Aim: Record, search and compare ML training runs

by polm23 • 6 years ago

45 26 6 years ago

marcinzm• 6 years ago

Honestly, it's really hard for me to tell from the documentations if this is something that is self-hosted, is run locally or is a SaaS product. The phrase "open source" shows up nowhere I can see for example.

As best I can tell it's an open source version of comet or wandb that you run locally (or I guess host somewhere). Is that right?

ellisv• 6 years ago

From what I can glean from the docs, you run the UI locally which reads from experiments from `.aim/`

The experiments results could be populated by running the training job remotely and committing the `.aim/` directory afterwards.

It's kinda like a UI for DVC

jszymborski2• 6 years ago

yes, it looks like it's meant to be run in a similar way to Tensorboard

gevorg_s13• 6 years ago

Yea, spot on. Right now UI is ran locally and it reads the data from `.aim`. We have seen users deploy it for the team and have seen standalone in the local environment too. Once training is ran, the logs are saved in the `.aim`. We are using a format that is ~50% more memory efficient than the tb logs - and searchable (see the aimrecords repo).

gevorg_s13• 6 years ago

Hi, Aim is fully open source and self-hosted (at the moment - just like tensorboard). Open source version of wandb would be one way to put it.

But we are building a new way of interacting with the ML training runs that lets the researchers compare lots of them (1000s) in really short period of time while having full access to the context of the experiments. This is a super early version. And lots more work needs to be done.

We have implemented a pythonic search to search through the experiments that is easy to use. Hopefully this sheds more light to the work we are doing.

frakt0x90• 6 years ago

I've seen a lot these projects recently. I have used MLFlow for a while and enjoyed it. How does this compare?

jszymborski2• 6 years ago

or how either compares with Tensorboard and its HPARAMS tab? (PSA: PyTorch Lightning makes it even easier to use).

gevorg_s13• 6 years ago

Pls see my answers above.

gevorg_s13• 6 years ago

the big diff and the advantage is that on tb you can't group by hyperparams or easily divide into subplots while having all the research info in fro nt of you.

Aim does that and also aggregates groups of runs to reduce the dimension and make it easy to compare. It has a proper search by hyperparsams (and everything else tracked/collected really). All in one panel where you can compare 100s of experiments at a time.

Loading many runs on TB, with very long names makes it super slow to analyze the runs really. Tbh that has been a motivation for building this open source tool - to have something efficient and beautiful :)

williamsmj2• 6 years ago

Yes, I was looking for the comparison to local MLFlow and Tensorboard (and Losswise, and Weights & Biases, and all the remote options in this ecosystem). It looks nice, but without that, it's difficult to know whether it's worth spending more time looking into it.

gevorg_s13• 6 years ago

We are working on a new paradigm on interacting with Ml training runs. A lot of the effort is now focused on very efficient experiment comparison capabilities - talking about 1000s of them. Lots of challenges on the UI and the backend. When loading TB or any other tool really with lots of experiments it's super slow and becomes useless. Also no way to do effective comparison of runs by hyperparams or other metadata on the tensorboard or MLFlow. Quite basic capabilities.

ashotarzumanyan• 6 years ago

Can't agree more. A comparison with others (some sort of table or a blog post) would help a lot.

gevorg_s13• 6 years ago

We are building Aim as a new paradigm for interacting with and organizing the ML training runs. And the project is really just a few months old.

It's focused on comparing 1000s of experiments really effectively in minutes. MLFlow, Tensorboard don't have these capabilities which has motivated us to work on Aim. Especially valuable when running hyperparam sensitive tasks such as RL.

davidbuniat• 6 years ago

Oh nice, it's like open-source version of W&B, and seems much better than Tensorboard. How many experiments I can compare at the same time without crashing chrome? :)

gevorg_s13• 6 years ago

Aim easily handles 100s of ML training runs. There are folks who have 1000s of experiments too. We haven't oficially benchmarked it yet though.

gevorg_s13• 6 years ago

Hi all I am one of the co-authors to this project, and will try to answer all the Qs here. Was just forwarded this link - one of the community members must have posted it.

pchal• 6 years ago

Interesting effort. Does it snapshot the state of source code at the time an experiment is run? Does it do it without requiring a git commit? I believe the Replicate experiment tracking tool does this.

gevorg_s13• 6 years ago

We have got similar requests couple of times and its in the pipeline. Currently focused on the comparison of 1000s of metrics/training runs. It's a serious challenge both on the Ui and on the storage end.

Inviting you to the Aim [slack channel](https://slack.aimstack.io/). We would love to learn more about such use cases and why they are important.

karankanwar• 6 years ago

This is great stuff :))

mari_lee__• 6 years ago

Awesome! Will look forward to the project's further development.

gevorg_s13• 6 years ago

Thanks :)

lusinem• 6 years ago

Wow! Amazing project!

Aim: Record, search and compare ML training runs

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