Course-Getting Started eith AI on jetson Nano-Image Classification

Autonomous Machines Jetson & Embedded Systems Jetson Nano
1

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The CUDA environment path is correct, the error cannot be found, is it because of the CUDA version?

3

Hi,

Below is a related topic:

Could you check the suggestion first?

Thanks.

4

If you are running the Nano DLI container, also make sure that the version of the container you are running matches your L4T version. You can check your L4T version with cat /etc/nv_tegra_release

For example, L4T R32.5.0 would use this tag of the container: nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0

5

I made sure that the container version I was running matched the L4T version.
echo “sudo docker run -it --rm --network host
–volume ~/nvdli-data:/nvdli-nano/data
–device /dev/video0
–volume /usr/lib/aarch64-linux-gnu/tegra:/usr/lib/aarch64-linux-gnu/tegra
nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.4.4” > docker_dli_run.sh
chmod +x docker_dli_run.sh
./docker_dli_run.sh

6

hi，
libcurand.so.10 ，This file exists.
export LD_LIBRARY_PATH=/usr/local/cuda/lib64 ${LD_LIBRARY_PATH:+:${LD_LIBRARY_PATH}}
After running this command, what is the next step?

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7

Hi,
There is no update from you for a period, assuming this is not an issue any more.
Hence we are closing this topic. If need further support, please open a new one.
Thanks

The docker you used is for r32.4.4.
Do you also get the same version from nv_tegra_release?
Could you share the output log of cat /etc/nv_tegra_release with us?

Thanks.