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Basic functions of processing tensors in 5 PyTorchEvery beginner of deep learning should know these five basic functions of pytoch.Being able to construct neural networks in an accurate and effective way is one of the most sought after skills of recruiters in deep learning engineers. PyTorch is a Python library mainly used for deep learning. On ...

Welcome to my official account, reply to 001 Google programming specification.  O_o   >_<   o_O   O_o   ~_~   o_O   Hello, I'm Jizhi horizon. This paper analyzes the implementation of ACIQ symmetric quantization algorithm, taking Tengine's implementation as an example.  this is the third part of quantitative implementation. Ther ...

1. Basic steps for pytorch to realize linear regression Construct data setDefine Model function moduleConstruct the forward() function in the function module (that is, calculate y_pred)Calculate loss valueSelect optimization methodTraining cycle iteration 2. Several optimization methods of pytorch AdagradAdamAdamaxASGDLBFGSRMSpropRpr ...

Part of speech prediction by Python note42 LSTM Summary of all notes: Pytoch note Happy Planet Model introduction For a word, there will be different parts of speech. First, we can make a preliminary judgment according to the suffix of a word. For example, the suffix - ly is very likely to be an adverb. In addition, a same word can repre ...

Deepstream provides nvinfer plugin s for encapsulating call models. Deepstream's sample code, deepstream app, implements the use of one primary inference engine for invoking multiple models, and one or more secondary inference engines, because the models are converted to TensorRT's engine files before they are used. So it's generally called eng ...

1. What is GAN GAN (Generative Adversarial Networks) is a deep learning model, which passes through two modules in the framework In the original GAN theory, as long as G and D can fit the corresponding generation and discrimination functions, they are not required to be neural networks, but in our practical application, we generally use deep n ...

This article continues with the last part. This article continues with examples of multi-catalog data training models. 4. Multi-directory data training This example is based on previous batch data training and repeated iteration training, and stores data files in multiple directories instead of just one directory to support distributed data a ...

In the first issue, we explained and realized the most basic linear regression. In this issue, we will talk about the regression problem to the classification problem. At this time, we need to add some elements based on the linear regression model, that is activation function so that our model can solve nonlinear data and classification pro ...

Introduction: This paper introduces the angle detection of Apriltag from the experimental point of view, which is related to the posting direction of Apriltag and the internal parameter setting of camera. The robustness of the algorithm is verified by rotating Apriltag code direction detection. Key words: Apriltag, homography matrix   ...

Making image segmentation label data using labelme in Win10 system preface This paper mainly introduces how to use labelme to make semantic segmented label data, and convert the generated json files into usable image labels in batch through code. 1, Install labelme3 sixteen point two 1. Install Anaconda (ignore this step if you hav ...