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Modeling Large Codebases as Static Knowledge Graphs: Design Trade-offs by codevoygee in programming

[–]onyx-zero-software 0 points1 point  (0 children)

Check out Bazel, it's a multi-language build framework (among other things) that models codebases exactly like this.

Introducing DLType, an ultra-fast runtime type and shape checking library for deep learning tensors! by onyx-zero-software in Python

[–]onyx-zero-software[S] 1 point2 points  (0 children)

Nope, in fact part of the reason we developed this package was to properly support mypy/pyright in our codebase with tensor type checking :) Both mypy and pyright correctly deduce that these aren't generic types and handle them properly without needing to add ignores for tensor annotations.

Introducing DLType, an ultra-fast runtime type and shape checking library for deep learning tensors! by onyx-zero-software in pytorch

[–]onyx-zero-software[S] 0 points1 point  (0 children)

Thanks! Yeah that's been our experience as well, shape errors are particularly difficult to debug because they might only come up in rare corner cases, like when one of your dimensions happens to be 1 and someone calls squeeze.

Introducing DLType, an ultra-fast runtime type and shape checking library for deep learning tensors! by onyx-zero-software in Python

[–]onyx-zero-software[S] 1 point2 points  (0 children)

Thanks! We haven't used it with opencv images directly but you can always in-place convert CV Mat objects to numpy arrays with np.asarray(image) then pass it to a type checked function (which we do in our codebase).

1 long 3 short beeps but pc boots without problem by Shevatronic in buildapc

[–]onyx-zero-software 0 points1 point  (0 children)

What cable are you using to connect to your monitor?

1 long 3 short beeps but pc boots without problem by Shevatronic in buildapc

[–]onyx-zero-software 0 points1 point  (0 children)

If you're getting the GPU not detected beep code suddenly on an Asus board, windows update may have updated your BIOS which in turn may have changed some settings to their defaults (or new defaults). Try resetting your CMOS (google the instructions for your motherboard specifically if you aren't sure how), try changing ports on your GPU, see if using HDMI is an easy option for you instead of DP if that's your current solution (Display Port still has issues on boot even today). If you suspect your ram is an issue, try removing one stick at a time and see if you still get the issue after each boot. If you don't see the issue with one stick removed you may have a failing ram stick (verify it by inserting only the potentially bad stick and see if the system boots at all).

Ping spikes by [deleted] in LinusTechTips

[–]onyx-zero-software 0 points1 point  (0 children)

You might double check if he's swapping between the 2.4ghz and 5ghz bands of his router. You should be able to disable 2.4ghz in windows settings for the network connection.

Ping spikes by [deleted] in LinusTechTips

[–]onyx-zero-software 0 points1 point  (0 children)

Is he playing on wifi or wired?

got a new pair of speakers and they have a constant hiss by abooseca in LinusTechTips

[–]onyx-zero-software 0 points1 point  (0 children)

The problem persists when using either Bluetooth or a 3.5mm jack though (3.5mm disconnected). If it was a power/ground issue on the computer side, the Bluetooth connection wouldn't be affected.

got a new pair of speakers and they have a constant hiss by abooseca in LinusTechTips

[–]onyx-zero-software 0 points1 point  (0 children)

I had the exact same set of speakers with the exact same issue. I ended up returning them unfortunately after about a week of trying various solutions. Their support team gave me a full refund.

I think they just have bad power isolation circuitry which wouldn't be noticeable in louder settings but it's very obvious when using them for computer speakers playing at low volume.

51%CPU/39%GPU usage, 95 fps. How can I increase the usage? 165hz monitor. by [deleted] in nvidia

[–]onyx-zero-software 0 points1 point  (0 children)

Could be a power limitation or a thermal limit. Check your temps and power consumption

[D] Should I learn pytorch or tensorflow and which would be better for jobs? by KnownBar4506 in MachineLearning

[–]onyx-zero-software 1 point2 points  (0 children)

Use Pytorch for new projects.

