ii nvidia-l4t-kernel-oot-headers 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA OOT Kernel Module Headers Package
ii nvidia-l4t-kernel-oot-modules 5.15.148-tegra-36.4.3-20250107174145 arm64 NVIDIA OOT Kernel Module Drivers Package
ii nvidia-l4t-libwayland-client0 36.4.3-20250107174145 arm64 NVIDIA Wayland Package
ii nvidia-l4t-libwayland-cursor0 36.4.3-20250107174145 arm64 NVIDIA Wayland Package
ii nvidia-l4t-libwayland-egl1 36.4.3-20250107174145 arm64 NVIDIA Wayland Package
ii nvidia-l4t-libwayland-server0 36.4.3-20250107174145 arm64 NVIDIA Wayland Package
ii nvidia-l4t-multimedia 36.4.3-20250107174145 arm64 NVIDIA Multimedia Package
ii nvidia-l4t-multimedia-utils 36.4.3-20250107174145 arm64 NVIDIA Multimedia Package
ii nvidia-l4t-nvfancontrol 36.4.3-20250107174145 arm64 NVIDIA Nvfancontrol debian package
ii nvidia-l4t-nvml 36.4.3-20250107174145 arm64 NVIDIA NVML Package
ii nvidia-l4t-nvpmodel 36.4.3-20250107174145 arm64 NVIDIA Nvpmodel debian package
ii nvidia-l4t-nvpmodel-gui-tools 36.4.3-20250107174145 arm64 NVIDIA Nvpmodel GUI Tools debian package
ii nvidia-l4t-nvsci 36.4.3-20250107174145 arm64 NVIDIA NvSci Package
ii nvidia-l4t-oem-config 36.4.3-20250107174145 arm64 NVIDIA OEM-Config Package
ii nvidia-l4t-openwfd 36.4.3-20250107174145 arm64 NVIDIA OpenWFD Package
ii nvidia-l4t-optee 36.4.3-20250107174145 arm64 OP-TEE userspace daemons, test programs and libraries
ii nvidia-l4t-pva 36.4.3-20250107174145 arm64 NVIDIA PVA Package
ii nvidia-l4t-tools 36.4.3-20250107174145 arm64 NVIDIA Public Test Tools Package
ii nvidia-l4t-vulkan-sc 36.4.3-20250107174145 arm64 NVIDIA Vulkan SC run-time package
ii nvidia-l4t-vulkan-sc-dev 36.4.3-20250107174145 arm64 NVIDIA Vulkan SC Dev package
ii nvidia-l4t-vulkan-sc-samples 36.4.3-20250107174145 arm64 NVIDIA Vulkan SC samples package
ii nvidia-l4t-vulkan-sc-sdk 36.4.3-20250107174145 arm64 NVIDIA Vulkan SC SDK package
ii nvidia-l4t-wayland 36.4.3-20250107174145 arm64 NVIDIA Wayland Package
ii nvidia-l4t-weston 36.4.3-20250107174145 arm64 NVIDIA Weston Package
ii nvidia-l4t-x11 36.4.3-20250107174145 arm64 NVIDIA X11 Package
ii nvidia-l4t-xusb-firmware 36.4.3-20250107174145 arm64 NVIDIA USB Firmware Package
- Install PyCUDA:
(RStudio) alexlai@jetson:~$ pip3 install pycuda numpy
- test_cuda.py with pycuda
import pycuda.driver as cuda
import pycuda.autoinit
def main():
print("CUDA Device Query (PyCUDA)")
print("Detected {} CUDA Capable device(s)".format(cuda.Device.count()))
for i in range(cuda.Device.count()):
gpu = cuda.Device(i)
print("Device {}: {}".format(i, gpu.name()))
print(" Compute Capability: {}.{}".format(*gpu.compute_capability()))
print(" Total Memory: {} MB".format(gpu.total_memory() // (1024 ** 2)))
if __name__ == "__main__":
main()
- run
$ python3 test_cuda.py
CUDA Device Query (PyCUDA)
Detected 1 CUDA Capable device(s)
Device 0: Orin
Compute Capability: 8.7
Total Memory: 7619 MB
- using tensorflow
import tensorflow as tf
def main():
print("TensorFlow version:", tf.__version__)
print("Num GPUs Available:", len(tf.config.list_physical_devices('GPU')))
if __name__ == "__main__":
main()
- test
$ python3 test_tensorflow.py
TensorFlow version: 2.18.0
Num GPUs Available: 0 <--- not found
- using torch
$ pip install torch
(RStudio) alexlai@jetson:~/build/src$ python3 -c "import torch; print(torch.cuda.is_available())"
False