fastvideo.training.wan_i2v_distillation_pipeline

Module Contents

Classes

WanI2VDistillationPipeline

A distillation pipeline for Wan that uses a single transformer model. The main transformer serves as the student model, and copies are made for teacher and critic.

Functions

main

Data

logger
vsa_available

API

class fastvideo.training.wan_i2v_distillation_pipeline.WanI2VDistillationPipeline(model_path: str, fastvideo_args: fastvideo.fastvideo_args.TrainingArgs, required_config_modules: list[str] | None = None, loaded_modules: dict[str, torch.nn.Module] | None = None)

Bases: fastvideo.training.distillation_pipeline.DistillationPipeline

A distillation pipeline for Wan that uses a single transformer model. The main transformer serves as the student model, and copies are made for teacher and critic.

Initialization

Initialize the pipeline. After init, the pipeline should be ready to use. The pipeline should be stateless and not hold any batch state.

create_training_stages(training_args: fastvideo.fastvideo_args.TrainingArgs)

May be used in future refactors.

initialize_pipeline(fastvideo_args: fastvideo.fastvideo_args.FastVideoArgs)

Initialize Wan-specific scheduler.

initialize_validation_pipeline(training_args: fastvideo.fastvideo_args.TrainingArgs)

set_schemas()

fastvideo.training.wan_i2v_distillation_pipeline.logger

‘init_logger(…)’

fastvideo.training.wan_i2v_distillation_pipeline.main(args) → None

fastvideo.training.wan_i2v_distillation_pipeline.vsa_available

‘is_vsa_available(…)’