Source: Read Chip Technology This article is approximately 4800 words, and it is recommended to read it in 10 minutes. This article introduces 9 tips for training neural networks using Pytorch. Image Source: unsplash.com/@dulgier In fact, your model may still be at the level of the Stone Age. You might still be training with 32-bit … Read more
Click the above “Beginner’s Guide to Vision” to select “Star” or “Top” Heavyweight content delivered first-hand This article is sourced from | Visual Algorithms Don’t let your neural network end up like this Let’s face it, your model might still be stuck in the Stone Age. I bet you’re still using 32-bit precision or GASP … Read more
Hello everyone, I’m Cat Brother! Today let’s talk about PyTorch Geometric, abbreviated as PyG. This is a library based on PyTorch specifically designed for handling Graph Neural Networks (GNN). If you’re interested in graph data such as social networks, recommendation systems, molecular structures, etc., then PyG is an excellent choice! PyG provides many efficient operations … Read more
MLNLP ( Machine Learning Algorithms and Natural Language Processing ) community is a well-known natural language processing community both domestically and internationally, covering NLP master’s and doctoral students, university teachers, and corporate researchers. The vision of the community is to promote communication between the academic and industrial fields of natural language processing and machine learning, … Read more
Click the above “Beginner Learning Vision” to choose to add Star Mark or “Top” Important content delivered immediately I recently started using PyTorch and have encountered quite a few pitfalls. I’m recording them here as I feel they are common issues that many might face. I would also like to thank my friends who helped … Read more
Kaggle Competition Tips Author:William Falcon, Source: AI Park Introduction Some small details can indeed improve speed. Over the past 10 months, during my work with PyTorch Lightning, the team and I have encountered many styles of structuring PyTorch code, and we have identified some key places where people inadvertently introduce bottlenecks. We are very careful … Read more
This article is approximately 1800 words long and is recommended to be read in 5 minutes. This article will deeply introduce the 7 core functions of the torch.utils.data module in PyTorch, which can help you better manage and manipulate data. In machine learning and deep learning projects, data processing is a crucial part. PyTorch, as … Read more
Introduction When constructing models, especially when dealing with the input-output data formats between layers, some commonly used data processing functions such as tensor calculations and broadcasting mechanisms are very important. They remain indispensable when later using the Transformers library with pre-trained models. This article aims to explain the most commonly used Pytorch processing functions for … Read more
Click the “CVer” above to select “Star” or “Pin”. Heavyweight content delivered at the first time. Author: Bi Ji Ji https://zhuanlan.zhihu.com/p/59271905 This article is authorized, and no secondary reproduction is allowed without permission. 1. The Differences Between nn.Module.cuda() and Tensor.cuda() Both the cuda() function can achieve memory migration from CPU to GPU for models and … Read more
Click on the “CVer” above to select “Star” or “Top” Heavyweight content delivered promptly Author: Yu Zhenbo https://zhuanlan.zhihu.com/p/77952356 This article is authorized by the author and cannot be reproduced without permission. Recently, I just started using PyTorch and have encountered quite a few pitfalls. I record them here, as I feel they are common issues … Read more