cwenzi/neuroflow-cpp

1#include <iostream>2#include "../include/neuroflow/tensor.hpp"3#include "../include/neuroflow/networks.hpp"4 5using namespace neuroflow;6 7int main() {8    std::cout << "LayerNorm class test..." << std::endl;9    10    // Create LayerNorm11    std::cout << "Creating LayerNorm(32)..." << std::endl;12    LayerNorm norm(32);13    14    std::cout << "weight shape size: " << norm.weight.shape_.size() << std::endl;15    std::cout << "weight shape[0]: " << norm.weight.shape_[0] << std::endl;16    std::cout << "weight numel: " << norm.weight.numel() << std::endl;17    std::cout << "weight data_size: " << norm.weight.data_size_ << std::endl;18    19    std::cout << "bias shape size: " << norm.bias.shape_.size() << std::endl;20    std::cout << "bias shape[0]: " << norm.bias.shape_[0] << std::endl;21    std::cout << "bias numel: " << norm.bias.numel() << std::endl;22    std::cout << "bias data_size: " << norm.bias.data_size_ << std::endl;23    24    // Create input25    Tensor input({2, 32});26    float* id = input.as_fp32();27    for (size_t i = 0; i < input.numel(); ++i) id[i] = 0.1f * i;28    29    std::cout << "Calling norm.forward(input)..." << std::endl;30    Tensor output = norm.forward(input);31    32    std::cout << "output shape: [" << output.shape_[0] << ", " << output.shape_[1] << "]" << std::endl;33    34    std::cout << "Success!" << std::endl;35    return 0;36}37