Computation kernels for convolution and deconvolution layers. More...

#include <base_convolution.hpp>

Inheritance diagram for lbann::base_convolution_layer< TensorDataType, Device >:

Collaboration diagram for lbann::base_convolution_layer< TensorDataType, Device >:

Public Types
Public Types
using	WeightsType = data_type_weights< TensorDataType >
	The concrete weights type used by this object. More...

using	OptimizerType = data_type_optimizer< TensorDataType >
	The concrete optimizer type used by this object. More...

template<El::Device D>
using	DMatDT = El::Matrix< TensorDataType, D >

using	ScalingType = TensorDataType

Public Types inherited from lbann::data_type_layer< TensorDataType >
using	InputAbsDistMatrixType = El::AbstractDistMatrix< TensorDataType >
	The tensor type expected in this object. More...

using	OutputAbsDistMatrixType = El::AbstractDistMatrix< TensorDataType >

using	InputAbsDistMatReadProxyType = El::AbstractDistMatrixReadDeviceProxy< TensorDataType, D >
	The proxy tensor type expected in this object. More...

using	OutputAbsDistMatReadProxyType = El::AbstractDistMatrixReadDeviceProxy< TensorDataType, D >

using	InputAbsMatrixType = El::AbstractMatrix< TensorDataType >
	The local tensor type expected in this object. More...

using	OutputAbsMatrixType = El::AbstractMatrix< TensorDataType >

using	WeightsProxyType = weights_proxy< TensorDataType >
	The proxy type for weights used by this object. More...

Public Member Functions
const std::vector< int > &	get_conv_dims () const
	Get convolutional layer parameters. More...

const std::vector< int > &	get_pads () const

const std::vector< int > &	get_strides () const

const std::vector< int > &	get_dilations () const

	base_convolution_layer (int num_data_dims, int output_channels, std::vector< int > conv_dims, std::vector< int > pads, std::vector< int > strides, std::vector< int > dilations, int groups, bool has_bias)

	base_convolution_layer (const base_convolution_layer &other)

base_convolution_layer &	operator= (const base_convolution_layer &other)

	~base_convolution_layer ()

description	get_description () const override
	Human-readable description. More...

void	setup_dims () override
	Setup tensor dimensions Called by the 'setup' function. If there are any input tensors, the base method sets all uninitialized output tensor dimensions equal to the first input tensor dimensions. More...

void	setup_data (size_t max_mini_batch_size) override
	Setup layer data. The kernel weights are setup in the convolution and deconvolution classes. More...

void	setup_gpu () override
	Initialize GPU objects. More...

Serialization
template<typename ArchiveT >
void	serialize (ArchiveT &ar)

Public Member Functions inherited from lbann::data_type_layer< TensorDataType >
	data_type_layer (lbann_comm *, bool persistent_error_signals=false)

virtual	~data_type_layer ()=default

std::string	get_datatype_name () const override

void	forward_prop () final

void	summarize_matrices (lbann_summary &summarizer, int step) override

void	check_setup () override

const OutputAbsDistMatrixType &	get_activations (const Layer &child) const override

OutputAbsDistMatrixType &	get_activations (int child_index=0)

const OutputAbsDistMatrixType &	get_activations (int child_index=0) const

const InputAbsDistMatrixType &	get_error_signals (const Layer &parent) const override

InputAbsDistMatrixType &	get_error_signals (int parent_index=0)

const InputAbsDistMatrixType &	get_error_signals (int parent_index=0) const

El::Int	current_output_mini_batch_size () const override

El::Int	infer_mini_batch_size_from_parents_or_default_to_current () const override

OutputAbsDistMatrixType &	get_temp_grad ()

InputAbsDistMatrixType &	get_branch_tag_input (int tag)

std::vector< std::unique_ptr< InputAbsDistMatrixType > > &	get_branch_tag_input_vector ()

std::vector< std::unique_ptr< OutputAbsDistMatrixType > > &	get_all_activations ()

std::vector< std::unique_ptr< InputAbsDistMatrixType > > &	get_all_prev_activations ()

std::vector< std::unique_ptr< OutputAbsDistMatrixType > > &	get_all_prev_error_signals ()

std::vector< std::unique_ptr< InputAbsDistMatrixType > > &	get_all_error_signals ()

OutputAbsMatrixType &	get_local_activations (int child_index=0)

const OutputAbsMatrixType &	get_local_activations (int child_index=0) const

InputAbsMatrixType &	get_local_error_signals (int parent_index=0)

const InputAbsMatrixType &	get_local_error_signals (int parent_index=0) const

void	set_keep_error_signals (bool) override
	Set whether to keep or dynamically reallocate error signals. More...

