Table of Contents

Namespace AiDotNet.KnowledgeDistillation.Teachers

Classes

AdaptiveTeacherModel<T>

Adaptive teacher model that wraps a base teacher and provides its logits.

CurriculumTeacherModel<T>

Curriculum teacher that wraps a base teacher for curriculum learning scenarios.

DistributedTeacherModel<T>

Distributed teacher model that aggregates predictions from multiple distributed workers.

EnsembleTeacherModel<T>

Ensemble teacher model that combines predictions from multiple teacher models.

MultiModalTeacherModel<T>

Multi-modal teacher that combines multiple input modalities (vision, text, audio).

OnlineTeacherModel<T>

Online teacher model that updates its parameters during student training.

PretrainedTeacherModel<T>

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

QuantizedTeacherModel<T>

Quantized teacher model with reduced precision for efficient deployment.

SelfTeacherModel<T>

Self teacher model that uses the student's own predictions from earlier training.

TransformerTeacherModel<T>

Transformer-based teacher model that provides logits from transformer architectures.

Enums

AggregationMode

Specifies how multiple teacher outputs are combined into a single supervision signal.

CurriculumStrategy

Defines the curriculum learning strategy direction.

EnsembleAggregationMode

Defines how ensemble predictions are aggregated.

OnlineUpdateMode

Defines how an online teacher model is updated during training.