Cannot see files from Getting Started with AI on Jetson Nano course

In the course Getting Started with AI on Jetson Nano I followed the steps and downloaded docker and started JupyterLab , but in the tutorial JupyterLab had files like regression , images , hello_camera etc. but mine shows folders from home , I cannot find the files of the project after follow the procedure . Can someone please tell me how to get those files ?

Hi @akshaygugnani15, did you start the Docker container? The notebooks are found inside the container, and the container also runs the JupyterLab server instance.

Does the below command does that :-

echo "sudo docker run --runtime nvidia -it --rm --network host \
    --volume ~/nvdli-data:/nvdli-nano/data \
    --volume /tmp/argus_socket:/tmp/argus_socket \
    --device /dev/video0 \
    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

I am getting an error on this command (i am guessing due to the absence of any camera module) :-

docker: Error response from daemon: error gathering device information while adding custom device “/dev/video0”: no such file or directory.

OK, yes. Try removing --device /dev/video0 by running this command instead:

echo "sudo docker run --runtime nvidia -it --rm --network host \
    --volume ~/nvdli-data:/nvdli-nano/data \
    --volume /tmp/argus_socket:/tmp/argus_socket \
    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

Also can you check that your L4T version with cat /etc/nv_tegra_release? It should match the container tag. For example, if you are running L4T R32.5.0, then use nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0 instead. The exception is that L4T R32.5.1 uses the R32.5.0 container.

Thank you . Now I’m getting output

allow 10 sec for JupyterLab to start @ http://192.168.55.1:8888 (password dlinano)
JupterLab logging location: /var/log/jupyter.log (inside the container)

but I installed jupyter lab before this tutorial so every time I go to http://192.168.55.1:8888 with pass dlinano it says invalid credentials but when i use my pass (which i gave while configuring jupyter) it opens jupyter but it dosen’t show the files as shown in the tutorial.

So what should i do to get those files on my jupyterLab.

Are you still running that other jupyter server that you previously installed? If so, shut it down. And probably exit the dlinano container and start that again too.

Could you please tell me how to exit running jupyter server and dlinano .

Hi @akshaygugnani15, you should be able to shutdown Jupyter server by opening it in your browser, and going to File->Quit. Or if you installed JupyterLab as service, you can try sudo systemctl stop jupyter

To shutdown the dlinano container, press Ctrl+D in the terminal where the container is running.

I shut down the jupyter lab from the browser . and restarted the container using commands :

> echo "sudo docker run --runtime nvidia -it --rm --network host \
--volume ~/nvdli-data:/nvdli-nano/data \
--volume /tmp/argus_socket:/tmp/argus_socket \
--device /dev/video0 \
nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0" > docker_dli_run.s

chmod +x docker_dli_run.sh

./docker_dli_run.sh

Output :

allow 10 sec for JupyterLab to start @ http://192.168.55.1:8888 (password dlinano)
JupterLab logging location: /var/log/jupyter.log (inside the container)

But still when i type in the password dlinano it says invalid credentials .

OK - shut down the container. Then, can you check that you are no longer able to connect/login to Jupyter from your browser? If you can still connect to it, then your other JupyterLab server must still be running.

Could you please explain the steps with commands by which I can shut down jupyter lab and container and then start the container from the course and get the files on jupyter lab , I am new to jetson platform so I don’t know how to use docker containers that much .

You can shut-down the container by pressing Ctrl+D in the terminal window from which you launch the container. Or you can just reboot your system, the container won’t be running after reboot.

After rebooting, can you still login to JupyterLab from your web browser? If so, that means when you installed JupyterLab (outside of container), it got installed as a service and runs automatically on boot. You may be able to disable it like so:

sudo systemctl stop jupyter.service
sudo systemctl disable jupyter.service
sudo reboot

I did reboot my module and then I went to http://192.168.55.1:8888/lab , It was still running .
Then I ran the commands :

sudo systemctl stop jupyter.service
sudo systemctl disable jupyter.service

But it failed in both commands saying :

Failed to stop jupyter.service: Unit jupyter.service not loaded.

Hi @akshaygugnani15, sorry for the delay. Unfortunately I’m not sure how JupyterLab was installed on your system outside container, such that it continues to restart (but is not a systemd service). So you may need to find the way to shut that down, or alternatively to uninstall your version of Jupyter outside container. You can run this on your system (outside of container):

pip3 uninstall jupyter

It should then not start anymore and after rebooting you should be able to start the DLI container and login to that Jupyter instance.

I did the whole setup again and then followed the steps in the tutorial again . But after running this command :-

echo "sudo docker run --runtime nvidia -it --rm --network host \
    --volume ~/nvdli-data:/nvdli-nano/data \
    --device /dev/video0 \
    nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0" > docker_dli_run.sh
chmod +x docker_dli_run.sh
./docker_dli_run.sh

I’m getting this error :-

Unable to find image 'nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0' locally
docker: Error response from daemon: Get https://nvcr.io/v2/: dial tcp: lookup nvcr.io on 127.0.0.1:53: read udp 127.0.0.1:58844->127.0.0.1:53: i/o timeout.
See 'docker run --help'.

Hi @akshaygugnani15, is your Nano connected to the internet? Are you able to ping google.com?

If so, can you sudo docker pull nvcr.io/nvidia/dli/dli-nano-ai:v2.0.1-r32.5.0?