TorchPQ
Approximate nearest neighbor search with product quantization on GPU in pytorch and cuda (by DeMoriarty)
deepmind-research
This repository contains implementations and illustrative code to accompany DeepMind publications (by google-deepmind)
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TorchPQ | deepmind-research | |
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3 | 29 | |
202 | 12,783 | |
- | 2.0% | |
3.5 | 1.5 | |
5 months ago | 9 days ago | |
Cuda | Jupyter Notebook | |
MIT License | Apache License 2.0 |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
TorchPQ
Posts with mentions or reviews of TorchPQ.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-01-15.
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[D] Is there an open-source implementation of the Retrieval-Enhanced Transformer (RETRO)?
if you're decided to run nearest neighbor search on GPU, you might wanna give TorchPQTorchPQ a try
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[P] TorchPQ: Efficient Nearest Neighbor Search and Clustering on GPUs
TorchPQ is a python library for approximate nearest neighbor search on GPUs. It has efficient implementations of IVFPQ algorithm as well as some of its variants (e.g IVFPQ+R). The project is written mostly in python using pytorch library, with some custom CUDA kernels to accelerate clustering, searching and indexing.
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Are there more practical tools for KNN searches and storing documents/embeddings?
If you're using GPU for search, You can give TorchPQ a try, it's an ANN search library implemented with PyTorch and CUDA. with TorchPQ, you can freely add / remove vectors with IDs, you can save/load them just like a regular PyTorch model. TorchPQ is still in development, and I'd love to hear any suggestion or feedback.
deepmind-research
Posts with mentions or reviews of deepmind-research.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-02-03.
- This A.I. Subculture's Motto: Go, Go, Go. The eccentric pro-tech movement known as "Effective Accelerationism" wants to unshackle powerful A.I., and party along the way.
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How worried are you about AI taking over music?
Deepmind 63
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Are there Notebooks of AlphaFold 1?
Found some here and here.
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Trying to port this non-standard Tensorflow model to Pytorch and not sure if I'm missing anything
I am trying to make a physics-simulation model based on DeepMind's research, with its source code found here https://github.com/deepmind/deepmind-research/tree/master/learning_to_simulate . The thing that mainly confuses me is how to properly implement the embedding situation found at https://github.com/deepmind/deepmind-research/blob/master/learning_to_simulate/learned_simulator.py on lines 78 and 152.
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[D] Is it possible to use machine learning to create 3D images for the purpose of 3D printing?
Yes. There's a fair bit of research into using ML to generate 3D models. Early work, like Neural Radiance Fields (NeRF) generated a voxel model, which could be used for 3D printing, but it would be low resolution, like blowing up a tiny image vs an SVG vector file. However, more recent research can generate polygonal models from a video taken of a real object. Polygonal models are much better for 3D printing.
- DeepMind Research – code to accompany DeepMind publications
- Skilful precipitation nowcasting using deep generative models of radar - Dr. Piotr Mirowski - Zoom
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[R] Skilful precipitation nowcasting using deep generative models of radar - Link to a free online lecture by the author in comments (deepmind research published in nature)
Skilful precipitation nowcasting using deep generative models of radar https://www.nature.com/articles/s41586-021-03854-z https://deepmind.com/blog/article/nowcasting https://github.com/deepmind/deepmind-research/tree/master/nowcasting
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Deepmind Open-Sources DM21: A Deep Learning Model For Quantum Chemistry
Github: https://github.com/deepmind/deepmind-research/tree/master/density_functional_approximation_dm21
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[P] Choosing a self-supervised learning framework that's easy to use
BYOL - again, it seems that it's not optimized for running on multiple GPUs.
What are some alternatives?
When comparing TorchPQ and deepmind-research you can also consider the following projects:
faiss - A library for efficient similarity search and clustering of dense vectors.
jaxline
RETRO-pytorch - Implementation of RETRO, Deepmind's Retrieval based Attention net, in Pytorch
dm-haiku - JAX-based neural network library
nmslib - Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.
Scalix - Scalix is a data parallel compute library that automatically scales to the available compute resources.
flax - Flax is a neural network library for JAX that is designed for flexibility.