El::mpi::Comm &	get_subgrid_comm ()

void	serialize (ArchiveT &ar)

Public Member Functions inherited from lbann::Layer
void	write_proto (lbann_data::Layer &proto) const
	Write layer to proto file. More...

lbann_comm *	get_comm () const

int	get_grid_tag () const noexcept
	Identifying tag for process grid. More...

void	set_grid_tag (int tag)
	Set process grid. More...

bool	runs_inplace () const
	If true, the layer will run in-place (the input and output activations point to the same tensor). Value is set during graph setup (in setup_pointers) based on layer traits and neighboring layers. More...

bool	distconv_enabled () const
	Indicate whether distconv is enabled. More...

	Layer ()

virtual	~Layer ()=default

virtual Layer *	copy () const =0
	Copy function. This function dynamically allocates memory for a layer instance and instantiates a copy. The caller is responsible for deallocating the instance. More...

void	set_name (const std::string name)
	Set the layer instance's name. Each layer in a model should have a unique, preferably human-readable, name. More...

void	set_model (model *m)
	Set the model that manages this layer. More...

std::string	get_name () const
	Get the layer instance's name. More...

model *	get_model () const noexcept
	Get a reference to the model that manages this layer. More...

virtual std::string	get_type () const =0
	Get the layer type's name. More...

virtual data_layout	get_data_layout () const =0
	Get data layout of the data tensors. We assume that the data layouts of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its data layout should override this function to return its template parameter. More...

virtual El::Device	get_device_allocation () const =0
	Get the device allocation for the data tensors. We assume that the decice allocation of the previous activations, activations, previous error signals, and error signals are the same. Each concrete layer that is templated on its device allocation should override this function to return its template parameter. More...

int	get_expected_num_parent_layers () const noexcept
	Get expected number of parent layers. A negative value indicates no limit. More...

int	get_expected_num_child_layers () const noexcept
	Get expected number of child layers. A negative value indicates no limit. More...

virtual int	get_backprop_requirements () const
	Returns the necessary tensors for computing backpropagation. More...

ParallelStrategy &	get_parallel_strategy () noexcept
	Get the parallel strategy for the layer. More...

ParallelStrategy const &	get_parallel_strategy () const noexcept
	Get the parallel strategy for the layer. More...

virtual bool	can_run_inplace () const
	If True, the computation can run in-place (feeding each input activations tensor as the corresponding output activations) More...

bool	using_gpus () const noexcept
	Whether the layer is using a GPU implementation. More...

void	back_prop ()
	Backward propagation step. Given the objective function gradients w.r.t. the output tensors, compute the gradients w.r.t. the input tensors and w.r.t. the weights. This is essentially an application of the chain rule. More...

bool	update ()
	Update step. Update the layer's internal members. Note that the optimization step for the weights happens elsewhere. More...

virtual void	setup (size_t max_mini_batch_size, const std::vector< El::Grid *> &grids)
	Setup layer members. More...

void	summarize_stats (lbann_summary &summarizer, int step)

void	reset_counters ()
	Reset layer stat counters. More...

void	set_communication_flag (SubGraphCommunication type)

SubGraphCommunication	get_communication_flag ()

void	set_num_spliting_groups (El::Int spliting_groups)

El::Int	get_num_spliting_groups () const

std::shared_ptr< El::Grid >	get_mygrid () const

void	reset_inter_subgrid_vc_comm (std::shared_ptr< El::mpi::Comm > mpi_comm)

void	set_subgraph_parallelism_execution ()

bool	subgraph_parallelism_execution () const noexcept

void	set_run_layer_in_subgraph ()

bool	get_run_layer_in_subgraph () const noexcept

const Layer &	get_parent_layer (size_t index=0) const

const Layer &	get_child_layer (size_t index=0) const

std::vector< const Layer * >	get_parent_layers () const

std::vector< const Layer * >	get_child_layers () const

size_t	find_parent_layer_index (const Layer &l) const

size_t	find_child_layer_index (const Layer &l) const

int	get_num_parents () const noexcept
	Get number of parent layers. More...

