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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 35 36 37 38 39 40 41 42 43 44 45 46 | #include <iostream>
#include "../include/neuroflow/tensor.hpp"
#include "../include/neuroflow/networks.hpp"
using namespace neuroflow;
int main() {
std::cout << "Linear detail test..." << std::endl;
Linear linear(64, 32);
Tensor input({2, 64});
for (size_t i = 0; i < input.numel(); ++i) input.as_fp32()[i] = 0.1f * i;
std::cout << "input shape: [" << input.shape_[0] << ", " << input.shape_[1] << "]" << std::endl;
std::cout << "input numel: " << input.numel() << std::endl;
std::cout << "input data_size: " << input.data_size_ << std::endl;
std::cout << "input owns_data: " << input.owns_data_ << std::endl;
std::cout << "Linear weight shape: [" << linear.weight.shape_[0] << ", " << linear.weight.shape_[1] << "]" << std::endl;
std::cout << "Linear weight numel: " << linear.weight.numel() << std::endl;
std::cout << "Linear weight data_size: " << linear.weight.data_size_ << std::endl;
std::cout << "Calling linear.forward..." << std::endl;
Tensor output = linear.forward(input);
std::cout << "output shape: [" << output.shape_[0] << ", " << output.shape_[1] << "]" << std::endl;
std::cout << "output numel: " << output.numel() << std::endl;
std::cout << "output data_size: " << output.data_size_ << std::endl;
std::cout << "output owns_data: " << output.owns_data_ << std::endl;
// Check data pointer
float* od = output.as_fp32();
std::cout << "output data ptr: " << (void*)od << std::endl;
std::cout << "First 5 output values: ";
for (size_t i = 0; i < 5; ++i) std::cout << od[i] << " ";
std::cout << std::endl;
// Now do something with output
std::cout << "Copying output..." << std::endl;
Tensor copied = output.clone();
std::cout << "Success!" << std::endl;
return 0;
}
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