sparktorch
polyaxon
| sparktorch | polyaxon | |
|---|---|---|
| 1 | 9 | |
| 334 | 3,483 | |
| - | 0.4% | |
| 2.5 | 8.7 | |
| 12 months ago | 8 days ago | |
| Python | Python | |
| MIT License | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
sparktorch
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Spark2 + pytorch on GPU
Was reading the documentation of sparktorch (https://github.com/dmmiller612/sparktorch) which says you need spark >= 2.4.4. But to the best of my knowledge spark2 doesn't have gpu compute capabilities. Does that mean it can only use cpu compute? Am I missing something?
polyaxon
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Any MLOps platform you use?
If you're not concerned about self-hosting, WandB is one of the more fully featured training monitoring tools (I've used it in the past without any issues but the lack of data and training privacy and lack of self-hosting possibilities makes it a hard no for anything that isn't scholastic). Polyaxon is an alternative but rewriting all your variable logging to conform to their requirements makes it very difficult to switch to it in the middle of a project so you have to commit to it from the get-go.
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[D] Kubernetes for ML - how are y'all doing it?
We use Polyaxon and it’s pretty good
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[D] What MLOps platform do you use, and how helpful are they?
Disclosure - I'm the author of Polyaxon.
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Does anyone have experience with polyaxon?
I just came across https://github.com/polyaxon/polyaxon because mlflow gives me a hard time and costs my company money by the day because it is not working as expected.
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[D] Productionalizing machine learning pipelines for small teams
For running experiments, http://polyaxon.com/ is a really good free open-source package that has lots of nice integrations so you can quickly run experiments in k8s but it might be overkill in some cases.
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Top 5 tools to get started with MLOps !
Polyaxon : https://polyaxon.com
- Open source alternative to AWS Sagemaker, Google AI Platform, and Azure ML
What are some alternatives?
pytorch-lightning - Build high-performance AI models with PyTorch Lightning (organized PyTorch). Deploy models with Lightning Apps (organized Python to build end-to-end ML systems). [Moved to: https://github.com/Lightning-AI/lightning]
MLflow - Open source platform for the machine learning lifecycle
fastT5 - ⚡ boost inference speed of T5 models by 5x & reduce the model size by 3x.
kubeflow - Machine Learning Toolkit for Kubernetes
torch2trt - An easy to use PyTorch to TensorRT converter
flyte - Scalable and flexible workflow orchestration platform that seamlessly unifies data, ML and analytics stacks.
BERT-NER - Pytorch-Named-Entity-Recognition-with-BERT
dvc - 🦉 ML Experiments and Data Management with Git
openfl - An open framework for Federated Learning.
onepanel - The open source, end-to-end computer vision platform. Label, build, train, tune, deploy and automate in a unified platform that runs on any cloud and on-premises.
pytorch-lightning - Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
mmlspark - Simple and Distributed Machine Learning [Moved to: https://github.com/microsoft/SynapseML]