- The 12 fastvideo/training/*_pipeline.py entry points load a
TrainingRunConfig from --config <yaml> plus dotted overrides (mode
finetuning or distillation) instead of TrainingArgs argparse flags.
- The training pipelines read self.resolved_config.training.<section>.<field>
and typed paths; the training_args alias, the inference_mode toggles,
and the writes to the training config are gone. Teacher and critic
models load with a with_override config and the loading_teacher_critic_model
argument; validation pipelines are built from their own resolved config
(resolve_validation_config), and the tracker receives to_dict().
- Each of the 37 training launchers has a YAML file next to it with the
values its flags held; shell variables stay as dotted overrides. Against
the 3f6893a0 TrainingArgs snapshots every value and PipelineConfig
matches, except mode/inference_mode (the stage readers saw training mode
before and after), the dropped flags without a reader, lora_alpha (now
derived from the rank by a step), and the vae_tiling and compile-kwargs
defaults.
- Validation stages read the validation pipeline's config: modules that
validation loads itself use the inference offload defaults, and the
bf16-autocast VAE decode of two distillation launchers becomes fp32.
Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_012M91wnVFmPEvJ9h39r5BH7
