Update embedded-devices example for the latest PyTorch and JetPack #4399
Labels
part: examples
Add or update a Flower example
state: revision needed
Revision required before maintainers can act on Issue/PR.
type: feature request
This issue or comment suggests an additional feature.
Describe the type of feature and its functionality.
Following @jafermarq's suggestion(#4381 , #4382 ), I am creating this new issue.
How would you feel about providing guidelines for the build script?
I’ve modified the build script (
build_jetson_flower_client.sh
) to use Flower (flwr
) with JetPack 6.0 and successfully tested it. I believe it would be beneficial to provide guidelines for the build script. Utilizing the BASE_PYTORCH variable could simplify the process compared to reinstalling PyTorch from scratch.Currently, the NVIDIA NGC Catalog offers base images supporting up to PyTorch v2.0.0. Additionally, with a bit more searching, we can find the dustynv base image for PyTorch v2.2.0, which is compatible with JetPack 6.0. I have also confirmed on the NVIDIA forums that the R36.2 container image is compatible with R36.3.
Let me know if this approach aligns with your plans or if there's anything else I can assist with. I'm happy to help further, whether it's refining the build script guidelines or contributing in other ways!
Describe step by step what files and adjustments are you planning to include.
build_jetson_flower_client.sh
`Update the build script to accept the BASE_PYTORCH and BASE_TF variables as input arguments.
Ensure that the script defaults to a standard base image if no argument is provided.
Dockerfile
`In my experience using the dusty-nv base image, I encountered an issue where libsndfile1 was missing. To resolve this, I added the following command to the Dockerfile:
README.md
`Add a table that lists the available base images along with a brief description and reference links.
Is there something else you want to add?
No response
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