int	get_num_children () const noexcept
	Get number of child layers. More...

void	add_parent_layer (ViewingLayerPtr parent)
	Add a parent layer. More...

void	add_child_layer (ViewingLayerPtr child)
	Add a child layer. More...

void	replace_parent_layer (ViewingLayerPtr l, size_t index)

void	replace_child_layer (ViewingLayerPtr l, size_t index)

void	clear_parent_layers ()
	Remove pointers to parent layers. More...

void	clear_child_layers ()
	Remove pointers to child layers. More...

ViewingLayerPtr	get_parent_layer_pointer (size_t index) const

ViewingLayerPtr	get_child_layer_pointer (size_t index) const

virtual std::vector< ViewingLayerPtr >	get_layer_pointers ()
	List of pointers to other layers. More...

virtual void	set_layer_pointers (std::vector< ViewingLayerPtr > layers)
	Set list of pointers to other layers. More...

std::vector< ViewingWeightsPtr >	get_weights_pointers () const
	List of pointers to weights. More...

void	set_weights_pointers (std::vector< ViewingWeightsPtr > ptrs)
	Set list of pointers to weights. More...

void	replace_weights (Layer const &other_layer)
	Replace weights with another Layer's weights. More...

std::vector< int >	get_input_dims (size_t input_index=0) const
	Get input tensor dimensions. More...

int	get_input_size (size_t input_index=0) const
	Get input tensor size. More...

std::vector< int >	get_output_dims (size_t output_index=0) const
	Get output tensor dimensions. More...

int	get_output_size (size_t output_index=0) const
	Get output tensor size. More...

void	set_output_dims (std::vector< int > dims, size_t output_index=0)
	Set output tensor dimensions. More...

El::Int	infer_mini_batch_size_from_parents () const

void	set_hint_layer (ViewingLayerPtr l)
	Set hint layer. More...

const Layer *	get_hint_layer () const
	Get hint layer. More...

void	freeze ()

void	unfreeze ()

bool	is_frozen () const

template<typename ArchiveT >
void	serialize (ArchiveT &ar)

Protected Member Functions
virtual std::vector< int >	get_kernel_dims () const =0

void	apply_convolution_dnn (bool during_forward_prop)

void	apply_transposed_convolution_dnn (bool during_forward_prop)

void	apply_bias_dnn ()

void	compute_gradients_dnn (bool using_transposed_convolution)

void	apply_convolution_im2col (bool during_forward_prop)

void	apply_transposed_convolution_im2col (bool during_forward_prop)

void	apply_bias_cpu ()

void	compute_gradients_im2col (bool using_transposed_convolution)

Protected Member Functions inherited from lbann::data_type_layer< TensorDataType >
InputAbsDistMatrixType &	get_prev_activations (int parent_index=0)

const InputAbsDistMatrixType &	get_prev_activations (int parent_index=0) const

OutputAbsDistMatrixType &	get_prev_error_signals (int child_index=0)

const OutputAbsDistMatrixType &	get_prev_error_signals (int child_index=0) const

const InputAbsMatrixType &	get_local_prev_activations (int parent_index=0) const

const OutputAbsMatrixType &	get_local_prev_error_signals (int child_index=0) const

void	setup_matrices (const std::vector< El::Grid * > &grids) override

void	setup_data (size_t max_mini_batch_size) override

void	fp_setup_inputs () override

void	fp_setup_outputs () override

void	bp_setup_gradient_wrt_inputs () override

void	bp_compute () override

InputAbsDistMatrixType const &	weights_values (size_t idx) const
	Get the values matrix for a specific weights object. More...

weights &	master_weights (size_t idx)
	Get a specific master weights object. More...

weights const &	master_weights (size_t idx) const

	data_type_layer (data_type_layer &&other)=default
	Protected lifecycle functions. More...

