Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How can it work for Raspberry pi? #24

Open
oroelipas opened this issue Mar 10, 2020 · 5 comments
Open

How can it work for Raspberry pi? #24

oroelipas opened this issue Mar 10, 2020 · 5 comments

Comments

@oroelipas
Copy link

Sorry, I'm new using pytorch and tvm so maybe I understand things wrong...

As I know all models in results/tvm_compiled/ are compiled for Jetson TX2.

What do I need to run a compiled model in a Raspberry pi as in tx2_run_tvm.py ?

I guess I have to Compile the model using tvm as explained in this tutorial:
https://docs.tvm.ai/tutorials/frontend/from_pytorch.html

Can anyone confirm?

@dwofk
Copy link
Owner

dwofk commented Jul 30, 2020

Hi @oroelipas

You were correct in that you need to compile the model anew for a different hardware platform. As the models in this repository were compiled specifically for the TX2, they will not be compatible with the Raspberry Pi without re-compilation.

@ideasxiang
Copy link

ideasxiang commented Dec 3, 2020

@oroelipas were you able to recompile for raspberry pi?

@oroelipas
Copy link
Author

Hi @ideasxiang, currently I am working in other projects and have not made progress with this. Anyway I am listening if someone publish something about it

@ideasxiang
Copy link

ideasxiang commented Dec 4, 2020

@oroelipas thank you for your reply, I will try recompile using the link you provided. https://docs.tvm.ai/tutorials/frontend/from_pytorch.html

@microboym
Copy link

@ideasxiang Did you succeed to recompile the model for raspberry pi?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

4 participants