Convolution operation following ONNX Conv operator specification. More...

#include <sdfg/data_flow/library_nodes/math/tensor/conv_node.h>

Inheritance diagram for sdfg::math::tensor::ConvNode:

Classes
struct	ConvExpandPrerequisits

Public Member Functions
	ConvNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, data_flow::DataFlowGraph &parent, const std::vector< symbolic::Expression > &shape, const std::vector< symbolic::Expression > &kernel_shape, const std::vector< symbolic::Expression > &strides, const std::vector< symbolic::Expression > &pads, const std::vector< symbolic::Expression > &dilations, symbolic::Expression output_channels, symbolic::Expression group, bool with_bias=false, QuantizationType quantization=QUANTIZATION_MATCH_INPUTS, const data_flow::ImplementationType &impl_type=data_flow::ImplementationType_NONE)
	Construct a convolution node.
symbolic::Expression	output_channels () const
	Get the output channels.
symbolic::Expression	group () const
	Get the group count.
void	validate (const Function &function) const override
	Validate the code node's configuration.
symbolic::MultiExpression	get_out_shape ()
bool	has_bias () const
passes::LibNodeExpander::ExpandOutcome	expand (passes::LibNodeExpander::ExpandContext &context, structured_control_flow::Block &block) override
	Expand convolution into nested maps for n-dimensional convolution.
symbolic::SymbolSet	symbols () const override
	Get all symbols used in this node.
void	replace (const symbolic::Expression old_expression, const symbolic::Expression new_expression) override
void	replace (const symbolic::ExpressionMapping &replacements) override
bool	supports_integer_types () const override
	Check if this operation supports integer types.
std::unique_ptr< data_flow::DataFlowNode >	clone (size_t element_id, const graph::Vertex vertex, data_flow::DataFlowGraph &parent) const override
	Clone this node for graph transformations.
std::string	toStr () const override
	Convert node to string representation.
symbolic::Expression	num_output_elements () const
	Total number of output elements: N * C_out * prod(output_spatial_dim(i)).
symbolic::Expression	kernel_iteration_count () const
	Number of multiply-accumulate iterations per output element: (C_in / group) * prod(kernel_shape[i]).
symbolic::Expression	flop () const override
	Calculate floating point operations for this node.
data_flow::PointerAccessType	pointer_access_type (int input_idx) const override
	Describes what a pointer is used for.
bool	check_expandable (data_flow::DataFlowGraph &dfg, ConvExpandPrerequisits &boundary) const
Public Member Functions inherited from sdfg::math::tensor::SpatialTensorNode
	SpatialTensorNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, data_flow::DataFlowGraph &parent, const data_flow::LibraryNodeCode &code, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs, const data_flow::ImplementationType &impl_type, QuantizationType quantization, const std::vector< symbolic::Expression > &shape, const std::vector< symbolic::Expression > &kernel_shape, const std::vector< symbolic::Expression > &strides, const std::vector< symbolic::Expression > &pads, const std::vector< symbolic::Expression > &dilations)
const std::vector< symbolic::Expression > &	shape () const
const std::vector< symbolic::Expression > &	kernel_shape () const
const std::vector< symbolic::Expression > &	strides () const
const std::vector< symbolic::Expression > &	pads () const
const std::vector< symbolic::Expression > &	dilations () const
QuantizationType	quantization () const
QuantizationType	quantization (const data_flow::DataFlowGraph &dataflow) const
	type of the math calculations.
std::optional< QuantizationType >	uniform_quantization (const data_flow::DataFlowGraph &dataflow) const
	Same result as quantization if it matches all the inputs.
QuantizationType	fixed_quantization () const
	configuration of the type for the math calculations, independent of current input types etc.
void	set_fixed_quantization (const QuantizationType quant)
symbolic::SymbolSet	symbols () const override
	Get all symbols used in this node.
void	replace (const symbolic::Expression old_expression, const symbolic::Expression new_expression) override
void	replace (const symbolic::ExpressionMapping &replacements) override
size_t	num_spatial_dims () const
	Number of spatial dimensions.
symbolic::Expression	output_spatial_dim (size_t i) const
	Compute the output size for spatial dimension `i`.
symbolic::Expression	output_spatial_volume () const
	Total number of output spatial elements: prod(output_spatial_dim(i)).
symbolic::Expression	kernel_volume () const
	Total number of kernel / window elements: prod(kernel_shape[i]).
