PyTorch-like neural network layers with automatic differentiation. More...

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

Include dependency graph for layers.hpp:

This graph shows which files directly or indirectly include this file:

Classes
class	dl::layers::Module< T >
	Base class for all neural network modules (PyTorch-like nn.Module) More...

class	dl::layers::Linear< T >
	Linear (fully connected) layer: y = xW^T + b. More...

class	dl::layers::ReLU< T >
	ReLU activation function. More...

class	dl::layers::Sigmoid< T >
	Sigmoid activation function. More...

class	dl::layers::Tanh< T >
	Tanh activation function. More...

class	dl::layers::Dropout< T >
	Dropout layer for regularization. More...

class	dl::layers::Sequential< T >
	Sequential container for chaining modules. More...

Typedefs
using	dl::layers::LinearD = Linear< double >

using	dl::layers::LinearF = Linear< float >

using	dl::layers::ReLUD = ReLU< double >

using	dl::layers::ReLUF = ReLU< float >

using	dl::layers::SigmoidD = Sigmoid< double >

using	dl::layers::SigmoidF = Sigmoid< float >

using	dl::layers::TanhD = Tanh< double >

using	dl::layers::TanhF = Tanh< float >

using	dl::layers::DropoutD = Dropout< double >

using	dl::layers::DropoutF = Dropout< float >

using	dl::layers::SequentialD = Sequential< double >

using	dl::layers::SequentialF = Sequential< float >

Detailed Description

PyTorch-like neural network layers with automatic differentiation.

Definition in file layers.hpp.

Classes