LibTorch之张量操作与线性回归

LibTorch之张量操作与线性回归

pytorch到libtorch，一般就是​​[]​​​到​​{}​​的变化

​​一 张量初始化​​​​二 深浅拷贝​​​​三 C++常用数据类型转换Tensor型变量​​​​四 张量维度变换​​​​五 截取张量​​​​六 张量的四则运算​​​​七 获取张量的大小​​​​8.​​​​9.​​​​0.​​

一 张量初始化

1.torch::zeros

#include using namespace std;int main(){ torch::Tensor b = torch::zeros({ 2,3 }); cout << b << endl; system("pause"); return 0;}

2.torch::ones

#include using namespace std;int main(){ torch::Tensor b = torch::ones({ 2,3 }); cout << b << endl; system("pause"); return 0;}

3.torch::eye

#include using namespace std;int main(){ torch::Tensor b = torch::eye(3); cout << b << endl; system("pause"); return 0;}

4.torch::full

#include using namespace std;int main(){ torch::Tensor b = torch::full({ 2,3 }, 999); cout << b << endl; system("pause"); return 0;}

5.torch::tensor

#include using namespace std;int main(){ torch::Tensor b = torch::tensor({ {1,2,3},{4,5,6} }); cout << b << endl; system("pause"); return 0;}

6.torch::rand(产生0-1之间的随机值)

#include using namespace std;int main(){ torch::Tensor b = torch::rand({ 2,3 }); cout << b << endl; system("pause"); return 0;}

7.torch::randn(取正态分布服从N(0,1)的随机值)

#include using namespace std;int main(){ torch::Tensor b = torch::randn({ 2,3 }); cout << b << endl; system("pause"); return 0;}

8.torch::randint（取[min,max)的随机整型数值）

#include using namespace std;int main(){ torch::Tensor b = torch::randint(1, 10, { 2,3 }); cout << b << endl; system("pause"); return 0;}

二 深浅拷贝

1.浅拷贝

torch::Tensor b1 = torch::zeros({3,4});// 浅拷贝torch::Tensor b2 =b1;torch::Tensor b2 = torch::Tensor(b1);

#include using namespace std;int main(){ torch::Tensor b1 = torch::zeros({ 2,3 }); cout << b1 << endl; torch::Tensor b2 = b1; //cout << b2 << endl; //torch::Tensor b2 = torch::Tensor(b1); cout << b2 << endl; // b2[0][0] = 888; cout << "b1:" << endl; cout << b1 << endl; system("pause"); return 0;}

2.深拷贝

torch::Tensor b1 = torch::zeros({3,4});torch::Tensor b2 = b.clone();

#include using namespace std;int main(){ torch::Tensor b1 = torch::zeros({ 2,3 }); cout << "b1:" << endl; cout << b1 << endl; torch::Tensor b2 = b1.clone();; b2[0][0] = 888; cout << "b2:" << endl; cout << b2 << endl; cout << "b1:" << endl; cout << b1 << endl; system("pause"); return 0;}

同大小张量

= torch::zeros_like(b1);b2 = torch::ones_like(b1);b2 = torch::rand_like(b1,torch::kFloat);

#include using namespace std;int main(){ torch::Tensor b1 = torch::zeros({ 2,3 }); torch::Tensor b2 = torch::zeros_like(b1); cout << b2 << endl; b2 = torch::ones_like(b1); cout << b2 << endl; b2 = torch::rand_like(b1, torch::kFloat); cout << b2 << endl; system("pause"); return 0;}

三 C++常用数据类型转换Tensor型变量

1.数组

#include using namespace std;int main(){ int a[10] = { 1,2,3,4,5,6 }; b = torch::from_blob(a, { 6 }, torch::kInt); cout << b << endl; system("pause"); return 0;}

float data[] = { 1, 2, 3, 4, 5, 6 };torch::Tensor f = torch::from_blob(data, {2, 3});

2.向量

#include using namespace std;int main(){ std::vector a = { 1,2,3,4,5,6 }; // 方式1 torch::Tensor b= torch::tensor(a); cout << b << endl; // 方式2 b = torch::from_blob(a.data(), { 2 }, torch::kFloat); cout << b << endl; system("pause"); return 0;}

四 张量维度变换

1.拼接：torch::cat

2.堆叠：torch::stack

3.unsqueeze

::Tensor a = torch::rand({2,3}); std::cout<

五 截取张量

六 张量的四则运算

七 获取张量的大小

#include using namespace std;int main(){ torch::Tensor rgb = torch::randn({ 1, 3, 6, 6 }); cout << rgb << endl; cout << rgb.sizes() << endl; system("pause"); return 0;}

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​​https://pytorch.org/cppdocs/notes/tensor_creation.html​​

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