Programmer Think

The official account was pushed by YOLOX for a while. All the public numbers were pushing hard. It is known as: the performance is over Yolov5, and all YOLO is being played. So, full of expectation, I downloaded the source code and prepared to try 1, Problem description Well, yes, I encountered a lot of bug s, but fortunately they were all s ...

catalogue preface step 1. Download yolov5 source code and tensorrtx source code, and download yolov5s Pt to wts modelstep 2. Install cuDNN, TensorRT and verify that TensorRT is installed successfullystep 3. https://github.com/wang-xinyu Use vs to run through the C + + code of yolov5.0 in githubstep 4. Running your own training modelsumm ...

Convolutional neural network series preface In this article, we use a custom implemented LeNet-5 neural network architecture to perform image classification on MNIST data sets. 1, Integration LeNet was founded in 1998 by Yann Lecun, Leon bottom, yoshua bengio, and Patrick Haffner My thesis Gradient-Based Learning Applied To ...

At present, the updated part includes the basic setting, basic module, relative position coordinate understanding and some code display of swin. swin contains four setting s, tiny, small, base and large. It can be compared to resnet. Swin-b main part network structure BasicLayer Structure display BasicLayer( (blocks): ModuleList ...

Introduction: We built the AlexNet network using the paddy framework, and tested the classification effect of AlexNet for Cifar10 using its supreme version on AI Studio. The classification effect of basic training on the test set can not exceed 60%, which is still a certain distance from the 80% classification effect mentioned in some arti ...

neuron Neuron and perceptron are essentially the same, but when we say perceptron, its activation function is a step function; When we talk about neurons, the activation function is often sigmoid function or tanh function. As shown in the figure below: The method of calculating the output of a neuron is the same as that of a perceptron. Suppo ...

1 Introduction Similarity and dissimilarity are important concepts in machine learning, because they are adopted by many data mining technologies, such as common clustering, nearest neighbor classification and anomaly detection. In many cases, once we calculate the similarity or dissimilarity of eigenvectors, we no longer need the original dat ...

preface In many recent transformer work, we often mention a word: relative position bias. Used in the calculation of self attention. When I first saw this concept, I didn't understand its meaning. This paper is used to my own understanding of relative position bias. The first time I saw the word was in swin transformer. Later, I saw it in bot ...

I Introduction to ResNet algorithm Residual neural network (ResNet) was proposed by he Kaiming of Microsoft Research Institute. ResNet won the championship in ILSVRC in 2015. Through experiments, ResNet has continuously improved the accuracy of the model with the deepening of the network layer, Reach the maximum (accuracy saturation), and the ...

If you are opening this notebook locally, please ensure that you have installed the above dependent packages. You can also here Find the multi GPU distributed training version of this notebook. pip install transformers datasets Fine tune the pre training model for text classification We'll show you how to use 🤗 Transformers The model in th ...