SeedVR2Prep

SeedVR2Prep prepares heavy SeedVR2 workflows by warming up caches, priming key models, and cleaning up afterward. Think of it as a one-button “get ready to render” helper for VRAM-intensive runs.

Inputs

run_warmup – Execute the warmup pass, loading and touching key models so the first real render doesn’t spike.
warmup_steps – Number of dummy steps to run during warmup. Higher values build a larger cache but take longer.
clear_after – Free caches once the main job finishes. Leave on if you’re about to switch projects.
log_only – When True, print what would happen without actually running warmup or cleanup. Useful for testing.
notes – Free-form text stored alongside the log output.

Outputs

log – Summary of warmup and cleanup actions.
status – Simple text flag (ready, skipped, cleared) for downstream branching.

Where It Fits

Drop SeedVR2Prep at the start of VRAM-heavy SeedVR2 graphs when you need stable runtimes or when the first render tends to hitch due to lazy model loading. Run it again at the end to clean up before switching to a different project or model set.

Tuning Tips

Start with a modest warmup_steps count (e.g., 5) and increase only if the first render still stutters.
Leave clear_after enabled on shared machines so other users get a clean slate.
Toggle log_only during setup to verify the node sees the right models before committing to a full warmup.

Troubleshooting

Warmup takes too long – Lower warmup_steps or limit which models participate in warmup within your workflow.
VRAM still spikes on first render – Ensure run_warmup is enabled and the node executes before the main generation block.
Cleanup skipped – Check that clear_after is toggled on and the node executes after your main render branch.

Screenshot: docs/screenshots/seedvr2_prep.png

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