Convolution implementations with NVidia cuDNN library. More...

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Functions
template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_valid ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	CUDNN implementation of a 2D 'valid' convolution C = I * K. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_valid_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	CUDNN implementation of a 2D 'valid' convolution C = I * K. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_forward ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	cudnn implementation of a 4D 'valid' convolution C = I * K More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_forward_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	cudnn implementation of a 4D 'valid' convolution C = I * K, with flipped weights More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_filter ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	CUDNN implementation of a 4D 'valid' convolution C = I * K, where the output are considered to be kernels. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_filter_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	CUDNN implementation of a 4D 'valid' convolution C = I * K, where the output are considered to be kernels, with flipped weights. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_full ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv)
	cudnn implementation of a 2D 'full' convolution C = I * K More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_full_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv)
	cudnn implementation of a 2D 'full' convolution C = I * K More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_data_full ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv)
	cudnn implementation of a 4D 'full' convolution C = I * K More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_data_full_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv)
	cudnn implementation of a 2D 'valid' convolution C = I * K, with multiple kernels More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_valid_multi ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	CUDNN implementation of a 2D 'valid' convolution C = I * K. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv2_valid_multi_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	Standard implementation of a 2D 'valid' convolution C = I * K, with multiple flipped kernels. More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_data ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	cudnn implementation of a 4D 'valid' backward convolution C = I * K More...

template<typename I , typename K , typename C >
void	etl::impl::cudnn::conv4_backward_data_flipped ([[maybe_unused]] I &&input, [[maybe_unused]] K &&kernel, [[maybe_unused]] C &&conv, [[maybe_unused]] size_t s1, [[maybe_unused]] size_t s2, [[maybe_unused]] size_t p1, [[maybe_unused]] size_t p2)
	cudnn implementation of a 2D 'valid' backward convolution C = I * K More...

Variables
template<typename I , typename K , typename C >
constexpr bool	etl::impl::cudnn::conv_possible = cudnn_enabled&& all_homogeneous<I, K, C>&& all_row_major<I, K, C>&& all_dma<I, K, C>
	Traits indicating if Convolution with CUDNN is possible for the given configuration. More...

template<typename I , typename K >
constexpr bool	etl::impl::cudnn::conv_possible_ = cudnn_enabled&& all_homogeneous<I, K>&& all_row_major<I, K>&& all_dma<I, K>
	Traits indicating if Convolution with CUDNN is possible for the given configuration. More...

Detailed Description

Convolution implementations with NVidia cuDNN library.

Function Documentation

◆ conv2_full()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_full	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv
	)

cudnn implementation of a 2D 'full' convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv2_full_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_full_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv
	)

cudnn implementation of a 2D 'full' convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv2_valid()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_valid	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

CUDNN implementation of a 2D 'valid' convolution C = I * K.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix
s1	The first dimension stride
s2	The second dimension stride
p1	The first dimension padding (left and right)
p2	The second dimension padding (top and bottom)

◆ conv2_valid_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_valid_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

CUDNN implementation of a 2D 'valid' convolution C = I * K.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix
s1	The first dimension stride
s2	The second dimension stride
p1	The first dimension padding (left and right)
p2	The second dimension padding (top and bottom)

◆ conv2_valid_multi()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_valid_multi	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

CUDNN implementation of a 2D 'valid' convolution C = I * K.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv2_valid_multi_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv2_valid_multi_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

Standard implementation of a 2D 'valid' convolution C = I * K, with multiple flipped kernels.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_data()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_data	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

cudnn implementation of a 4D 'valid' backward convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_data_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_data_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

cudnn implementation of a 2D 'valid' backward convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_data_full()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_data_full	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv
	)

cudnn implementation of a 4D 'full' convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_data_full_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_data_full_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv
	)

cudnn implementation of a 2D 'valid' convolution C = I * K, with multiple kernels

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_filter()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_filter	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

CUDNN implementation of a 4D 'valid' convolution C = I * K, where the output are considered to be kernels.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_backward_filter_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_backward_filter_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

CUDNN implementation of a 4D 'valid' convolution C = I * K, where the output are considered to be kernels, with flipped weights.

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_forward()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_forward	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

cudnn implementation of a 4D 'valid' convolution C = I * K

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

◆ conv4_forward_flipped()

template<typename I , typename K , typename C >

void etl::impl::cudnn::conv4_forward_flipped	(	[[maybe_unused] ] I &&	input,
		[[maybe_unused] ] K &&	kernel,
		[[maybe_unused] ] C &&	conv,
		[[maybe_unused] ] size_t	s1,
		[[maybe_unused] ] size_t	s2,
		[[maybe_unused] ] size_t	p1,
		[[maybe_unused] ] size_t	p2
	)

cudnn implementation of a 4D 'valid' convolution C = I * K, with flipped weights

Parameters

input	The input matrix
kernel	The kernel matrix
conv	The output matrix

Variable Documentation

◆ conv_possible

template<typename I , typename K , typename C >

constexpr bool etl::impl::cudnn::conv_possible = cudnn_enabled&& all_homogeneous<I, K, C>&& all_row_major<I, K, C>&& all_dma<I, K, C>

Traits indicating if Convolution with CUDNN is possible for the given configuration.

Parameters

I	The type of the input matrix
K	The type of the kernel matrix
C	The type of the output matrix

◆ conv_possible_

template<typename I , typename K >

constexpr bool etl::impl::cudnn::conv_possible_ = cudnn_enabled&& all_homogeneous<I, K>&& all_row_major<I, K>&& all_dma<I, K>

Traits indicating if Convolution with CUDNN is possible for the given configuration.

Parameters

I	The type of the input matrix
K	The type of the kernel matrix

Functions

Variables

Detailed Description

Function Documentation

◆ conv2_full()

◆ conv2_full_flipped()

◆ conv2_valid()

◆ conv2_valid_flipped()

◆ conv2_valid_multi()

◆ conv2_valid_multi_flipped()

◆ conv4_backward_data()

◆ conv4_backward_data_flipped()

◆ conv4_backward_data_full()

◆ conv4_backward_data_full_flipped()

◆ conv4_backward_filter()

◆ conv4_backward_filter_flipped()

◆ conv4_forward()

◆ conv4_forward_flipped()

Variable Documentation

◆ conv_possible

◆ conv_possible_