executing-plans
executing-plans
Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available
training-workflowsRoute Pyramid-Flow Causal VAE training, DiT fine-tuning, distributed launchers, and launch-time prerequisites.
Independent GitHub snapshot · Automated classification · Original documentation governs
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.