losses.hpp File Reference

PyTorch-like loss functions with automatic differentiation. More...

#include <memory>
#include <vector>
#include "utils/autograd.hpp"
#include "utils/matrix.hpp"

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Classes
class	dl::loss::AutogradLoss< T >
	Base class for autograd-compatible loss functions. More...
class	dl::loss::MSELoss< T >
	Mean Squared Error Loss with autograd support. More...
class	dl::loss::CrossEntropyLoss< T >
	Cross Entropy Loss with autograd support. More...
class	dl::loss::BCELoss< T >
	Binary Cross Entropy Loss with autograd support. More...
class	dl::loss::BCEWithLogitsLoss< T >
	Binary Cross Entropy with Logits Loss. More...
class	dl::loss::HingeLoss< T >
	Hinge Loss with autograd support. More...
class	dl::loss::HuberLoss< T >
	Huber Loss with autograd support. More...

Namespaces
namespace	dl
namespace	dl::loss

Typedefs
using	dl::loss::MSELossD = MSELoss< double >
using	dl::loss::MSELossF = MSELoss< float >
using	dl::loss::CrossEntropyLossD = CrossEntropyLoss< double >
using	dl::loss::CrossEntropyLossF = CrossEntropyLoss< float >
using	dl::loss::BCELossD = BCELoss< double >
using	dl::loss::BCELossF = BCELoss< float >
using	dl::loss::BCEWithLogitsLossD = BCEWithLogitsLoss< double >
using	dl::loss::BCEWithLogitsLossF = BCEWithLogitsLoss< float >
using	dl::loss::HingeLossD = HingeLoss< double >
using	dl::loss::HingeLossF = HingeLoss< float >
using	dl::loss::HuberLossD = HuberLoss< double >
using	dl::loss::HuberLossF = HuberLoss< float >

Detailed Description

PyTorch-like loss functions with automatic differentiation.

Author

Kalenitid

Version

1.0.0

Definition in file losses.hpp.