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Spark in me

Логотип телеграм канала @snakers4 — Spark in me S
Логотип телеграм канала @snakers4 — Spark in me
Адрес канала: @snakers4
Категории: Технологии
Язык: Русский
Количество подписчиков: 2.68K
Описание канала:

Lost like tears in rain. DS, ML, a bit of philosophy and math. No bs or ads.

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Последние сообщения 14

2021-12-20 10:10:37
Again - these are not mine, these are shitty PSUs
429 viewsAlexander, 07:10
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2021-12-20 10:09:14 Hilariously Stupid and Epic Bugs Part 3 - Exploding PSU

This is not bug per se, but some chain of events and my personal hilarious stupidity that lead to funny consequences.

The whole 3090 power issues mumbo jumbo. GPU and PSU manufacturers provide little (if any) proper (not marketing BS) guidance on actual fundamentals behind how you should connect your devices to a PSU.

3090 is known to consume from 300 to 540 W (sic). And typically it has only 2 8 pin power connectors (sometimes 3). If am not mistaken, the recommended load is about 150W for a single 8 PIN PCIE power connector. Also the PCIE port itself can deliver around 50 - 70W of energy. So if you GPU consumes around 300W, then nothing to worry about, provided you connect it WITH 2 PCIE POWER CABLES. There was a similar argument about 1080 Ti, but I believe people eventually settled that 1 cable was kind of ok. A10 on the other hand consumes ... exactly 150W, wow.

nvidia-smi --query-gpu=index,timestamp,power.draw,clocks.sm,clocks.mem,clocks.gr --format=csv -l 1

0, 2021/12/20 06:46:04.941, 275.42 W, 1830 MHz, 9501 MHz, 1830 MHz
0, 2021/12/20 06:46:05.959, 284.80 W, 1152 MHz, 9501 MHz, 1725 MHz
0, 2021/12/20 06:46:06.974, 287.45 W, 1845 MHz, 9501 MHz, 1845 MHz
0, 2021/12/20 06:46:07.987, 278.15 W, 1172 MHz, 9501 MHz, 1755 MHz

Also of importance are bullshit cooling settings done by some manufacturers (i.e. turbo fan does not spin faster than 50%), but let us leave this can of worms for now (I had no idea this was an issue - I was just lucky to buy proper GPUs, but just extra 20-30% of fan speed solves thermal issues, lol, you even do not need 100%, 3090 works under full load at ~70C).

So I went to a data center for regular maintenance of our servers (just visually check all connectors, blow the dust, this kind of stuff). A quick adventure, in and out, 20 minutes! What could go wrong?

When I arrived I realized that I forgot about the whole 8 + 8 thing. You see, I wanted to replace some 1080 Tis with 3090. So I needed more cables.

Tuned out, my cables were stored at my older flat where my relatives live. And they were ... mixed. There are nice pouches provided by Leadex, but my relatives were kind enough to take pouches out of the boxes. No problem, you can check them with a multi-meter.

After waiting for the pouches to be delivered ... I saw that visually cables from 2 pouches were identical and they forgot to put a multimeter. I heard stories about PSUs exploding if you mixed cables EVEN WITHIN the same model and year.

So, YOLO? And yes, the PSU exploded. Good thing the butcher's bill did not take anything else and I had a spare PSU for some reason (with precariously inviting 8 + 8 single PCIE connectors - a disaster waiting to happen). But it was as hilarious as nerve-racking.

By the way, Leadex, WTF? You put PCIE power cables with newer PSUs having 1 PCIE => 2 * 8 pin connectors! This is a disaster waiting to happen.

The conclusion:

- Label you fucking PSU boxes and pouches and store them under the bed;
- Take an extra layer of precautions all of the time;
- YOLO works only a handful of times;
- Backup your data. Even RAID 10 is not a backup;
- Modern high-end hardware is surprisingly robust and fault-tolerant;
- Rely on fundamentals;
- Have at least some power margin;
- Use better components;

Another funny situation on the same topic (not me). Turns out even if your cables start smoldering (in this particular case it was a shitty PSU), your PSU and GPU and MB may be just fine.

#epic_bug_moments
417 viewsAlexander, 07:09
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2021-12-19 10:19:16 Farcical Self-Delusion

As usual, I adore this series:

https://blog.piekniewski.info/2021/12/18/farcical-self-delusion/

My personal concern is that I started to see obviously sponsored content on Tesla's and Google's self-driving products in allegedly previously independent sci-fi channels on YouTube.

What bothers me, previously critical content creators suddenly list only vague dangers and fail to do their homework. I wonder why.

It is the most painful when people claiming to combat darkness join it.

#no_bs
370 viewsAlexander, edited  07:19
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2021-12-19 10:10:32 Hilariously Stupid and Epic Bugs Part 2

This is an anecdote from one of my previous jobs from the times when Keras vs PyTorch vs TF debate was still a thing.

Tldr - there was quite an arcane binary classifier. Also there was some intern claiming to have a 99%+ accuracy, while I had somewhere around 85%-90% accuracy.

I read his code multiple times (and it was in TF) and I was reluctant to run it and reassemble it, so basically I reimplemented everything in PyTorch.

One issue was glaring from the start - he was reading images for his pipeline sequentially, not randomly (do not remember if there were augmentations). And images on his disk were sorted by class, i.e. [..., class0, class0, class0, class1, class1, class1, ...].

The reason was truly hilarious - turns out the leak was in the batch normalization. The network somehow learned to pick up this data structure and the only 1% erroneous images were around the [..., class0, class1, ...] part.