std::basic_ostream< char > &	operator<< (std::basic_ostream< char > &os) const
Public Member Functions inherited from sdfg::math::tensor::TensorNode
	TensorNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, data_flow::DataFlowGraph &parent, const data_flow::LibraryNodeCode &code, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs, const data_flow::ImplementationType &impl_type)
	Construct a tensor node.
virtual void	verify_data_types (const data_flow::DataFlowGraph &graph) const
	Called as part of validate.
void	validate (const Function &function) const override
	Validate tensor node constraints.
types::PrimitiveType	primitive_type (const data_flow::DataFlowGraph &graph) const
	Get the primitive type of this tensor operation.
Public Member Functions inherited from sdfg::math::MathNode
	MathNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, data_flow::DataFlowGraph &parent, const data_flow::LibraryNodeCode &code, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs, const data_flow::ImplementationType &implementation_type, bool side_effects=false)
	Construct a mathematical library node.
Public Member Functions inherited from sdfg::data_flow::LibraryNode
	LibraryNode (const LibraryNode &data_node)=delete
LibraryNode &	operator= (const LibraryNode &)=delete
virtual	~LibraryNode ()=default
ElementType	type_id () const override
	Returns the type of the element.
const LibraryNodeCode &	code () const
	Get the operation code.
const ImplementationType &	implementation_type () const
	Get the implementation type (const).
ImplementationType &	implementation_type ()
	Get the implementation type (mutable).
void	set_implementation_type (const ImplementationType &impl_type)
bool	side_effect () const override
	Check if this node has side effects.
PointerAccessType	pointer_access_type (const Memlet &edge) const
virtual bool	relocalize_operand (int input_idx, const math::tensor::TensorLayout &packed)
	Repoint the operand at `input_idx` to a locally staged buffer.
virtual bool	can_relocalize_operand (int input_idx, const math::tensor::TensorLayout &packed) const
	Side-effect-free predicate mirroring relocalize_operand: whether the operand at `input_idx` can be repointed at the buffer view `packed`.
virtual std::optional< SubgroupAccess >	operand_access (int input_idx, unsigned subgroup_size) const
	The elements one subgroup of `subgroup_size` lanes reads from the operand at `input_idx`, if the node declares them.
EdgeRemoveOption	can_remove_out_edge (const data_flow::DataFlowGraph &graph, const Memlet *memlet) const override
	Is the edge in question removable, or will this make the node its an output on invalid?
EdgeRemoveOption	can_remove_in_edge (const data_flow::DataFlowGraph &graph, const Memlet *memlet) const override
bool	pointer_use_creates_side_effects (const DataFlowGraph &dataflow, const Function &func)
Public Member Functions inherited from sdfg::data_flow::CodeNode
	CodeNode (const CodeNode &data_node)=delete
CodeNode &	operator= (const CodeNode &)=delete
const std::vector< std::string > &	outputs () const
	Get output connector names (const).
const std::vector< std::string > &	inputs () const
	Get input connector names (const).
std::vector< std::string > &	outputs ()
	Get output connector names (mutable).
std::vector< std::string > &	inputs ()
	Get input connector names (mutable).
const std::string &	output (size_t index) const
	Get output connector name by index.
const std::string &	input (size_t index) const
	Get input connector name by index.
bool	has_constant_input (size_t index) const
	Check if an input is connected to a constant node.
Public Member Functions inherited from sdfg::data_flow::DataFlowNode
	DataFlowNode (const DataFlowNode &data_node)=delete
DataFlowNode &	operator= (const DataFlowNode &)=delete
graph::Vertex	vertex () const
	Get the graph vertex for this node.
const DataFlowGraph &	get_parent () const
	Get the parent dataflow graph (const).
DataFlowGraph &	get_parent ()
	Get the parent dataflow graph (mutable).
virtual bool	update_edge_removed (const std::string &out_conn)
Public Member Functions inherited from sdfg::Element
	Element (size_t element_id, const DebugInfo &debug_info)
virtual	~Element ()=default
size_t	element_id () const
const DebugInfo &	debug_info () const
void	set_debug_info (const DebugInfo &debug_info)
void	add_metadata (const std::string &key, const std::string &value)
void	remove_metadata (const std::string &key)
const std::string &	metadata (const std::string &key) const
const std::string *	metadata_if_exists (const std::string &key) const
const std::unordered_map< std::string, std::string > &	metadata () const
std::string_view	element_type () const
	Returns the type of the element as a human-readable string.

