The Truth of Sisyphus
  • Introduction
  • Deep Learning
    • Basics
      • Hinge Loss
      • Regularizations
      • Linear Classification
      • Multi-Class and Cross Entropy Loss
      • Batch Norm and other Normalizations
      • Optimization
      • Optimization Functions
      • Convolution im2col
      • Activation Functions
      • Derivatives
        • Derivatives of Softmax
        • A Smooth (differentiable) Max Function
      • Model Ensemble
      • Layers Python Implementation
    • Classification
      • Mobile friendly networks
      • Non-local Neural Networks
      • Squeeze-and-Excitation Networks
      • Further Attention Utilization -- Efficience & Segmentation
      • Group Norm
      • ShuffleNet V2
    • Segmentation
      • Several Instance Segmentation
      • A Peek at Semantic Segmentation
      • Design Choices for Mobile Friendly Deep Learning Models, Semantic Segmentation
      • Efficient Video Object Segmentation via Network Modulation
      • BiSeNet
      • DeepLabV3+
    • Detection
      • CornerNet
      • IoU-Net
      • Why smooth L1 is popular in BBox Regression
      • MTCNN-NCNN
      • DetNet
      • SSD Illustration
    • RNN Related
      • GRU vs LSTM
      • BERT
    • Reinforcement Learning
      • AutoML in Practice Review
      • DRL for optimal execution of profolio transaction
    • Multi-task
      • Multi-task Overview
      • What are the tricks in Multi-Task network design?
    • Neural Network Interpretation
      • Neuron Visualization
    • Deep Learning Frameworks
      • How does Caffe work
      • [Gluon] When to use (Hybrid)Sequential and (Hybrid)Block
      • Gluon Hybrid Intro
      • Gluon HybridBlocks Walk-Through
      • A quick tour of Torch internals
      • NCHW / NHWC in Pytorch
      • Static & Dynamic Computation Graph
    • Converting Between DL Frameworks
      • Things To Be Considered When Doing Model Converting
      • Caffe to TensorFlow
    • Computation Graph Optimization
      • Two ways of TensorRT to optimize Neural Network Computation Graph
      • Customized Caffe Memory Optimization
      • NCNN Memory Optimization
      • Symbolic Programs Advantages: More Efficient, Reuse Intermediate Memory, Operation Folding
    • Deep Learning Debug
      • Problems caused by dead ReLU
      • Loss jumps to 87.3365
      • Common Causes of NANs During Training
    • Deployment
      • Efficient Convolution Operation
      • Quantization
    • What I read recently
      • Know Google the Paper Way
      • ECCV 2018
      • Neural Machine Translation
      • Street View OCR Extraction System
      • Teaching Machines to Draw
      • Pixel to Graph
      • Burst Image Deblurring
      • Material for Masses
      • Learning to Separate Object Sounds by Watching Unlabeled Video
    • Papers / Posts to be read
    • Dummy thoughts
  • Machine Learning
    • Classification
    • Regression
    • Clustering
    • Dimension Reduction
    • Metrics
    • Regularization
    • Bayesian Example
    • Machine Learning System Design
    • Recommendation
    • Essentials of Machine Learning
    • Linear Regression
    • Logistic Regression
      • Logistic Function
    • Gaussian Discriminant Analysis
    • Naive Bayes
    • SVM
    • MLE vs MAP
    • Boosting
    • Frequent Questions
    • Conclusion of Machine Learning
  • Python notes
    • Python _ or __ underscores usage
    • Python Multiprocess and Threading Differences
    • Heapq vs. Q.PriorityQueue
    • Python decorator
    • Understanding Python super()
    • @ property
    • Python __all__
    • Is Python List a Linked List or Array
    • What is the "u" in u'Hello world'
    • Python "self"
    • Python object and class
    • Python Class' Instance method, Class method, and Static Methods Demystified
    • Python WTF
    • Python find first value index in a list: [list].index(val)
    • Sort tuples, and lambda usecase
    • Reverse order of range()
    • Python check list is empty
    • Python get ASCII value from character
    • An A-Z of useful Python tricks
    • Python nested function variable scope
    • Python reverse a list
    • Python priority queue -- heapq
  • C++ Notes
    • Templates
    • std::string (C++) and char* (or c-string "string" for C)
    • C++ printf and cout
    • Class Member Function
    • Inline
    • Scope Resolution Operator ::
    • Constructor
    • Destructor
    • Garbage Collection is Critical
    • C++ Question Lists
  • Operating System
    • Basics
    • Mutex & Semaphore
    • Ticket Selling System
    • OS and Memory
    • Sort implementation in STL
    • Compile, link, loading & run
    • How to understand Multithreading and Multiprocessing from the view of Operating System
  • Linux & Productivity
    • Jupyter Notebook on Remote Server
    • Nividia-smi monitoring
  • Leetcode Notes
    • Array
      • 11. Container With Most Water
      • 35. Search Insert Position
    • Linked List
      • Difference between Linked List and Array
      • Linked List Insert
      • Design of Linked List
      • Two Pointers
        • 141. Linked List Cycle
        • 142. Linked List Cycle II
        • 160. Intersection of two Linked List
        • 19. Remove N-th node from the end of linked list
      • 206. Reverse Linked List
      • 203. Remove Linked List Elements
      • 328. Odd Even Linked List
      • 234. Palindrome Linked List
      • 21. Merge Two Sorted Lists
      • 430. Flatten a Multilevel Doubly Linked List
      • 430. Flatten a Multilevel Doubly Linked List
      • 708. Insert into a Cyclic Sorted List
      • 138. Copy List with Random Pointer
      • 61. Rotate List
    • Binary Tree
      • 144. Binary Tree Preorder Traversal
      • 94. Binary Tree Iterative In-order Traverse
    • Binary Search Tree
      • 98. Validate Binary Search Tree
      • 285. Inorder Successor in BST
      • 173. Binary Search Tree Iterator
      • 700. Search in a Binary Search Tree
      • 450. Delete Node in a BST
      • 701. Insert into a Binary Search Tree
      • Kth Largest Element in a Stream
      • Lowest Common Ancestor of a BST
      • Contain Duplicate III
      • Balanced BST
      • Convert Sorted Array to Binary Search Tree
    • Dynamic Programming
      • 198. House Robber
      • House Robber II
      • Unique Path
      • Unique Path II
      • Best time to buy and sell
      • Partition equal subset sum
      • Target Sum
      • Burst Ballons
    • DFS
      • Clone Graph
      • General Introduction
      • Array & String
      • Sliding Window
  • Quotes
    • Concert Violinist Joke
    • 船 Ship
    • What I cannot create, I do not understand
    • Set your course by the stars
    • To-do list
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  1. C++ Notes

