Programmer Think

This article begins with the official account of "AI little boy". Last article This paper introduces the basic process of post training quantization, and demonstrates the simplest post training quantization algorithm with pytorch. Although post training quantization is easy to operate, most reasoning frameworks provide such off-line ...

import torch import torch.nn as nn import numpy as np torch.__version__ '1.0.0' 3.1 actual combat of logistic regression In this chapter, we will deal with structured data and use logistic regression to classify structured data. 3.1.1 introduction to logistic regression Logistic regression is a generalized linear model, which has man ...

DDP principle Distributed data parallel (DDP) supports multi machine and multi card distributed training. pytorch native support. This paper briefly summarizes the use of DDP and the test under multi card, and introduces it according to the actual code. voxceleb_trainer: open source voiceprint recognition tool, simple and easy to use, ...

If you want to complete the project, I will put the github link at the end of the article: You can see that the final identification license plate number is min G99999. In fact, I accidentally thought of doing a small project with c + + in the winter of the previous year, and then realized the license plate extraction and segmentation with c+ ...

1. Purpose of using data loader in the model In the previous linear regression model, we use very little data, so we directly put all the data into the model. However, in deep learning, the amount of data is usually very large. With such a large amount of data, it is impossible to carry out forward calculation and back propagation i ...

  1. General ¶   The core of PyTorch is to provide two main functions: n-dimensional tensor, similar to NumPy, but can run on GPU Automatic differentiation for constructing and training neural networks   We will use the problem of fitting a third-order polynomial to y = sin(x) as a running example. The network will have four paramet ...

preface import torch import torch.nn as nn from torch.nn.utils.rnn import pad_sequence from torch.nn.utils.rnn import pack_padded_sequence from torch.nn.utils.rnn import pad_packed_sequence Notice utils. Above RNN, have you? These functions are "usually" used for RNN related processing. So you have to understand some standard conc ...

Team Introduction The name of our team is Baseline. Because we share Baseline, we call our team Baseline. Captain: Fang Xi is from Shanghai Jiaotong University, the third graduate student. Team member: LV Xiaoxin from Netease, AI Engineer Team member: Wang Hao is from Beijing Xinghe bright spot, software R & D Team member: Yang Xinda i ...

pytorch data operation Getting started and building data Guide Package import torch Create a row vector (a special tensor) What is a tensor: a tensor represents an array of values that may have multiple dimensions. A tensor with one axis corresponds to a vector in mathematics; A tensor with two axes corresponds to a mathematical matrix; Te ...

be careful: 1. All the articles in this series are mainly developed by the gradient lifting tree model. The extracted features are mainly to help the gradient lifting tree model mine the information it can't mine. All the features introduced in this paper can be directly added to the model as features, which is slightly different from the stra ...