Click on the above “Beginner Learning Visuals” to select “Star” or “Pin” Important content delivered to you first Selected from | Medium Author | Aakash N S Contributors | Panda This article is the fourth in this series and will introduce how to train deep neural networks using PyTorch on a GPU. In previous tutorials, … Read more
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
Click the above “Beginner’s Guide to Vision“, select to add “Starred” or “Pinned“ Important content delivered promptly Author: Diving Champion @ Zhihu Source: https://zhuanlan.zhihu.com/p/272767300 Editor: Jishi Platform Jishi Guide The author summarizes their experience in the conversion of models from Pytorch to ONNX, mainly introducing the significance of this conversion work, the path for model … Read more
Click on the above“Beginner Learning Vision” to choose to addStar or “Top” Heavyweight content delivered promptly As we all know, programmers often search for a lot of information online while coding, most of which are code snippets. However, this work can often be exhausting and time-consuming. Therefore, today the editor has reprinted an article from … Read more
MLNLP(Machine Learning Algorithms and Natural Language Processing) community is a well-known natural language processing community both at home and abroad, covering NLP master’s and doctoral students, university teachers, and enterprise researchers. The vision of the community is to promote communication and progress between the academic and industrial sectors of natural language processing and machine learning, … Read more
1 Configuration Issues (1). For computers equipped with a GPU and a need for deep learning, set up a usable and clean deep learning environment. (2). Configure with Anaconda3 + CUDA10.0 + CuDNN + Pytorch1.2 + Pycharm. (3). Resolve the issue of not being able to use the torchvision library in Pytorch. 2 Setup Process … Read more
Author: z.defying Reprinted from: Datawhale Table of Contents: 1 Specify GPU ID 2 View Model Layer Output Details 3 Gradient Clipping 4 Expand Dimensions of a Single Image 5 One-Hot Encoding 6 Prevent Out of Memory When Validating Model 7 Learning Rate Decay 8 Freeze Parameters of Certain Layers 9 Use Different Learning Rates for … Read more
Reprinted from | Xinzhiyuan Author | JinHui Source | https://zhuanlan.zhihu.com/p/220403674 1 『Visualization of Network Structure』 When training a neural network, in addition to observing the trend of the loss function with each step or epoch to establish a basic understanding of the network optimization, we can also use some additional visualization libraries to visualize our … Read more
Source: Deephub Imba This article is approximately 3200 words long and is recommended to be read in 7 minutes. This article will introduce gradient checkpointing, a technique that allows you to train larger models on the GPU at the cost of increased training time. We will implement it in PyTorch and train a classifier model. … Read more