Turns out some basic best practices are there for a reason, TF 1 sucked a lot then and the arcane nature of the classifier helped a lot.

That organization was broken on many more levels (and it backfired in future), but I am not sure I want to share the negative things that are not hilarious.

#epic_bug_moments
383 viewsAlexander, 07:10
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2021-12-19 09:52:20 Log libraries and the tendency to open holes in things

This is just epic - https://rachelbythebay.com/w/2021/12/18/log/

Cannot help sharing this. Typically such epic fails do not get shared in a modern two-faced world.

PS
Looks like she has a book worth of this stuff.

#no_bs
386 viewsAlexander, edited  06:52
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2021-12-17 23:00:07 Нечастая рубрика «Давайте обвалим Product Hunt»

Наверное вы все недавно видели этот треш (если вы не разбираетесь в ML, это был такой лубок, натянутый на потемкинскую деревню, рекламу которого проплатили и выдавали за достижение отечественного "Ай-Ай").

Что характерно, на Android приложение сначала таки набрало заветные 2 балла из 5 и словами "нативной" рекламы в телеге (которую уже стадливо потерли конечно, ахахаа) "настоящие патриоты русского дип лёрнинга и стартапинга" оценили усилия.

Почему пациенты поставили высокие отзывы на яблоке судить я не берусь (может там роль ботов играют сами юзеры), но говорят, что нельзя платить больше 1000 долларов каждый год за телефон и обладать критическим мышлением одновременно.

Короче, к чему это все. Мы недавно сделали охуенный VAD (детектор голоса). Возможно лучший в мире на данный момент. Да, сами сделали, очень много возились, сделали и выложили полезную вещь (а не очередной подписочный сервис от МЯСО), а не просто накопипастили из чужого репозитория и обмазали GPT-3 под освоение бабла инвестора под булшит бинго из MS Powerpoint.

И я подумал, может "настоящие патриоты русского дип лёрнинга" поддержат его. Ибо такая "простая" задача как детекция голоса претендует на "решенность" (и мне кажется мы сделали как минимум заявку на это), в отличие от всех остальных задач (типа синтеза или распознавания голоса), которые по сути бесконечны.

Еще я запостил его на Product Hunt (максимально фееричный из всех подобных популярных сайтов сайт) чисто для троллинга и сбора лулзов, может там будут какие-то срывы покровов, но вряд ли конечно.

Короче - "русский дип лернинг" бывает разный. И я просто так преисполнился от этого кейса, что не смог не написать этот пост.

Мой посыл такой - если вы не хотите принимать мрак, не принимайте.
287 viewsAlexander, edited  20:00
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2021-12-17 18:27:10 New V3 ONNX VAD Released

We finally were able to port a model to ONNX:

- Compact model (~100k params);
- Both PyTorch and ONNX models are not quantized;
- Same quality model as the latest best PyTorch release;
- Only 16kHz available now (ONNX has some issues with if-statements and / or tracing vs scripting) with cryptic errors;
- In our tests, on short audios (chunks) ONNX is 2-3x faster than PyTorch (this is mitigated with larger batches or long audios);
- Audio examples and non-core models moved out of the repo to save space;

https://github.com/snakers4/silero-vad
389 viewsAlexander, 15:27
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2021-12-17 10:01:10 Github Codespaces

I just found out that this exists - https://docs.github.com/en/codespaces.

On paper looks cool, if you have some mono-repo project based around code (mostly writing and packaging code) - you can just spin up what looks like basically a cloud based VSCode instance.

In retrospect, MS buying Github and integrating it with VSCode makes a lot of sense. All of this still has to be set up by a senior engineer, but the spinning up part may be done with one click.

The downside? It is a yet another subscription service you cannot control that has hourly billing (hours * people) in US$ for corporate accounts (and probably a lot of fine print and surcharge conditions for power users). I believe that for some (most likely frontend) light-weight projects it will be a blessing, especially for large corporations with a lot of personnel churn.

Also I suspect that if you have anything requiring remotely large builds and images, the prices would skyrocket (e.g. a base image of PyTorch weighs several gigabytes).

In a similar fashion some time ago I was interested in Github docker image repository (or how is it called), but saw the prices (and most likely they will be billing you repeatedly even for retagged docker images). I was appalled to see that a shit-ton of pricey enterprise solutions solving are just based on docker private repository ... and some bugs features have not been touched for years and are inherited into this bloatware ... which is just interfaces.

In any case - the rich get richer, nothing new, do not expect a free lunch. If something (like Colab) is really kind of free, then you just do not understand their business model (yet) or you are the product.
498 viewsAlexander, edited  07:01
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2021-12-17 09:46:55 A brief history of code search at GitHub

A nice history overview - https://github.blog/2021-12-15-a-brief-history-of-code-search-at-github/

Did not really understand anything about their new fully internal custom solution (probably I was not supposed to), but looks like that even for such an exotic case like code search ... ngrams still reign supreme.

Also an interesting remark - looks like only 2 companies have been able to deploy BERT / transformer based search on scale - Google and Microsoft.

I wonder why it has not trickled down to Github since MS bought it.
480 viewsAlexander, 06:46
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2021-12-16 06:12:31
Ice giant cooler?
Anonymous Poll
0%
I tried it (what is your experience?)
11%
I know about it but could not buy / expensive / not available
0%
I know about ... but why it exists?
89%
No idea what it is
9 voters50 viewsAlexander, 03:12
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