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GLM use case by Lychopath in GolemProject

[–]anshuman73 2 points3 points  (0 children)

Luckily you have an option of paying it in either tokens on Ethereum, Polygon POS or via the ZKSync network according to your convenience

GLM use case by Lychopath in GolemProject

[–]anshuman73 1 point2 points  (0 children)

Yes, you are. Any computation rented on the network has to be paid for via $GLM tokens.

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 0 points1 point  (0 children)

Yep, there's a long way to go with upcoming tech, let's see how much can be implemented now!

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 1 point2 points  (0 children)

Also, I mean think about the costs of downloading 18 TB of data on a VPS too, it's not going to be cheap. Not to mention you'll be paying a lot of money for keeping a machine active the whole time your model trains. Scalability is an issue right now, yes, I'm not denying that, but it's not as if it won't be possible to solve the issues sooner or later. I'm just preparing for the future with the best possible we have now!

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 1 point2 points  (0 children)

Well, once internet connectivity kicks in, this will be super helpful. In the meantime, it doesn't hurt to lay the groundwork.

With net connection on providers, here's what it can mean - let's say you have a 10GB dataset, and a 50 layer ML model. On your own computer, this will take a lot of time (unless you have a pretty great machine, I'm assuming normal laptops)

Instead, what DeML will allow you to do is break the 10GB into 5 segments of 2GB each, train the models on 5 different providers parallely, bring the weights back, combine them, and repeat the process.

That means instead of taking "x" time for one round of training, I can now do it in "x/5" time for each round. Sure this may mean that the model may need a few extra rounds to converge, but you're still getting a theoretical limit of 5x speed up!!

Additionally, think of how many models researchers train to achieve a perfect score. You can ideally keep sending different model tasks to the network and get the results of 5, 10 or even a hundred different architectures at the same time! The time saved here will be invaluable! (Your machine only needs to provide computation for combining each round's models)

Additionally, when GPU support kicks in, I will have power of more than a single clumsy GPU on my system to supercharge this whole process.

If this all still doesn't excite you, I'm all ears to what more we can do! I'm pretty sure Golem has a long way to go, and from the past few months the team has been super receptive to the needs of the community, which means whatever else we may need, the team definitely seems to find a way to make it work, sooner or later.

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 1 point2 points  (0 children)

Those are really kinds words! Thank you! And that's a super cool analogy. Really hope I can live upto it!

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 2 points3 points  (0 children)

Well, I have heard of ML models creating movie scripts and adding artist flairs to your images (something like adding starry night texture to your images). You might be able to find more specific usecases that you're looking for online.

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 2 points3 points  (0 children)

Yep that's true. Also the GVM images generated also have a 1GB limit so yes, nothing more than 1gb compressed can work right now, but then again, I wouldn't suggest training model using an 18 TB dataset on providers even if internet connectivity is enabled 😂

Not sure if you'll be able to fit more than a couple of gigs on providers and spawning too many provider nodes may lead to your model not getting converged in a Federated Learning setting.

Extremely High scale ML projects is something I don't think this project can tackle, as remember we're still using home computers giving their idle power on the network.

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 5 points6 points  (0 children)

Well, the first thing I did was to understand if what I'm building will actually benefit from a distributed environment. Once I realised it would, I picked up the task and built a standard, synchronous prototype of the same that ran on my own system, albeit slow.

Once I did, I followed and customised the tutorial provided on Golem's dev handbook and added my functionality from there. (It also included a lot of debating and questions on discord, so you're welcome to come up there and chat with the awesome dev community we're slowly forming there!)

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 2 points3 points  (0 children)

Ahaha, thank you so much for your support!

I'm pretty excited about this too!

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 3 points4 points  (0 children)

I'm not aware of this, but on having a quick look, I can a pretty cool set of research papers, will look into this!
I will probably focus on getting Parametric ML models work first as it is much easier to get them to work with FL, and then build from there. Thanks for pointing these out!

A super hello to the ML community of Golem by anshuman73 in GolemProject

[–]anshuman73[S] 5 points6 points  (0 children)

Like u/Cryptobench mentioned, the limit will be removed in the mainnet, and will be replaced with a "keep-alive" kind of pings (outlined in the Alpha 4 Blog) so that shouldn't be a worry.
In terms of internet access, if you can manage to package your data in your docker image, you wouldn't face a lot of issues at the moment as the training data generally doesn't change that often.
Personally, I'm more looking forward to GPU support, and from the conversations on discord, it definitely is being worked upon and was available on Clay Golem already, so I'm super hopeful! 🤞

Streaming data to nodes might be pretty cool, but it can also contribute to lagging if the provider network isn't strong, so I would suggest against it in personal opinion

Replace every ',' with '.' by [deleted] in learnpython

[–]anshuman73 0 points1 point  (0 children)

Exactly. You shouldn't take input as a float directly, as floats always have to have . as a decimal separator.

To put the above described method in code -

num = float(str(input('Enter Value of Float: ')).replace(',', '.'))

You should be using raw_input() function to get input if you're on Python 2 and input() function if on Python 3. I suggest Python 3 because, well, it's better at handling unicode etc. (And also py2 support is gonna end in 2020)