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MLNLP community is a well-known machine learning and natural language processing community in China and abroad, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The Vision of the Community is to promote communication and progress between the academic and industrial circles of natural language processing and machine learning in China and abroad, … Read more
This article is about 4200 words long, recommended reading time is over 10 minutes. This article provides a detailed introduction to several key normalization techniques in deep learning. Normalization is a key concept in deep learning that ensures faster convergence, more stable training, and better overall performance. PyTorch includes several normalization layers, and we will … Read more
Source: DeepHub IMBA This article is approximately 6500 words long and is recommended to be read in 13 minutes. This article will build a basic unconditional diffusion model, namely the Denoising Diffusion Probabilistic Model (DDPM). Diffusion models are typically a type of generative deep learning model that creates data by learning the denoising process. There … Read more
Source: DeepHub IMBA This article is about 6400 words long and is recommended for a 12-minute read. In this article, we will demonstrate the use of new features in PyTorch 2.0 and highlight some issues you might encounter when using it. It has been some time since the release of PyTorch 2.0. Have you started … Read more
Translated by: Lin Likun Proofread by: zrx This article is about 6700 words long and is recommended for a 10-minute read. This article discusses the performance analysis and optimization of PyTorch models. Photo by Torsten Dederichs, uploaded to Unsplash Training deep learning models, especially large ones, can be an expensive endeavor. Performance optimization is one … Read more
Click on the above“Beginner Learning Vision”, select to add “Starred” or “Pinned” Essential content delivered promptly Compiled by | ronghuaiyang Source | Frontiers of Artificial Intelligence PyTorch has gained a lot of attention in both academic and industrial research applications. It is a deep learning framework with great flexibility, utilizing a wealth of practical tools … Read more
Source: DeepHub IMBA This article is approximately 2000 words long and is recommended to be read in 9 minutes. Understanding and utilizing multiprocessing techniques are essential for optimizing performance in PyTorch. PyTorch is a popular deep learning framework that is very convenient when using a single GPU for computation. However, when it comes to handling … Read more
Click on the above “Beginner Learning Vision”, select to add “Star” or “Top” Essential resources delivered promptly This is for academic sharing only and does not represent the views of this public account. Please contact us for removal if there is any infringement. Reposted from Zhihu author丨z.defying@Zhihu Source丨https://zhuanlan.zhihu.com/p/76459295 This article整理了13则PyTorch使用的小窍门，包括了指定GPU编号、梯度裁剪、扩展单张图片维度等实用技巧，能够帮助工作者更高效地完成任务。 Table of Contents 1. Specify … Read more
Click the above“Beginner’s Guide to Vision”, select to add “Bookmark” or “Pin” Heavyweight content delivered first-hand Source: Xinzhi Yuan [Guide] The latest 3D visualization tool ‘mm’ released by the Pytorch team can simulate matrix multiplication in a virtual world. The simulated world of matrices is truly here. Matrix multiplication (matmul) is a very important operation … Read more
Click the "Little White Learning Vision" above, select to add "Star" or "Top" Important content delivered first Master these 17 methods to accelerate your PyTorch deep learning training in the most effortless way. Recently, a post on Reddit has gone viral. The topic is about how to speed up PyTorch training. The original author is … Read more