一个开源的科学计算引擎
Email: zk@likedge.top
Edge-Computing-Engine is an open-source scientific computing engine designed for matrix computation and machine learning tasks. It provides a wide range of matrix operations and neural network building blocks.
Email: zk@likedge.top
read_csv(string &file_path): Reads a formatted file (csv) and returns a matrix with automatically calculated dimensions.- Formatted file writing interface. Similar to
pandas.to_csv. - Broadcasting mechanism for matrices with padding interface.
- Fully connected layer forward and backward propagation interfaces with automatic differentiation support.
- Matrix differentiation and automatic differentiation interfaces.
save_txt(Matrix mid1,string path = "./",string delimiter = ",",string header="./"): Reads the file header and writes formatted files. It supports writing matrix-type data, custom headers, writing file paths, and custom delimiters (default is ", ").create(row,cols): Creates a matrix with specified dimensions and initializes all elements to 0.move_ele(int &ele1, int &ele2): Changes the value of an element at a specific position.add(Matrix mid1, Matrix mid2, int flag = 1): Matrix addition operation with optional bitwise operation acceleration.subtract(Matrix mid1, Matrix mid2): Matrix subtraction operation.mul(Matrix mid1, Matrix mid2): Matrix multiplication operation.times_mat(int times,Matrix mid1): Scalar matrix multiplication.get_T(Matrix mid1): Matrix transposition operation.mul(matrix1,matrix2): Matrix product (complete mathematical definition).flatten(Matrix mid1): Returns a flattened array.matrix_rs(Matrix mid1,int rs_row,int rs_col): Matrix structure compression.matrix_sum(Matrix mid1): Matrix summation.matrix_mean(Matrix mid1): Matrix mean.apply(Matrix mid1,Matrix mid2,int axis = 0): Matrix concatenation.iloc(Matrix mid1,int start_x=0,int end_x=0,int start_y=0,int end_y=0): Matrix slicing.mul_simple(Matrix mid1,Matrix mid2): Element-wise matrix multiplication for machine learning applications.Relu: Activation function matrix interface.MSE: Mean squared error matrix interface.- Random weight matrix creation interface.
- Convolutional neural network definition (including but not limited to convolution kernel, pooling layer definition, and custom loss interface).
- C++11 or above.
- Clone the repository:
git clone git@github.com:AllenZYJ/Edge-Computing-Engine.git - Build the project:
cd Edge-Computing-Engine/install_diff && make && make install
g++ main.cpp -o main -lautodiff./mainContributions to Edge-Computing-Engine are welcome. To contribute, please follow these steps:
- Fork the repository.
- Create a new branch for your feature or bug fix:
git checkout -b my-new-feature - Make your changes and commit them:
git commit -am 'Add some feature' - Push your changes to the branch:
git push origin my-new-feature - Submit a pull request.
Please ensure your code adheres to the existing style and passes the existing tests before submitting a pull request.
email:zk@likedge.top | edge@ibooker.org.cn
The author's personal website is Likedge, and the author's email is zk@likedge.top.
Edge-Computing-Engine is released under the Apache2.0. See the LICENSE file for details.
