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Xla Alternatives
Similar projects and alternatives to xla
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InvokeAI
InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
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pytorch-lightning
Discontinued 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] (by PyTorchLightning)
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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determined
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
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ignite
High-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently. (by pytorch)
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snowboy
Future versions with model training module will be maintained through a forked version here: https://github.com/seasalt-ai/snowboy
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gloo
Collective communications library with various primitives for multi-machine training. (by facebookincubator)
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pytorch-lightning
Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.
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Spoken-Keyword-Spotting
In this repository, we explore using a hybrid system consisting of a Convolutional Neural Network and a Support Vector Machine for Keyword Spotting task.
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NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better xla alternative or higher similarity.
xla reviews and mentions
Posts with mentions or reviews of xla.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2024-01-26.
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Who uses Google TPUs for inference in production?
> The PyTorch/XLA Team at Google
Meanwhile you have an issue from 5 years ago with 0 support
https://github.com/pytorch/xla/issues/202
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Google TPU v5p beats Nvidia H100
PyTorch has had an XLA backend for years. I don't know how performant it is though. https://pytorch.org/xla
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Why Did Google Brain Exist?
It's curtains for XLA, to be precise. And PyTorch officially supports XLA backend nowadays too ([1]), which kind of makes JAX and PyTorch standing on the same foundation.
1. https://github.com/pytorch/xla
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Accelerating AI inference?
Pytorch supports other kinds of accelerators (e.g. FPGA, and https://github.com/pytorch/glow), but unless you want to become a ML systems engineer and have money and time to throw away, or a business case to fund it, it is not worth it. In general, both pytorch and tensorflow have hardware abstractions that will compile down to device code. (XLA, https://github.com/pytorch/xla, https://github.com/pytorch/glow). TPUs and GPUs have very different strengths; so getting top performance requires a lot of manual optimizations. Considering the the cost of training LLM, it is time well spent.
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[D] Colab TPU low performance
While apparently TPUs can theoretically achieve great speedups, getting to the point where they beat a single GPU requires a lot of fiddling around and debugging. A specific setup is required to make it work properly. E.g., here it says that to exploit TPUs you might need a better CPU to keep the TPU busy, than the one in colab. The tutorials I looked at oversimplified the whole matter, the same goes for pytorch-lightning which implies switching to TPU is as easy as changing a single parameter. Furthermore, none of the tutorials I saw (even after specifically searching for that) went into detail about why and how to set up a GCS bucket for data loading.
- How to train large deep learning models as a startup
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Distributed Training Made Easy with PyTorch-Ignite
XLA on TPUs via pytorch/xla.
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[P] PyTorch for TensorFlow Users - A Minimal Diff
I don't know of any such trick except for using TensorFlow. In fact, I benchmarked PyTorch XLA vs TensorFlow and found that the former's performance was quite abysmal: PyTorch XLA is very slow on Google Colab. The developers' explanation, as I understood it, was that TF was using features not available to the PyTorch XLA developers and that they therefore could not compete on performance. The situation may be different today, I don't know really.
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www.saashub.com | 26 Apr 2024
Stats
Basic xla repo stats
8
2,291
9.9
1 day ago
pytorch/xla is an open source project licensed under GNU General Public License v3.0 or later which is an OSI approved license.
The primary programming language of xla is C++.
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