TorchDNN2Level Class Reference

A class that implements a 2-level deep neural network using PyTorch, inheriting from MLFunction. More...

#include <functions.h>

Inheritance diagram for TorchDNN2Level:

Public Member Functions
	TorchDNN2Level (float **weights, float **bias, std::vector< int > dimensions)
	Constructor that initializes the neural network with weights and biases.
void	apply (const SelectivityVector &rows, std::vector< VectorPtr > &args, const TypePtr &type, exec::EvalCtx &context, VectorPtr &output) const override
	Applies the 2-level neural network to the input array.
float *	getTensor () const override
	Returns the tensor associated with this function.
float **	getWeights () const
	Returns the weights of the neural network.
float **	getBias () const
	Returns the biases of the neural network.
std::string	getFuncName ()
	Returns the name of the function.
CostEstimate	getCost (std::vector< int > inputDims)
	Estimates the computational cost of applying the neural network.
Public Member Functions inherited from MLFunction
virtual	~MLFunction ()=default
	Virtual destructor.
virtual std::vector< int >	getDims ()
	Returns the dimensions of the function.
virtual int	getNumDims ()
	Returns the number of dimensions of the function.

Static Public Member Functions
static std::vector< std::shared_ptr< exec::FunctionSignature > >	signatures ()
	Returns the function signatures supported by this class.
static std::string	getName ()
	Static method to return the name of the function.

Additional Inherited Members
Protected Member Functions inherited from MLFunction
double	getWeightedCost (std::string name, float cost)
	Calculates the weighted cost of the function.
std::vector< double >	getCoefficientVector (std::string name)
	Retrieves the cost coefficients for the function.
Protected Attributes inherited from MLFunction
std::vector< int >	dims
	Dimensions of the function.

Detailed Description

A class that implements a 2-level deep neural network using PyTorch, inheriting from MLFunction.

This class provides functionality to apply a 2-level dense neural network with ReLU activation and softmax output.

Constructor & Destructor Documentation

TorchDNN2Level()

TorchDNN2Level::TorchDNN2Level ( float ** weights, float ** bias, std::vector< int > dimensions )

inline

Constructor that initializes the neural network with weights and biases.

Parameters

weights	A pointer to an array of pointers to weight matrices.
bias	A pointer to an array of pointers to bias vectors.
dimensions	A vector containing the dimensions of the neural network layers.

Member Function Documentation

apply()

void TorchDNN2Level::apply ( const SelectivityVector & rows, std::vector< VectorPtr > & args, const TypePtr & type, exec::EvalCtx & context, VectorPtr & output ) const

inlineoverride

Applies the 2-level neural network to the input array.

This method processes the input array, applies the neural network, and stores the result in the output vector.

Parameters

rows	A SelectivityVector specifying the rows to process.
args	A vector of input arguments (e.g., the input array).
type	The type of the output vector.
context	The execution context.
output	The output vector where the result will be stored.

getBias()

float ** TorchDNN2Level::getBias ( ) const

inline

Returns the biases of the neural network.

Returns

A pointer to an array of pointers to bias vectors.

getCost()

CostEstimate TorchDNN2Level::getCost ( std::vector< int > inputDims )

inlinevirtual

Estimates the computational cost of applying the neural network.

Parameters

inputDims

A vector containing the dimensions of the input.

Returns

A CostEstimate object representing the estimated cost.

Reimplemented from MLFunction.

getFuncName()

std::string TorchDNN2Level::getFuncName ( )

inlinevirtual

Returns the name of the function.

Returns

The name of the function as a string.

Reimplemented from MLFunction.

getName()

static std::string TorchDNN2Level::getName ( )

inlinestatic

Static method to return the name of the function.

Returns

The name of the function as a string ("torch_dnn").

getTensor()

float * TorchDNN2Level::getTensor ( ) const

inlineoverridevirtual

Returns the tensor associated with this function.

Returns

A pointer to an empty float array (no weights for TorchDNN2Level).

Implements MLFunction.

getWeights()

float ** TorchDNN2Level::getWeights ( ) const

inline

Returns the weights of the neural network.

Returns

A pointer to an array of pointers to weight matrices.

signatures()

static std::vector< std::shared_ptr< exec::FunctionSignature > > TorchDNN2Level::signatures ( )

inlinestatic

Returns the function signatures supported by this class.

Returns

A vector of shared pointers to FunctionSignature objects.

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

• functions.h