	data_type_layer (data_type_layer const &other)

data_type_layer &	operator= (data_type_layer &&other)=default

data_type_layer &	operator= (data_type_layer const &other)

Protected Member Functions inherited from lbann::Layer
void	setup_grid ()
	Setup process grid. More...

virtual void	setup_pointers ()
	Setup layer pointers. Called by the 'setup' function. Pointers to parent/child layers are assumed to be already initialized. More...

virtual void	fp_compute ()=0
	Apply layer operation. Called by the 'forward_prop' function. Given the input tensors, the output tensors are populated with computed values. More...

virtual bool	update_compute ()
	Perform the computation for the update step. Returns false if the layer must reset for a new training epoch. More...

	Layer (Layer &&other)=default

	Layer (Layer const &other)

Layer &	operator= (Layer &&other)=default

Layer &	operator= (Layer const &other)

void	add_weights (ViewingWeightsPtr w)

size_t	num_weights () const noexcept

bool	has_weights () const noexcept

bool	has_weights (size_t idx) const noexcept

void	set_num_weights (size_t n)

void	set_weights (size_t idx, ViewingWeightsPtr w)

weights const &	get_weights (size_t idx) const

weights &	get_weights (size_t idx)

void	add_as_gradient_source ()

void	remove_as_gradient_source ()

Protected Attributes
int	m_output_channels

std::vector< int >	m_conv_dims
	Spatial dimensions for convolution kernel. More...

std::vector< int >	m_pads

std::vector< int >	m_strides

std::vector< int >	m_dilations

int	m_groups

ScalingType	m_bias_scaling_factor

Protected Attributes inherited from lbann::Layer
int	m_expected_num_parent_layers = 1

int	m_expected_num_child_layers = 1
	Expected number of child layers. A negative value indicates no limit. More...

model *	m_model = nullptr
	Reference to model managing this layer. More...

bool	m_frozen
	Avoid back prop if frozen. More...

EvalType	m_fp_time
	Time spent in forward propagation. More...

EvalType	m_fp_compute_time
	Time spent in the forward propagation computation. More...

EvalType	m_bp_time
	Time spent in backward propagation. More...

EvalType	m_bp_compute_time
	Time spent in the backward propagation computation. More...

EvalType	m_update_time
	Time spent in updates. More...

std::string	m_name
	Layer instance's name. Each layer in a model should have a unique, preferably human-readable, name. More...

bool	m_runs_inplace = false
	If true, the layer will run in-place (the input and output activations point to the same tensor). Value is set during graph setup (in setup_pointers) based on layer traits and neighboring layers. More...

int	m_grid_tag = -1
	Identifying tag for process grid. More...

SubGraphCommunication	subgraph_communication_method = PT2PT

bool	m_subgraph_parallelism_execution = false

bool	run_layer_in_subgraph = false

std::unique_ptr< std::set< int > >	m_subgrid_ranks

El::Int	m_num_spliting_groups = 1

std::shared_ptr< El::mpi::Comm >	m_interSubGridVCComm

Detailed Description

template<typename TensorDataType, El::Device Device>
class lbann::base_convolution_layer< TensorDataType, Device >

Computation kernels for convolution and deconvolution layers.

Definition at line 94 of file base_convolution.hpp.

Member Typedef Documentation

◆ DMatDT

template<typename TensorDataType , El::Device Device>

template<El::Device D>

using lbann::base_convolution_layer< TensorDataType, Device >::DMatDT = El::Matrix<TensorDataType, D>

Definition at line 107 of file base_convolution.hpp.

◆ OptimizerType

template<typename TensorDataType , El::Device Device>

using lbann::base_convolution_layer< TensorDataType, Device >::OptimizerType = data_type_optimizer<TensorDataType>

The concrete optimizer type used by this object.

Definition at line 104 of file base_convolution.hpp.

◆ ScalingType

template<typename TensorDataType , El::Device Device>

using lbann::base_convolution_layer< TensorDataType, Device >::ScalingType = TensorDataType

Definition at line 112 of file base_convolution.hpp.

◆ WeightsType

template<typename TensorDataType , El::Device Device>

using lbann::base_convolution_layer< TensorDataType, Device >::WeightsType = data_type_weights<TensorDataType>

The concrete weights type used by this object.