Static Public Member Functions
static blas::BLAS_Precision	get_blas_precision (types::Scalar base_type)
Static Public Member Functions inherited from sdfg::data_flow::LibraryNode
static bool	classof (const Element &element)
Static Public Member Functions inherited from sdfg::data_flow::CodeNode
static bool	classof (const Element &element)
	LLVM-style RTTI predicate: true if `element` is a CodeNode.
Static Public Member Functions inherited from sdfg::data_flow::DataFlowNode
static bool	classof (const Element &element)
	LLVM-style RTTI predicate: true if `element` is a DataFlowNode.

Static Public Attributes
static int constexpr	Y_INPUT_IDX = 0
static int constexpr	X_INPUT_IDX = 1
static int constexpr	W_INPUT_IDX = 2
static int constexpr	B_INPUT_IDX = 3
Static Public Attributes inherited from sdfg::data_flow::CodeNode
static constexpr ElementType	TypeGroup = ElementType::Tasklet \| ElementType::LibraryNode
	Bitmask of all concrete ElementTypes that are CodeNodes.
Static Public Attributes inherited from sdfg::data_flow::DataFlowNode
static constexpr ElementType	TypeGroup
	Bitmask of all concrete ElementTypes that are DataFlowNodes.

Protected Attributes
symbolic::Expression	output_channels_
	Number of output channels (C_out).
symbolic::Expression	group_
	Number of groups for grouped convolution.
bool	with_bias_
Protected Attributes inherited from sdfg::math::tensor::SpatialTensorNode
QuantizationType	fixed_quantization_
std::vector< symbolic::Expression >	shape_
	Input shape [N, C, D1, ..., Dn].
std::vector< symbolic::Expression >	kernel_shape_
	Pooling window shape [k1, ..., kn].
std::vector< symbolic::Expression >	strides_
	Stride along each spatial axis.
std::vector< symbolic::Expression >	pads_
	Padding (start and end for each axis).
std::vector< symbolic::Expression >	dilations_
	Dilation along each spatial axis.
Protected Attributes inherited from sdfg::data_flow::LibraryNode
LibraryNodeCode	code_
	Operation identifier (e.g., "GEMM", "Add").
bool	side_effect_
	Whether this node has side effects.
ImplementationType	implementation_type_
	How to implement this node.
Protected Attributes inherited from sdfg::data_flow::CodeNode
std::vector< std::string >	outputs_
	Names of output connectors.
std::vector< std::string >	inputs_
	Names of input connectors.
Protected Attributes inherited from sdfg::Element
size_t	element_id_
DebugInfo	debug_info_
std::unordered_map< std::string, std::string >	metadata_

Additional Inherited Members
Protected Member Functions inherited from sdfg::math::tensor::TensorNode
void	validate_shape_matches (const std::vector< symbolic::Expression > &required_shape, const TensorLayout &layout, const std::string &name) const
Protected Member Functions inherited from sdfg::data_flow::LibraryNode
	LibraryNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, DataFlowGraph &parent, const LibraryNodeCode &code, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs, const bool side_effect, const ImplementationType &implementation_type)
	Protected constructor for library nodes.
Protected Member Functions inherited from sdfg::data_flow::CodeNode
	CodeNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, DataFlowGraph &parent, const std::vector< std::string > &outputs, const std::vector< std::string > &inputs)
	Protected constructor for code nodes.
Protected Member Functions inherited from sdfg::data_flow::DataFlowNode
	DataFlowNode (size_t element_id, const DebugInfo &debug_info, const graph::Vertex vertex, DataFlowGraph &parent)
	Protected constructor for dataflow nodes.
Static Protected Member Functions inherited from sdfg::math::tensor::TensorNode
static data_flow::TaskletCode	get_integer_minmax_tasklet (types::PrimitiveType prim_type, bool is_max)
	Get the appropriate tasklet code for min/max operations on integers.

Detailed Description

Convolution operation following ONNX Conv operator specification.

ConvNode represents a convolution operation that is compatible with the ONNX Conv operator. The operation is expanded using nested maps for n-dimensional convolutions (1D, 2D, 3D, etc.).

