Tensorflow causing restart loop?

Configuration
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For what little it’s worth, I’m seeing exactly the same thing.

I’m running the Docker container for HomeAssistant 0.91.3, and I also followed the previously linked script.

If I have my image_processing config block in, the container just constantly boot loops. The docker logs don’t show anything that jumps out as obviously related.

I’ve tried using different cameras (switching between ffmpeg and mjpeg), different Tensorflow model and I’ve recompiled the models with protoc twice just to be sure. Without fail, I get a boot loop until I remove the image_processing block.

My host machine has AMD Turion II which I thought supported AVX but I’ll try compiling Tensorflow myself too.

I know there is not much new info in this post but just wanted @xrapidx to know you’re not alone!

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@Insanitum @xrapidx Im having this exact issue, did you ever figure it out? Its driving me nuts!!

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@mkono87 Sadly not yet- I tried a few times but kept having different issues with missing libraries and multiple compilation failures. I’ve shelved it for now as it was just taking so much time and I already had doubts that my CPU would be able to handle it. I’ve spent so long on it that I’m contemplating moving to a NUC just to get around this issue!

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Pretty much the same status as @Insanitum - spent quite a bit of time trying different methods, but none seem to work for different reasons.

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@xrapidx @Insanitum I figured it out late last night. As im using proxmox and I had to set my vm to cpu type:host from its default kvm64. That allowed the vm to see all cpu instructions. What cpu are you guys using?

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Running on a HP Gen8 microserver: Intel® Celeron® CPU G1610T @ 2.30GHz

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@mkono87 Congrats, glad to hear you have it working!

I’m using Docker on top of Ubuntu, running on an AMD Turion II. The Turion doesn’t have AVX, so I need to compile TensorFlow without the AVX instructions, but that’s proven to be easier said than done.

I’ve seen some discussion about how big the HomeAssistant docker image is getting and TensorFlow was mentioned as a candidate to break out into a separate container; I’d hoped to be able to contribute that but even getting TF compiling is proving tough. That way, we’d all be able to precompile different flavours of TensorFlow and make it easier to just pull and link to one that fits your hardware.

As I’ve struggled with it so much, and I was already skeptical that my CPU would have enough power run TF anyway, I think I may personally end up saving up for a NUC with an i5 CPU to give me both AVX and a bit more compute power.

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I bought a Dell optiplex 9100 with an i5-3570 in it. Was suppose to be just for Blue Iris but I threw Home Assistant on there and works great. I could use more ram but so far so good. Having multiple options of dockers would be fantastic.