Class NagGpuConfig

Namespace

AiDotNet.Interfaces

Assembly

AiDotNet.dll

Configuration for Nesterov Accelerated Gradient (NAG) optimizer on GPU.

public class NagGpuConfig : IGpuOptimizerConfig

Inheritance

object

NagGpuConfig

Implements

IGpuOptimizerConfig

Inherited Members

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Remarks

NAG is a variation of momentum that looks ahead by evaluating the gradient at the "lookahead" position. This often leads to better convergence.

For Beginners: NAG improves on regular momentum by being smarter about where to look. Instead of computing the gradient at the current position, it first moves in the direction of accumulated momentum, then computes the gradient. This "lookahead" helps it slow down before overshooting.

Constructors

NagGpuConfig(float, float, float, int)

Creates a new NAG GPU configuration.

public NagGpuConfig(float learningRate, float momentum = 0.9, float weightDecay = 0, int step = 0)

Parameters

learningRate float

Learning rate for parameter updates.

momentum float

Momentum coefficient (default 0.9).

weightDecay float

Weight decay coefficient (default 0).

step int

Current optimization step.

Properties

LearningRate

Gets the learning rate for parameter updates.

public float LearningRate { get; init; }

Property Value

float

Momentum

Gets the momentum coefficient (typically 0.9).

public float Momentum { get; init; }

Property Value

float

OptimizerType

Gets the type of optimizer (SGD, Adam, AdamW, etc.).

public GpuOptimizerType OptimizerType { get; }

Property Value

GpuOptimizerType

Step

Gets the current optimization step (used for bias correction in Adam-family optimizers).

public int Step { get; init; }

Property Value

int

WeightDecay

Gets the weight decay (L2 regularization) coefficient.

public float WeightDecay { get; init; }

Property Value

float

Methods

ApplyUpdate(IDirectGpuBackend, IGpuBuffer, IGpuBuffer, GpuOptimizerState, int)

Applies the optimizer update to the given parameter buffer using its gradient.

public void ApplyUpdate(IDirectGpuBackend backend, IGpuBuffer param, IGpuBuffer gradient, GpuOptimizerState state, int size)

Parameters

backend IDirectGpuBackend

The GPU backend to execute the update.

param IGpuBuffer

Buffer containing the parameters to update (modified in-place).

gradient IGpuBuffer

Buffer containing the gradients.

state GpuOptimizerState

Optimizer state buffers (momentum, squared gradients, etc.).

size int

Number of parameters to update.

Remarks

For Beginners: This method applies the optimizer's update rule directly on the GPU. Each optimizer type (SGD, Adam, etc.) implements its own update logic using GPU kernels. The state parameter contains any auxiliary buffers needed (like velocity for SGD with momentum, or m/v buffers for Adam).

Design Note: Following the Open/Closed Principle, each optimizer config knows how to apply its own update, so adding new optimizers doesn't require modifying layer code.