Input/Output Requirements

Input connector "X": Input tensor [N, C_in, D1, ..., Dn]
Input connector "W": Weight tensor [C_out, C_in/group, k1, ..., kn]
Input connector "B" (optional): Bias tensor [C_out]
Output connector "Y": Output tensor [N, C_out, D1_out, ..., Dn_out]

Expansion Support

naïve: Full support
im2col: Does not support non-contiguous output tensor and non-BLAS primitive types
im2row: Does not support grouping (groups != 1) and non-BLAS primitive types

Example

Creating a 2D convolution:

std::vector<symbolic::Expression> kernel_shape = {symbolic::integer(3), symbolic::integer(3)};
std::vector<symbolic::Expression> strides = {symbolic::integer(1), symbolic::integer(1)};
std::vector<symbolic::Expression> pads = {symbolic::integer(1), symbolic::integer(1),
                                           symbolic::integer(1), symbolic::integer(1)};
std::vector<symbolic::Expression> dilations = {symbolic::integer(1), symbolic::integer(1)};
auto group = symbolic::integer(1);
 
auto& conv_node = builder.add_library_node<math::tensor::ConvNode>(
    block, debug_info, kernel_shape, strides, pads, dilations, group
);

Constructor & Destructor Documentation

◆ ConvNode()

sdfg::math::tensor::ConvNode::ConvNode	(	size_t	element_id,
		const DebugInfo &	debug_info,
		const graph::Vertex	vertex,
		data_flow::DataFlowGraph &	parent,
		const std::vector< symbolic::Expression > &	shape,
		const std::vector< symbolic::Expression > &	kernel_shape,
		const std::vector< symbolic::Expression > &	strides,
		const std::vector< symbolic::Expression > &	pads,
		const std::vector< symbolic::Expression > &	dilations,
		symbolic::Expression	output_channels,
		symbolic::Expression	group,
		bool	with_bias = false,
		QuantizationType	quantization = QUANTIZATION_MATCH_INPUTS,
		const data_flow::ImplementationType &	impl_type = data_flow::ImplementationType_NONE )

Construct a convolution node.

Parameters

element_id	Unique element identifier
debug_info	Debug information
vertex	Graph vertex
parent	Parent dataflow graph
shape	Input tensor shape [N, C_in, D1, ..., Dn]
kernel_shape	Shape of the convolution kernel
strides	Stride along each spatial axis (defaults to 1 for each axis)
pads	Padding for start and end of each axis (defaults to 0)
dilations	Dilation along each spatial axis (defaults to 1)
output_channels	Number of output channels
group	Number of groups for grouped convolution (defaults to 1)

Member Function Documentation

◆ check_expandable()

bool sdfg::math::tensor::ConvNode::check_expandable	(	data_flow::DataFlowGraph &	dfg,
		ConvExpandPrerequisits &	boundary ) const

◆ clone()

std::unique_ptr< data_flow::DataFlowNode > sdfg::math::tensor::ConvNode::clone	(	size_t	element_id,
		const graph::Vertex	vertex,
		data_flow::DataFlowGraph &	parent ) const

overridevirtual

Clone this node for graph transformations.

Parameters

element_id	New element identifier for the clone
vertex	New graph vertex for the clone
parent	Parent graph for the clone

Returns: Unique pointer to the cloned node

Pure virtual function that must be implemented by derived classes to support graph transformations and optimizations.

Implements sdfg::data_flow::DataFlowNode.

◆ expand()

passes::LibNodeExpander::ExpandOutcome sdfg::math::tensor::ConvNode::expand	(	passes::LibNodeExpander::ExpandContext &	context,
		structured_control_flow::Block &	block )

overridevirtual

Expand convolution into nested maps for n-dimensional convolution.

Expands the convolution operation by:

Creating outer maps for parallel iteration over batch and output dimensions
Creating inner for loops for sequential accumulation over input channels and kernel
Computing convolution using FMA (fused multiply-add) tasklets
Adding bias if present
Writing results to output tensor

Supports n-dimensional convolutions (1D, 2D, 3D, and higher) with configurable strides and padding for each spatial dimension.

Implements sdfg::math::MathNode.

◆ flop()

symbolic::Expression sdfg::math::tensor::ConvNode::flop ( ) const

overridevirtual

Calculate floating point operations for this node.

Returns: Symbolic expression for FLOP count (or null)

Reimplemented from sdfg::data_flow::LibraryNode.

◆ get_blas_precision()

blas::BLAS_Precision sdfg::math::tensor::ConvNode::get_blas_precision ( types::Scalar base_type )

static

◆ get_out_shape()

symbolic::MultiExpression sdfg::math::tensor::ConvNode::get_out_shape ( )

◆ group()

symbolic::Expression sdfg::math::tensor::ConvNode::group ( ) const

inline

Get the group count.

Returns: Number of groups for grouped convolution

◆ has_bias()

bool sdfg::math::tensor::ConvNode::has_bias ( ) const

◆ kernel_iteration_count()

symbolic::Expression sdfg::math::tensor::ConvNode::kernel_iteration_count ( ) const

Number of multiply-accumulate iterations per output element: (C_in / group) * prod(kernel_shape[i]).

