Perceptron Perceporn
Theory "Statistical Learning Methods" Chapter 2 Perceptron
Code numpy version && torch version
Python3.7
%matplotlib inline
Model
The linear classification model of binary classification aims to find a hyperplane to linearly divide all instances into positive examples and negative examples, a ...
Posted by dbrown on Fri, 27 Jan 2023 14:27:42 +0300
The use of tensorboard (1)
The use of the .add_scalar() method in the SummaryWriter class (you can hold down Ctrl and click add_scalar to view the function of this method).
First install tensorboard with pip, and execute the following command to draw an image with y=2x.
from torch.utils.tensorboard import SummaryWriter
writer = SummaryWri ...
Posted by pvraja on Fri, 20 Jan 2023 10:18:36 +0300
Deep neural networks take a long time to train. Training speed is affected by factors such as model complexity, batch size, GPU, size of training dataset, etc.In PyTorch, torch.utils.data.Dataset and torch.utils.data.DataLoader are commonly used to load datasets and generate batches. But starting with version 1.11, PyTorch introduces the TorchD ...
Posted by psychowolvesbane on Tue, 27 Dec 2022 05:47:13 +0300
MNIST libtorch practical exercise
Ready to work
First download the MNIST database, http://yann.lecun.com/exdb/mnist/
After downloading, do not decompress it with software such as winrar. For example, t10k-images-idx3-ubyte is decompressed into t10k-images.idx3-ubyte. It is best to decompress it with tar in Linux environment.
Suppose you unzip t ...
Posted by chrys on Wed, 25 May 2022 15:51:55 +0300
Running PyTorch code on GPU - neural network programming guide
In this episode, we will learn how to use GPU and PyTorch. We will see how to use the general methods of GPU, and we will see how to apply these general techniques to train our neural networks.
Deep learning using GPU
If you haven't seen the episode about why deep learning and neur ...
This article will share how to quickly run the interesting model on Hugging Face locally through Docker. Run the model with less code and less time cost than the original project.
If you are familiar with Python, most model projects can be deployed and run locally in about 10 minutes.
Write in front
In order to facilitate the display, I chos ...
From PyTorch 1.4 tutorial
Outline
Tensor
torch.autograd.backward
If the result node is scalar
If the result node is a vector
[PyTorch] Note 02: Autograd auto derivation
In PyTorch, the core of all neural networks is autograd package
1 Tensor
torch.Tensor is the core class of this autograd
A Tensor tensor usually records the following ...
Posted by rusbb on Thu, 19 May 2022 21:17:09 +0300
Overview of data processing toolbox
Pytoch involves data processing (data loading, data preprocessing, data enhancement, etc.), and the main toolkits and related relationships are as follows:
Overview of pytorch data processing toolkit
torch.utils.data Toolkit
1) Dataset: abstract class. Other datasets should inherit this class and contain ...
1, Foreword
Introduction to ECA-NET(CVPR 2020):
Thesis title:ECA-Net: Effificient Channel Attention for Deep Convolutional Neural NetworksThesis address:https://arxiv.org/abs/1910.03151Open source code:https://github.com/BangguWu/ECANet
As a lightweight attention mechanism, ECA net is actually an implementation form of channel attention mecha ...
Posted by phpflixnewbie on Sun, 15 May 2022 01:47:39 +0300
Recently, I will do line-level handwritten document detection work, merge CASIA-HWDB2.x (offline) data, and generate a page-level dataset with corresponding bbox. If you want to exchange ocr-related work, you can join the group (at the end of the article):
CASIA-HWDB2.x (offline) data set download address: http://www.nlpr.ia.ac.cn/databases/ha ...
Posted by nwoeddie23 on Sat, 14 May 2022 10:42:27 +0300