计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
training-workflows【效率与协作】Route Pyramid-Flow Causal VAE training, DiT fine-tuning, distributed launchers, and launch-time prerequisites.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill when the task is about Pyramid-Flow training launchers or preflight checks, not inference demos or low-level model internals.
train/train_pyramid_flow.py and scripts/train_pyramid_flow.sh.train/train_pyramid_flow.py and scripts/train_pyramid_flow_without_ar.sh.train/train_video_vae.py and scripts/train_causal_video_vae.sh.NUM_FRAMES, VIDEO_SYNC_GROUP, CONTEXT_SIZE, and per-device batch-size invariants.../generation-inference/SKILL.md.../data-preparation/SKILL.md.../core-components/SKILL.md.scripts/build_training_commands.py prints validated torchrun command shapes adapted from the three training shell launchers. It never starts a training run.scripts/check_training_prereqs.py validates command-builder invariants, CUDA/distributed visibility, optional source syntax, and optional annotation samples before launch. It never launches torchrun.For any expensive run, build or check the command first, fix all preflight failures, then copy the printed command into the actual training environment.