Intel® Distribution of OpenVINO™ Toolkit
Community assistance about the Intel® Distribution of OpenVINO™ toolkit, OpenCV, and all aspects of computer vision-related on Intel® platforms.

Compile BiseNetv2 model for NPU

Maick
Beginner
987 Views

Hello,

 

I try to use the benchmark_app on a BiseNetv2 model and on NPU device, but the compilation process never ends.

 

If I choose CPU or NPU every think works fine. I also try with a mobilenet model and it works for all devices.

 

It seems related to this model on this device...

 

How could I get more information why the compilation failed ?

 

Here are my configuration: 

System : Intel Core Ultra7 155H

Operating System : Windows 11 (I also try on Ubuntu 22.04)

OpenVino 2024.5.0

NPU driver : 2024.5.0

 

Thanks for your answer.

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16 Replies
Aznie_Intel
Moderator
896 Views

Hi Maick,

 

Thanks for reaching out. Can you reconfirm again which plugin is working fine with the BiseNetv2 model? For further checking, you may share the model files (.xml and .bin).

 

 

Regards,

Aznie


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Maick
Beginner
876 Views

Hi Azine,

 

Thanks for your answer.

 

Sorry for the typo, it works fine with CPU and GPU.

 

I attached the .xml and .bin of the model.

 

Regards,

 

Maïck

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Aznie_Intel
Moderator
790 Views

Hi Maick,

 

Thanks for the model files. We are checking this with the engineering team and will get back to you once the information is available.

 

 

Regards,

Aznie


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Witold_Intel
Employee
738 Views

Hi, Maick,


Could you please share your NPU driver version with us? OpenVINO developers have reproduced the case without any compilation or inference problems, neither for fp16 nor for quantized (fp16-int8) model version. So our recommendation would be to upgrade to the latest available driver version ( https://github.com/intel/linux-npu-driver/releases/tag/v1.10.0 ). By the way, is your setup MTL or LNL?


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Maick
Beginner
731 Views
Hi,
 
Thanks for your answer !
 
Here is what I just tried : 
I still have the same behavior,  the script is blocked on step 7, it cannot build the model.
 
I don't understand what you mean by MTL or LNL ?
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Witold_Intel
Employee
664 Views

Thank you for your feedback. MTL is short for Meteor Lake and LNL for Lunar Lake chip family.


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Witold_Intel
Employee
640 Views

Please bear with us. I relayed your results to the developers but there has been no response yet.


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Witold_Intel
Employee
508 Views

Thank you for your patience. I haven't received any follow-up from the developers yet. I will try to obtain more information before our next planned meeting on January 15th.


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Witold_Intel
Employee
451 Views

I don't have any response from the developers yet. I will try to contact them directly.


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Witold_Intel
Employee
376 Views

As of now, developer response is still pending. Please bear with us.


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Witold_Intel
Employee
252 Views

Hello, thank you for your patience. There's a new developer looking at your issue. Just a small follow-up question - are NPU driver versions identical in your Windows and Ubuntu instances?


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Maick
Beginner
222 Views

Hello,

 

Thanks for your feedback, yes I try with 2024.5 on Ubuntu and Windows.

 

Best regards,

 

Maïck

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Witold_Intel
Employee
207 Views

Thank you very much for your response, I will relay this to the developer.


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Witold_Intel
Employee
139 Views

Hi Maick,


Thank you for your patience. I don't have a response from the developers yet but i will highlight your issue during our sync meeting on Wednesday. Hopefully, I will be able to provide more assistance by then.


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Witold_Intel
Employee
68 Views

Hi Maick,


in a meeting with developers I learnt that your OpenVINO version is a bit special. 2024.5 requires NPU driver 32.0.100.3052/3053 on Windows but doesn't have a Linux equivalent driver. One option would be to upgrade to OpenVINO 2024.6 or 2025.0 (compatible with 1.10.1 Linux driver). Another one to downgrade to 2024.4 (Linux driver 1.8). Would one of those solve your issue?


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Maick
Beginner
10 Views

Hi,

 

I try with OpenVIno 2024.6 and 1.10.1 linux driver but the issue is still the same.

 

I also try with the same model but with a smaller input shape and it works fine. Maybe it could be helpful for you.

 

Best regards,

 

Maïck

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