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name: super-resolution-training description: "Route sr.py super-resolution training, validation, resume, and debug workflows." disable-model-invocation: true metadata: disco-role: operating license: Apache 2.0

Super-Resolution Training

Use this sub-skill for sr.py super-resolution runs when the user wants to train, resume, validate, or debug a conditional SR3/DDPM workflow.

Start here

1. Read references/workflows.md to map the request to the right phase, config family, checkpoint rule, and output layout.
2. Read references/troubleshooting.md for dataset, checkpoint, CUDA, W&B, and result-path failures.
3. Use scripts/build_sr_command.py to validate a comment-bearing config and print a shell command. The helper only prints commands; it never launches training.

Covered requests

• new SR3 or DDPM training runs
• resume training from a checkpoint prefix
• validation-only runs from a trained checkpoint
• debug-sized runs with the repository runtime shrinkage flag
• GPU selection and optional W&B enablement

Do not use this sub-skill for

• dataset preparation
• unconditional generation
• pretrained inference
• metric-only evaluation