Class PretrainedTeacherModel<T>

Namespace

AiDotNet.KnowledgeDistillation.Teachers

Assembly

AiDotNet.dll

Pretrained teacher model from external source (e.g., ImageNet, BERT).

public class PretrainedTeacherModel<T> : TeacherModelBase<Vector<T>, Vector<T>, T>, ITeacherModel<Vector<T>, Vector<T>>, IJitCompilable<T>

Type Parameters

T

Inheritance

object

TeacherModelBase<Vector<T>, Vector<T>, T>

PretrainedTeacherModel<T>

Implements

ITeacherModel<Vector<T>, Vector<T>>

IJitCompilable<T>

Inherited Members

TeacherModelBase<Vector<T>, Vector<T>, T>.NumOps

TeacherModelBase<Vector<T>, Vector<T>, T>.OutputDimension

TeacherModelBase<Vector<T>, Vector<T>, T>.GetLogits(Vector<T>)

TeacherModelBase<Vector<T>, Vector<T>, T>.SupportsJitCompilation

TeacherModelBase<Vector<T>, Vector<T>, T>.ExportComputationGraph(List<ComputationNode<T>>)

TeacherModelBase<Vector<T>, Vector<T>, T>.CheckWrappedModelJitSupport(ITeacherModel<Vector<T>, Vector<T>>)

TeacherModelBase<Vector<T>, Vector<T>, T>.DelegateJitExport(ITeacherModel<Vector<T>, Vector<T>>, List<ComputationNode<T>>, string)

TeacherModelBase<Vector<T>, Vector<T>, T>.ThrowJitNotSupported(string, string)

TeacherModelBase<Vector<T>, Vector<T>, T>.ValidateInput(Vector<T>, string)

TeacherModelBase<Vector<T>, Vector<T>, T>.Softmax(Vector<T>, double)

TeacherModelBase<Vector<T>, Vector<T>, T>.ApplyTemperatureSoftmax(Vector<T>, double)

object.Equals(object)

object.Equals(object, object)

object.GetHashCode()

object.GetType()

object.MemberwiseClone()

object.ReferenceEquals(object, object)

object.ToString()

Remarks

Architecture Note: This class supports two construction modes:

• Function delegate mode: Uses a Func<> for forward pass (not JIT-compilable)
• IJitCompilable mode: Uses a JIT-compilable model for forward pass (JIT-compilable)

Constructors

PretrainedTeacherModel(IJitCompilable<T>, int, int)

Initializes a new instance using a JIT-compilable model.

public PretrainedTeacherModel(IJitCompilable<T> jitCompilableModel, int inputDimension, int outputDimension)

Parameters

jitCompilableModel IJitCompilable<T>

A JIT-compilable model for forward pass.

inputDimension int

The number of input dimensions.

outputDimension int

The number of output dimensions.

Remarks

JIT Support: This constructor enables JIT compilation when the underlying model supports it. Use this constructor for optimal inference performance.

PretrainedTeacherModel(Func<Vector<T>, Vector<T>>, int, int)

Initializes a new instance using a function delegate (not JIT-compilable).

public PretrainedTeacherModel(Func<Vector<T>, Vector<T>> pretrainedForward, int inputDimension, int outputDimension)

Parameters

pretrainedForward Func<Vector<T>, Vector<T>>

Function that performs forward pass.

inputDimension int

The number of input dimensions.

outputDimension int

The number of output dimensions.

Properties

OutputDimension

Gets the number of output dimensions (e.g., number of classes for classification).

public override int OutputDimension { get; }

Property Value

int

Remarks

For Implementers: Return the size of the output vector. For example, a 10-class classifier should return 10.

SupportsJitCompilation

Gets whether this teacher supports JIT compilation.

public override bool SupportsJitCompilation { get; }

Property Value

bool

true if constructed with a JIT-compilable model that supports JIT; otherwise, false.

Methods

ExportComputationGraph(List<ComputationNode<T>>)

Exports the computation graph for JIT compilation.

public override ComputationNode<T> ExportComputationGraph(List<ComputationNode<T>> inputNodes)

Parameters

inputNodes List<ComputationNode<T>>

List to populate with input computation nodes.

Returns

ComputationNode<T>

The output computation node.

Exceptions

NotSupportedException

Thrown when constructed with a function delegate instead of a JIT-compilable model.

GetLogits(Vector<T>)

Gets logits from the pretrained model.

public override Vector<T> GetLogits(Vector<T> input)

Parameters

input Vector<T>

Returns

Vector<T>

Remarks

Architecture Note: Returns raw logits. Temperature scaling and softmax are handled by distillation strategies, not by the teacher model.