Definition at line 101 of file base_convolution.hpp.

Constructor & Destructor Documentation

◆ base_convolution_layer() [1/2]

template<typename TensorDataType , El::Device Device>

lbann::base_convolution_layer< TensorDataType, Device >::base_convolution_layer	(	int	num_data_dims,
		int	output_channels,
		std::vector< int >	conv_dims,
		std::vector< int >	pads,
		std::vector< int >	strides,
		std::vector< int >	dilations,
		int	groups,
		bool	has_bias
	)

Todo:: Remove num_data_dims from arg list

◆ base_convolution_layer() [2/2]

template<typename TensorDataType , El::Device Device>

lbann::base_convolution_layer< TensorDataType, Device >::base_convolution_layer ( const base_convolution_layer< TensorDataType, Device > & other )

◆ ~base_convolution_layer()

template<typename TensorDataType , El::Device Device>

lbann::base_convolution_layer< TensorDataType, Device >::~base_convolution_layer ( )

Member Function Documentation

◆ apply_bias_cpu()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_bias_cpu ( )

protected

◆ apply_bias_dnn()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_bias_dnn ( )

protected

◆ apply_convolution_dnn()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_convolution_dnn ( bool during_forward_prop )

protected

Convolution with DNN library.

◆ apply_convolution_im2col()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_convolution_im2col ( bool during_forward_prop )

protected

Convolution with im2col GEMM algorithm.

◆ apply_transposed_convolution_dnn()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_transposed_convolution_dnn ( bool during_forward_prop )

protected

Transposed convolution with DNN library.

◆ apply_transposed_convolution_im2col()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::apply_transposed_convolution_im2col ( bool during_forward_prop )

protected

Transposed convolution with im2col GEMM algorithm.

◆ compute_gradients_dnn()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::compute_gradients_dnn ( bool using_transposed_convolution )

protected

◆ compute_gradients_im2col()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::compute_gradients_im2col ( bool using_transposed_convolution )

protected

◆ get_conv_dims()

template<typename TensorDataType , El::Device Device>

const std::vector<int>& lbann::base_convolution_layer< TensorDataType, Device >::get_conv_dims ( ) const

inline

Get convolutional layer parameters.

Definition at line 118 of file base_convolution.hpp.

◆ get_description()

template<typename TensorDataType , El::Device Device>

description lbann::base_convolution_layer< TensorDataType, Device >::get_description ( ) const

overridevirtual

Human-readable description.

Reimplemented from lbann::Layer.

◆ get_dilations()

template<typename TensorDataType , El::Device Device>

const std::vector<int>& lbann::base_convolution_layer< TensorDataType, Device >::get_dilations ( ) const

inline

Definition at line 121 of file base_convolution.hpp.

◆ get_kernel_dims()

template<typename TensorDataType , El::Device Device>

virtual std::vector<int> lbann::base_convolution_layer< TensorDataType, Device >::get_kernel_dims ( ) const

protectedpure virtual

Dimensions of convolution kernel.

Implemented in lbann::convolution_layer< TensorDataType, Layout, Device >, and lbann::deconvolution_layer< TensorDataType, Layout, Device >.

◆ get_pads()

template<typename TensorDataType , El::Device Device>

const std::vector<int>& lbann::base_convolution_layer< TensorDataType, Device >::get_pads ( ) const

inline

Definition at line 119 of file base_convolution.hpp.

◆ get_strides()

template<typename TensorDataType , El::Device Device>

const std::vector<int>& lbann::base_convolution_layer< TensorDataType, Device >::get_strides ( ) const

inline

Definition at line 120 of file base_convolution.hpp.

◆ operator=()

template<typename TensorDataType , El::Device Device>

base_convolution_layer& lbann::base_convolution_layer< TensorDataType, Device >::operator= ( const base_convolution_layer< TensorDataType, Device > & other )

◆ serialize()

template<typename TensorDataType , El::Device Device>

template<typename ArchiveT >

void lbann::base_convolution_layer< TensorDataType, Device >::serialize ( ArchiveT & ar )

◆ setup_data()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::setup_data ( size_t max_mini_batch_size )

overridevirtual

Setup layer data. The kernel weights are setup in the convolution and deconvolution classes.

