runhouse
Ray
runhouse | Ray | |
---|---|---|
6 | 43 | |
721 | 31,322 | |
3.7% | 2.3% | |
9.8 | 10.0 | |
3 days ago | 2 days ago | |
Python | Python | |
Apache License 2.0 | Apache License 2.0 |
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runhouse
- Runhouse
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Better GPU Cluster Scheduling with Runhouse
With Runhouse, it’s easy to send code to your compute no matter where it lives, and efficiently utilize your resources across multiple callers scheduling jobs (e.g. researchers, pipelines, inference services, etc). We believe less is more when it comes to AI DevOps, so we don’t make any assumptions about the structure of your code or the infrastructure to which you’re sending it.
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The Great MLOps Hoax: Is It Just Data Engineering in Disguise?
You may want to look at run.house [0] for a pretty powerful solution to many of these problems.
[0] https://github.com/run-house/runhouse
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Who uses Apache Airflow for MLOps? Enlighten me.
I was the product lead for PyTorch and was seeing the same problem all over, so I've been working on a new tool for exactly this: https://github.com/run-house/runhouse
- Run-house/runhouse: Programmable remote compute and data across environments
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How easy is it to migrate from one MLOps tool to another? And what SaaS platform would you recommend?
I've been working on a very flexible and low-lift OSS ML platform that sounds like it would suit your needs: https://github.com/run-house/runhouse
Ray
- Ray: Unified framework for scaling AI and Python applications
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Open Source Advent Fun Wraps Up!
22. Ray | Github | tutorial
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Fine-Tuning Llama-2: A Comprehensive Case Study for Tailoring Custom Models
Training times for GSM8k are mentioned here: https://github.com/ray-project/ray/tree/master/doc/source/te...
- Ray – an open source project for scaling AI workloads
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Methods to keep agents inside grid world.
Here's a reference from RLlib that points to docs and an example, and here's one from one of my projects that includes all my own implementations
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TransformerXL + PPO Baseline + MemoryGym
RLlib
- Is dynamic action masking possible in Rllib?
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AWS re:Invent 2022 Recap | Data & Analytics services
⦿ AWS Glue Data Quality - Automatic data quality rule recommendations based on your data AWS Glue for Ray - Data integration with Ray (ray.io), a popular new open-source compute framework that helps you scale Python workloads
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Think about it for a second
https://ray.io (just dropping the link)
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Elixir Livebook now as a desktop app
I've wondered whether it's easier to add data analyst stuff to Elixir that Python seems to have, or add features to Python that Erlang (and by extension Elixir) provides out of the box.
By what I can see, if you want multiprocessing on Python in an easier way (let's say running async), you have to use something like ray core[0], then if you want multiple machines you need redis(?). Elixir/Erlang supports this out of the box.
Explorer[1] is an interesting approach, where it uses Rust via Rustler (Elixir library to call Rust code) and uses Polars as its dataframe library. I think Rustler needs to be reworked for this usecase, as it can be slow to return data. I made initial improvements which drastically improves encoding (https://github.com/elixir-nx/explorer/pull/282 and https://github.com/elixir-nx/explorer/pull/286, tldr 20+ seconds down to 3).
[0] https://github.com/ray-project/ray
What are some alternatives?
omegaml - MLOps simplified. From ML Pipeline ⇨ Data Product without the hassle
optuna - A hyperparameter optimization framework
aim - Aim 💫 — An easy-to-use & supercharged open-source experiment tracker.
stable-baselines3 - PyTorch version of Stable Baselines, reliable implementations of reinforcement learning algorithms.
Faust - Python Stream Processing
gevent - Coroutine-based concurrency library for Python
stable-baselines - A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
SCOOP (Scalable COncurrent Operations in Python) - SCOOP (Scalable COncurrent Operations in Python)
Thespian Actor Library - Python Actor concurrency library
Dask - Parallel computing with task scheduling
django-celery - Old Celery integration project for Django
pymarl - Python Multi-Agent Reinforcement Learning framework