Vector Quantization - Pytorch A vector quantization library originally transcribed from Deepmind's tensorflow implementation, made conveniently into a package. It uses exponential moving averages to update the dictionary. VQ has been successfully used by Deepmind and OpenAI for high quality generation of...
如果'vector_quantize_pytorch'非标准库或已弃用,提供替代方案或建议: 如果vector_quantize_pytorch不是一个标准库,或者已经弃用,您可能需要寻找其他类似的库来实现向量化量化的功能。例如,PyTorch本身提供了向量量化(Vector Quantization)的功能,您可以通过PyTorch的官方文档来了解如何使用这些功能。此外,还有一些其他库(如...
Vector Quantization EMA Codebook Prior Learning Index Collapse & Perplexity VQ-VAE-2 VQGAN VQ-Diffusion Latent Diffusion (Stable Diffusion) VQ-VAE VQ-VAE[1] 是Google DeepMind 在 2017 年提出的一个类 VAE 生成模型,相比普通的 VAE,它有两点不同: 隐空间是离散的,通过 VQ (Vector Quantization) 操作...
@@ -1,6 +1,6 @@ [project] name = "vector-quantize-pytorch" version = "1.18.4" version = "1.18.5" description = "Vector Quantization - Pytorch" authors = [ { name = "Phil Wang", email = "lucidrains@gmail.com" } 0 comments on commit ca90db2 Please sign in to comment. ...
Vector Quantization 这个名字听起来有些玄乎,其实它本身并没有这么高深。大家都知道,模拟信号是连续的值,而计算机只能处理离散的数字信号,在将模拟信号转换为数字信号的时候,我们可以用区间内的某一个值去代替着一个区间,比如,[0, 1) 上的所有值变为 0 ,[1, 2) 上的所有值变成 1 ,如此类推。其这就是一...
Quantization both before and after model training is provided today either as part of mainstream DL libraries (“Post-training quantization | TensorFlow Lite,” 2022.; “Quantization — PyTorch 1.9.1 documentation,” 2022.) or third-party libraries such as Larq (“Larq | Binarized Neural Network...
Preventing Local Pitfalls in Vector Quantization via Optimal Transport 0. 摘要 向量量化网络(VQNs)在各种任务中承担了重要的编码工作,但是训练VQN非常不稳定,通常需要采用精细的初始化和模型蒸馏等技术。在本文中,我们确定局部最小值问题是这种不稳定性的主要原因。为了解决这个问题,我们用最优传输方法代替最近邻搜索...
In this blog post, we’ll outline the main ideas behind Neural Compression and Residual Vector Quantization. Neural Compression Neural Compression aims to transform various data types, be it in pixel form (images), waveforms (audio), or frame sequences (video), into more compact representations,...
PQ 方法是把高维向量分割成若干个子向量,然后对每个子向量进行独立的标量量化(Scalar Quantization, SQ),即用一个有限集合中最接近的值来近似表示每个子向量。这样做可以大大减少存储空间和计算时间,并且可以用乘积距离(Product Distance, PD)来近似表示原始距离。这就像是在超市里,商品不仅按照区域分类,还按照品牌分类...
MaskedVectorQuantization (CVPR2023) Offical PyTorch implementation of our CVPR2023 paper "Not All Image Regions Matter: Masked Vector Quantization for Autoregressive Image Generation". TL;DRExisting vector-quantization (VQ) based autoregressive image generation simply modelsall local regioninformation of imag...