Reimplemented from lbann::Layer.

◆ setup_dims()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::setup_dims ( )

overridevirtual

Setup tensor dimensions Called by the 'setup' function. If there are any input tensors, the base method sets all uninitialized output tensor dimensions equal to the first input tensor dimensions.

Reimplemented from lbann::Layer.

Reimplemented in lbann::convolution_layer< TensorDataType, Layout, Device >, and lbann::deconvolution_layer< TensorDataType, Layout, Device >.

◆ setup_gpu()

template<typename TensorDataType , El::Device Device>

void lbann::base_convolution_layer< TensorDataType, Device >::setup_gpu ( )

overridevirtual

Initialize GPU objects.

Reimplemented from lbann::Layer.

Member Data Documentation

◆ m_bias_scaling_factor

template<typename TensorDataType , El::Device Device>

ScalingType lbann::base_convolution_layer< TensorDataType, Device >::m_bias_scaling_factor

protected

Scaling factor for bias term. If the scaling factor is zero, bias is not applied.

Definition at line 145 of file base_convolution.hpp.

◆ m_conv_dims

template<typename TensorDataType , El::Device Device>

std::vector<int> lbann::base_convolution_layer< TensorDataType, Device >::m_conv_dims

protected

Spatial dimensions for convolution kernel.

Excludes number of input and output channels.

Definition at line 128 of file base_convolution.hpp.

◆ m_dilations

template<typename TensorDataType , El::Device Device>

std::vector<int> lbann::base_convolution_layer< TensorDataType, Device >::m_dilations

protected

Convolution dilations.

Definition at line 134 of file base_convolution.hpp.

◆ m_groups

template<typename TensorDataType , El::Device Device>

int lbann::base_convolution_layer< TensorDataType, Device >::m_groups

protected

Convolution groups. The channels are split into this many independent groups when performing convolution. The default convolution operation has one group, and a depthwise convolution has as many groups as there are input channels.

Definition at line 140 of file base_convolution.hpp.

◆ m_output_channels

template<typename TensorDataType , El::Device Device>

int lbann::base_convolution_layer< TensorDataType, Device >::m_output_channels

protected

Definition at line 124 of file base_convolution.hpp.

◆ m_pads

template<typename TensorDataType , El::Device Device>

std::vector<int> lbann::base_convolution_layer< TensorDataType, Device >::m_pads

protected

Convolution padding.

Definition at line 130 of file base_convolution.hpp.

◆ m_strides

template<typename TensorDataType , El::Device Device>

std::vector<int> lbann::base_convolution_layer< TensorDataType, Device >::m_strides

protected

Convolution strides.

Definition at line 132 of file base_convolution.hpp.

The documentation for this class was generated from the following file:

base_convolution.hpp

Public Types

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

template<typename TensorDataType, El::Device Device> class lbann::base_convolution_layer< TensorDataType, Device >

Member Typedef Documentation

◆ DMatDT

◆ OptimizerType

◆ ScalingType

◆ WeightsType

Constructor & Destructor Documentation

◆ base_convolution_layer() [1/2]

◆ base_convolution_layer() [2/2]

◆ ~base_convolution_layer()

Member Function Documentation

◆ apply_bias_cpu()

◆ apply_bias_dnn()

◆ apply_convolution_dnn()

◆ apply_convolution_im2col()

◆ apply_transposed_convolution_dnn()

◆ apply_transposed_convolution_im2col()

◆ compute_gradients_dnn()

◆ compute_gradients_im2col()

◆ get_conv_dims()

◆ get_description()

◆ get_dilations()

◆ get_kernel_dims()

◆ get_pads()

◆ get_strides()

◆ operator=()

◆ serialize()

◆ setup_data()

◆ setup_dims()

◆ setup_gpu()

Member Data Documentation

◆ m_bias_scaling_factor

◆ m_conv_dims

◆ m_dilations

◆ m_groups

◆ m_output_channels

◆ m_pads

◆ m_strides

template<typename TensorDataType, El::Device Device>
class lbann::base_convolution_layer< TensorDataType, Device >