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More on my cheap GPU experience.

I got a Tesla K40m. This card is meant to be used in workstations and datacenters. It doesn't have a fan. Instead, it has a massive heat sink. It's assumed that there is enough airflow to keep the thing cool.

A training step on a CPU in a intel/intel-optimized-tensorflow-avx512 container takes 138 ms.

It is slower than my old GPU, but it might be fast enough to get the first version of a model.

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A training step takes 38 ms on an Nvidia K40 which I got for $100.

On Google's Colab, a training step takes 21ms. (I don't remember what GPU I've used).

Colab is not expensive, but it is annoying to do long training runs as a connection is likely to drop.

I'm willing to compromise speed in favor of ease of development and early testing on a local machine.

If needed, the final model can always be trained in the cloud on a beefy GPU.

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The conda environment.yml that I used to build the environment is here gist.github.com/dimazest/40571

LD_LIBRARRY_PATH might be needed to be redefined, I used this command to fire up a notebook

LD_LIBRARY_PATH="$CONDA_PREFIX/lib":$LD_LIBRARY_PATH jupyter-notebook

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so i gave up on conda and install what i need with pip...

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I've spent to much time trying to install Tensorflow with the packages I want in a conda env. For some reason, conda-forge has tensorflow-hub, but doesn't have tensorflow-text. I need both to run a model.

What's the most user-friendly way to get tensorflow up and running?

Dima boosted

@dima you can block certain keywords like "RT", "Retweet", "Twitter" and "Birdsite" to filter out at least some content.

I wish it was possible to filter out Twitter content

to be fair, ai-benchmark assigned the score of 5330 to the GPU and 1397 to the CPU.

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I got an old, but cheap nvidia gpu (k40) to play with deep learning while i'm searching for a reasonably priced modern card.

To my surprise, the i7-1165G7 CPU (8 cores) is about twice faster than the GPU doing classification of images with a CNN.

Is it something one would expect. Did CPU's get better recently? Is the GPU I got too slow?

it works! Now when I connect any of my laptops, the keyboard and the mouse just work

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It looks like it's possible to pair Bluetooth devices to a dongle that is shared between several OSs. wiki.archlinux.org/title/bluet mentions dual boot, but I'll try to use this trick so that I cold connect a keyboard and a mouse to a laptop that is currently connected to my USB hub.

My frame.work was delivered this morning! It's an absolutely gorgeous piece of hardware. Setting it up was nothing but pleasure.

Today I spend quite some time putting together an new Ikea desk frame with motors and a desk top I had.

It's a combination of 2 models. I had to drill some holes to put them together. I like the end result.

Dima boosted

Python dev 

In recent years I've got a lot of mileage out of Python, but the packaging, building, distribution story is one that has been in constant flux since I've been developing with it. I never feel like I'm doing it right, and the blog post below confirms I have a boatload of code that is apparently doing it wrong. This shifting packaging story is a constant source of friction in this particular ecosystem, one that makes me wish I hadn't started down the Python path.

blog.ganssle.io/articles/2021/

Dima boosted

It saddens me somewhat that nearly every database interface library for the last decade or two has huge warnings not to string-interpolate data into your queries right at the top of the documentation and yet SQL injection vulnerabilities still keep cropping up all over the place

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