Constructor

■给创建的对象建立一个标识符;

■ 为对象数据成员开辟内存空间;

■ 完成对象数据成员的初始化。

■ 当用户没有显式的去定义构造函数时, 编译器会为类生成一个默认的构造函数, 称为 "默认构造函数”

■ 在对象被创建时自动执行;构造函数的函数名与类名相同;没有返回值类型、也没有返回值;构造函数不能被显式调用。

■ 由于在大多数情况下我们希望在对象创建时就完成一些对成员属性的初始化等工作, 而默认构造函数无法满足我们的要求, 所以我们需要显式定义一个构造函数来覆盖掉默认构造函数以便来完成必要的初始化工作, 当用户自定义构造函数后编译器就不会再为对象生成默认构造函数。

#给Python程序员的注释: C++中的构造函数类似于Python中的 __init__ 方法.
#include <iostream>

    using namespace std;

    class Point
    {
        public:
            Point(int x = 0, int y = 0)     //带有默认参数的构造函数
            {
                cout<<"自定义的构造函数被调用...\n";
                xPos = x;         //利用传入的参数值对成员属性进行初始化
                yPos = y;
            }
            void printPoint()
            {
                cout<<"xPos = " << xPos <<endl;
                cout<<"yPos = " << yPos <<endl;
            }

        private:
            int xPos;
            int yPos;
    };

    int main()
    {
        Point M(10, 20);    //创建对象M并初始化xPos,yPos为10和20
        M.printPoint();

        Point N(200);       //创建对象N并初始化xPos为200, yPos使用参数y的默认值0
        N.printPoint();

        Point P;            //创建对象P使用构造函数的默认参数
        P.printPoint();

        return 0;
    }
  • 构造函数也毕竟是函数, 与普通函数相同, 构造函数也支持重载, 需要注意的是, 在进行构造函数的重载时要注意重载和参数默认的关系要处理好, 避免产生代码的二义性导致编译出错

  • 构造函数的定义也可放在类外进行

  • 可以通过调用初始化表来进行完成初始化;每个成员在初始化表中只能出现一次, 并且初始化的顺序不是取决于数据成员在初始化表中出现的顺序, 而是取决于在类中声明的顺序。

Point(int x = 0, int y = 0):xPos(x), yPos(y)  //使用初始化表
        {
            cout<<"调用初始化表对数据成员进行初始化!\n";
        }
PreviousScope Resolution Operator ::NextDestructor

Last updated 6 years ago

https://www.cnblogs.com/mr-wid/archive/2013/02/19/2917911.html