SolitaryThinkerandClaude Opus 5.5
d692d1cc3b
These ports were marked pending removal in #1820. Each has a newer, maintained counterpart in the repo, and their model-specific hooks leaked into shared stages, request fields, CLI args, and loaders. Remove each model's code, configs, presets, examples, converters, tests, cookbook pages, CI planner rules, and registry entries, along with the shared-code hooks only they used: - camera kwargs (GameCraft camera_states, DreamX y_camera) in the shared denoising loop - LongCat refine branches in latent preparation, the decoding crop, the --bsa-* CLI args, its train model, and third_party/longcat_video - Z-Image cfg_normalization/cfg_truncation and GameCraft/DreamX camera/action fields in SamplingParam, ForwardBatch, and the schema - the GLM-Image vision-language loader and the TurboDiffusion rCM scheduler and SLA auto-select in the train entrypoint - the Wan definition groups that only preserved DreamX detector order Removed env vars and their legacy aliases move to DEPRECATED_VARIABLES per the env-var policy. Matrix Game 2.0 stays: the new trainer's world model scenarios depend on it. The SLA and BSA attention backends stay. The TurboDiffusion int8 kernels in fastvideo-kernel are left for a separate kernel PR. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Fastvideo New Modular Training Framework
This is the new training infrastructure for FastVideo, replacing the
monolithic per-model pipeline scripts in fastvideo/training/.
Key differences from fastvideo/training/
fastvideo/training/ (legacy) |
fastvideo/train/ (new) |
|
|---|---|---|
| Architecture | One pipeline class per model+method combo | Composable: model plugins + method classes |
| Adding a model | Write a full training pipeline from scratch | Add a model plugin under models/ |
| Adding a method | Fork an existing pipeline | Add a method class under methods/ |
| Config | Flat argparse flags | Hierarchical YAML with dotted-key overrides |
| Distributed | Manual FSDP setup per pipeline | Shared trainer handles FSDP/HSDP |
Structure
fastvideo/train/
├── models/ # Per-model plugins (wan/, hunyuan/, ...)
├── methods/ # Training methods (fine_tuning/, distribution_matching/, ...)
├── callbacks/ # Validation, grad clipping, etc.
├── entrypoint/ # CLI entry points (train.py, dcp_to_diffusers.py)
├── trainer.py # Core training loop
└── utils/ # Config parsing, dataloader, etc.
Usage
See examples/train/ for configs and launch scripts.