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Sync public subset from Flux (private)

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Gitea CI
2025-10-06 20:14:13 +00:00
parent 272e77c536
commit b2d00af0e1
390 changed files with 152131 additions and 0 deletions
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34
include/modules/neural_networks/loss/Loss _CategoricalCrossentrophy.h Normal file
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#pragma once
#include "./core/omp_config.h"
#include "./utils/vector.h"
#include "./utils/matrix.h"
namespace neural_networks{
template <typename Td, typename Ti>
struct Loss{
utils::Matrix<Td> sample_losses;
Td data_losses;
virtual utils::Vector<Td> forward(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y) = 0;
Td calculate(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y){
// Calculate sample losses
sample_losses = forward(output, y);
// Calculate mean loss
data_losses = numerics::mean(sample_losses);
return data_losses;
}
};
} // end namespace neural_networks

34
include/modules/neural_networks/loss/loss.h Normal file
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#pragma once
#include "./core/omp_config.h"
#include "./utils/vector.h"
#include "./utils/matrix.h"
namespace neural_networks{
template <typename Td, typename Ti>
struct Loss{
utils::Matrix<Td> sample_losses;
Td data_losses;
virtual utils::Vector<Td> forward(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y) = 0;
Td calculate(const utils::Matrix<Td>& output, const utils::Matrix<Ti>& y){
// Calculate sample losses
sample_losses = forward(output, y);
// Calculate mean loss
data_losses = numerics::mean(sample_losses);
return data_losses;
}
};
} // end namespace neural_networks