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26d5b81 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | #include <iostream>
#include "../include/neuroflow/tensor.hpp"
#include "../include/neuroflow/networks.hpp"
using namespace neuroflow;
int main() {
std::cout << "Linear + reshape test..." << std::endl;
size_t d_model = 64;
Linear W_q(d_model, d_model, false);
std::cout << "W_q weight shape: [" << W_q.weight.shape_[0] << ", " << W_q.weight.shape_[1] << "]" << std::endl;
Tensor input({1, d_model});
std::cout << "input shape: [" << input.shape_[0] << ", " << input.shape_[1] << "]" << std::endl;
float* d = input.as_fp32();
std::cout << "Writing data..." << std::endl;
for (size_t i = 0; i < input.numel(); ++i) d[i] = 0.1f * i;
std::cout << "Data written" << std::endl;
std::cout << "reshaping input..." << std::endl;
Tensor x_flat = input.reshape({1, d_model});
std::cout << "x_flat shape: [" << x_flat.shape_[0] << ", " << x_flat.shape_[1] << "]" << std::endl;
std::cout << "Calling W_q.forward(x_flat)..." << std::endl;
Tensor q = W_q.forward(x_flat);
std::cout << "q shape: [" << q.shape_[0] << ", " << q.shape_[1] << "]" << std::endl;
std::cout << "Success!" << std::endl;
return 0;
}
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