TAO classification /bin/sh: 1: pip3: not found

I have had several attempts, using different browsers and with and without password in the address.
Googling my ip gives



firefox gives similar results


I am not using a firewall.

Can you use
$ ifconfig

BTW, did you run
$ docker run --runtime=nvidia -it --entrypoint=“” -p 8888:8888 --rm -v /var/run/docker.sock:/var/run/docker.sock nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 /bin/bash

then
# jupyter notebook --ip 0.0.0.0 --allow-root --port 8888

Blockquote
I ran this.

Try
192.168.1.4:8888

This takes me here


How do I navigate to the notebook

Download the notebook from TAO Toolkit Quick Start Guide — TAO Toolkit 3.22.05 documentation

Then run below again.

$ docker run --runtime=nvidia -it --entrypoint=“” -p 8888:8888 --rm -v /var/run/docker.sock:/var/run/docker.sock -v yourlocal_folder_where_store_notebook:/test
nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 /bin/bash

then
# jupyter notebook --ip 0.0.0.0 --allow-root --port 8888

Then find the notebook under /test

I am getting a docker: error response with the following, am I doing something wrong?


$ docker run --runtime=nvidia -it --entrypoint="" -p 8888:8888 --rm -v /var/run/docker.sock:/var/run/docker.sock -v yourlocal_folder_where_store_notebook:/test
nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 /bin/bash

“yourlocal_folder_where_store_notebook” is
“/home/peter/cv_samples_v1.4.0/classification/tao_voc”

your instructions follow:

my absolute path to where notebook is stored replaces “yourlocal_folder_where_store_notebook” follows:

Hi,
Please use correct --entrypoint=""

Ah.
How do I find my entrypoint, please? (I have never specified an entrypoint because I don’t know where I would find that - apologies)

I mean you need to type the correct "" instead of “” .

“docker run” presumably needs an entrypoint to .docker?

which is at /home/peter?

but apparently not

No. Please run as below.
$ docker run --runtime=nvidia -it --entrypoint="" -p 8888:8888 --rm -v /var/run/docker.sock:/var/run/docker.sock -v yourlocal_folder_where_store_notebook:/test
nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 /bin/bash

Despite the fact that I am now simply copy/past’ing

docker run --runtime=nvidia -it --entrypoint="" -p 8888:8888 --rm -v /var/run/docker.sock:/var/run/docker.sock -v yourlocal_folder_where_store_notebook:/test
nvcr.io/nvidia/tao/tao-toolkit-tf:v3.22.05-tf1.15.5-py3 /bin/bash

and replacing “” with the absolute path to the directory containing “config.json”, because an earlier error message seemed to be looking for that.

I am currently having no success.

I am not typing the correct “” instead of “”, but where do I find more on this, it doesn’t seem to be covered in the nVidia documentation.

What is the config.json and what did you change? Could you share the config.json?

And adding the --entrypoint="" is the workaround when user run “docker run” instead of tao launcher. (See the background in Chmod: cannot access '/opt/ngccli/ngc': No such file or directory - #2 by Morganh )
Just need to set --entrypoint="" . Not needed to set any others.

I may have found the problem.

at /home/peter/.docker/config.json it looks like this:

just an authorisation code/token

at /home/peter/TAO_toolkit/config/files/config.json it looks like this:

I created this from the instructions “Creating an Experiment Spec File” found at TAO Toolkit — TAO Toolkit 3.22.05 documentation. It contains a placeholder spec. for a real-world use case.

This feels like I have been following two different sets of instructions and I need to reconcile them.

Please advise in easy steps what I need to do: I will not make any changes until I get feedback from you…

Do you mean Image Classification — TAO Toolkit 3.22.05 documentation ?

Yes

In TAO classification user guide, I do not find any info about creating config.json.
Actually it is a training spec file according to your screenshot.

In TAO, we only need to set ~/.tao_mounts.json. It is mentioned in tao launcher section. TAO Toolkit Launcher — TAO Toolkit 3.22.05 documentation