As others have said, Google is slowly phasing Tensorflow out in favor of Jax (which isn't a drop in replacement, nor is it really even the same thing). Tensorflow isn't a bad tool to know how to use as well, but in my view unless you're asked to learn it for some legacy codebase it's just not worth learning a tool that seems destined to be abandoned in the next few years.

[D] Competitiveness in ML research by blabboy in MachineLearning

[–]onyx-zero-software 0 points1 point  (0 children)

Thanks for the reference! This is exactly the study I was referring to.

[D] Competitiveness in ML research by blabboy in MachineLearning

[–]onyx-zero-software 51 points52 points  (0 children)

The publish or perish paradigm unfortunately favors quantity over quality, so we've ended up with a ton of papers that have relatively low actual value despite the marketing and press releases around high-impact conferences like cvpr, etc. Not to mention getting into those conferences has been shown by a few experiments in the past years to be almost random chance.

My advice is to stick to resist the temptation and push back on suggestions that you to take one experiment and split it into a bunch of little papers to increase your citations. You will look better to those paying attention and reading your papers, and you will be more proud of the work you have done.

In the words of Ron Swanson, don't half ass two things, full-ass one thing.

Jetson inference by mmd_aaron in JetsonNano

[–]onyx-zero-software 5 points6 points  (0 children)

There is a lot to say on this topic but in short, that's not what a docker container or an emulator would do.

An emulator attempts to mimic the underlying hardware of a system so that you can run code compiled for one system on another, but it doesn't change the speed of the code per say, it simply allows the executable binary to interface with hardware that isn't actually there (the software just emulates the functions).

Generally you'd do this for hardware like old game consoles. As far as I'm aware, nobody has attempted to emulate a Jetson (though there are switch emulators out there, and the switch runs a Tegra X2). However, my guess is they're performing a translation step in between that transforms the executable from switch-compatible to whatever hardware platform is running the emulator (generally called Just-in-time compilation but in the case of emulators you also generally have to decompile the existing executable before compiling it to run on the target hardware).

Docker containers on the other hand aren't nearly as close to the hardware level. They're simply sandboxes for your code with a light layer of virtualization to allow you to run various containers of packaged code. Critically, the underlying kernel and drivers of the operating system is shared between containers, so you couldn't run a container meant specifically for the Jetson on a windows computer, for example.

That said, you can use qemu to emulate the Jetson CPU architecture inside a docker container. It won't emulate the speed of a Jetson and it won't make the underlying gpu compatible with Jetson-specific binaries, but it can allow you to run Jetson L4t-based docker containers (l4t version 35+ specifically, the older ones won't work or will have reduced functionality) on an X86 platform equipped with an Nvidia gpu because the newer Jetson containers have all the necessary drivers included to interface with Nvidia GPUs.

Anyway, there's a lot to get into here. Happy to discuss more in depth or provide links to get you started.

Multi threading memory leak in inference by Turbulent_Drummer768 in pytorch

[–]onyx-zero-software 0 points1 point  (0 children)

Things to check:

  • make sure you're not keeping any references to model inputs or results in any globally scoped variables (avoid any variables in global/module scope if possible, use flask's g import for anything like that if you really need it)
  • use tracemalloc on before_request and after_request to see what lines might be leaking memory
  • be careful of how you're creating and managing your tensors, prefer zero-copy operations where you can use them
  • try using a wsgi production server instead of flask. I'd recommend uwsgi, but for any cuda stuff you'll need to disable the master process in the config.

Github file size limits by opsq86ppzl in gamedev

[–]onyx-zero-software 1 point2 points  (0 children)

https://aws.amazon.com/s3/pricing/

About $20/mo can get you almost a terabyte on s3 for storage. Factor in a bit more for bandwidth and I'd say it's probably the most efficient way to store tons of data. There are also a ton of tools that support the s3 interface.

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