Please provide the following information when requesting support.
• Hardware (GTX 3080)
• Network Type (Classification)
• TLT Version ( dockers:
nvidia/tao/tao-toolkit-tf:
v3.22.05-tf1.15.5-py3:
docker_registry: nvcr.io )
format_version: 2.0
toolkit_version: 3.22.05
published_date: 05/25/2022
• Training spec file(If have, please share here)
• How to reproduce the issue ? (This is for errors. Please share the command line and the detailed log here.)
This is the issue
I have read the earlier thread and tried your instructions.
As you can see from the screen grab they did not work here.
Has the ngc command been changed recently?
1 Like
According to
!wget “NVIDIA NGC ” -P $LOCAL_PROJECT_DIR/ngccli
!unzip -u “$LOCAL_PROJECT_DIR/ngccli/$CLI” -d $LOCAL_PROJECT_DIR/ngccli/
The ngc should be available in your $LOCAL_PROJECT_DIR/ngccli/
Please check.
Then chmod +x the ngc file. And run it.
I have done that but as this shows:
‘ngc’ is at /home/peter//TAO_toolkit/jp1/ngccli/ngc-cli
it is not at ngc_assests/ngccli/ngc-cli/ngc
Please advise - it doesn’t look like a directory called 'ngc_assets has been created.
In the notebook, there is not such cell. The notebook does not mention “ngc_assets”.
See GPU-optimized AI, Machine Learning, & HPC Software | NVIDIA NGC
Agreed, but the ngc file does not run despite the fact that I have made it executable because ls: cannot access ‘ngc_assests/ngccli/ngc-cli/ngc’: No such file or directory.
Please advise
Can you use “find” command to find where is the “ngc” bin file?
I already uploaded that information in post 2, but here it is again
So, you can use below way.
! /home/peter/TAO_toolkit/jp1/ngccli/ngc-cli/ngc registry model list nvidia/tao/pretrained_classification:*
Thank you, that works. Can you explain the issue?
I am afraid you did not run below well.
Do I need to go back? Does it create other issues?
Never mind. It is not needed.
The ngc is just a tool for you to download pretrained model.
It is not related to TAO training or etc.
system
Closed
August 11, 2022, 9:58am
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