◆ num_output_elements()

symbolic::Expression sdfg::math::tensor::ConvNode::num_output_elements ( ) const

Total number of output elements: N * C_out * prod(output_spatial_dim(i)).

◆ output_channels()

symbolic::Expression sdfg::math::tensor::ConvNode::output_channels ( ) const

inline

Get the output channels.

Returns: Number of output channels

◆ pointer_access_type()

data_flow::PointerAccessType sdfg::math::tensor::ConvNode::pointer_access_type ( int input_idx ) const

overridevirtual

Describes what a pointer is used for.

Parameters

input_idx index of input that is a pointer.

Returns: Invalid if not asked about a pointer input

Reimplemented from sdfg::data_flow::LibraryNode.

◆ replace() [1/2]

void sdfg::math::tensor::ConvNode::replace	(	const symbolic::Expression	old_expression,
		const symbolic::Expression	new_expression )

overridevirtual

Implements sdfg::Element.

◆ replace() [2/2]

void sdfg::math::tensor::ConvNode::replace ( const symbolic::ExpressionMapping & replacements )

overridevirtual

Reimplemented from sdfg::Element.

◆ supports_integer_types()

bool sdfg::math::tensor::ConvNode::supports_integer_types ( ) const

inlineoverridevirtual

Check if this operation supports integer types.

Operations like add, sub, mul, div, min, max support both floating-point and integer types. Operations like exp, log, tanh, sigmoid only support floating-point types.

Returns: true if integer types are supported, false otherwise

Implements sdfg::math::tensor::TensorNode.

◆ symbols()

symbolic::SymbolSet sdfg::math::tensor::ConvNode::symbols ( ) const

overridevirtual

Get all symbols used in this node.

Returns: Set of symbolic expressions used by this node

Implements sdfg::data_flow::LibraryNode.

◆ toStr()

std::string sdfg::math::tensor::ConvNode::toStr ( ) const

overridevirtual

Convert node to string representation.

Returns: String representation of the node

Reimplemented from sdfg::data_flow::LibraryNode.

◆ validate()

void sdfg::math::tensor::ConvNode::validate ( const Function & function ) const

overridevirtual

Validate the code node's configuration.

Parameters

function Function context for validation

Ensures that:

No two access nodes connect to the same data for inputs/outputs

Reimplemented from sdfg::data_flow::CodeNode.

Member Data Documentation

◆ B_INPUT_IDX

int constexpr sdfg::math::tensor::ConvNode::B_INPUT_IDX = 3

staticconstexpr

◆ group_

symbolic::Expression sdfg::math::tensor::ConvNode::group_

protected

Number of groups for grouped convolution.

◆ output_channels_

symbolic::Expression sdfg::math::tensor::ConvNode::output_channels_

protected

Number of output channels (C_out).

◆ W_INPUT_IDX

int constexpr sdfg::math::tensor::ConvNode::W_INPUT_IDX = 2

staticconstexpr

◆ with_bias_

bool sdfg::math::tensor::ConvNode::with_bias_

protected

◆ X_INPUT_IDX

int constexpr sdfg::math::tensor::ConvNode::X_INPUT_IDX = 1

staticconstexpr

◆ Y_INPUT_IDX

int constexpr sdfg::math::tensor::ConvNode::Y_INPUT_IDX = 0

staticconstexpr

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

sdfg/include/sdfg/data_flow/library_nodes/math/tensor/conv_node.h

Classes

Public Member Functions

Static Public Member Functions

Static Public Attributes

Protected Attributes

Additional Inherited Members

Detailed Description

Input/Output Requirements

Expansion Support

Example

Constructor & Destructor Documentation

◆ ConvNode()

Member Function Documentation

◆ check_expandable()

◆ clone()

◆ expand()

◆ flop()

◆ get_blas_precision()

◆ get_out_shape()

◆ group()

◆ has_bias()

◆ kernel_iteration_count()

◆ num_output_elements()

◆ output_channels()

◆ pointer_access_type()

◆ replace() [1/2]

◆ replace() [2/2]

◆ supports_integer_types()

◆ symbols()

◆ toStr()

◆ validate()

Member Data Documentation

◆ B_INPUT_IDX

◆ group_

◆ output_channels_

◆ W_INPUT_IDX

◆ with_bias_

◆ X_INPUT_IDX

◆ Y_INPUT_IDX