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name: training-references description: "Use when planning or auditing TorchVision reference training/evaluation workflows for classification, quantization, detection, segmentation, video classification, optical flow, similarity learning, or stereo depth without launching expensive jobs." disable-model-invocation: true metadata: disco-role: operating license: BSD 3-Clause

TorchVision Training References

Use this sub-skill to turn TorchVision's official reference scripts into safe command plans, dataset-layout checks, and troubleshooting notes. The reference scripts are training baselines rather than stable package APIs; always treat generated commands as plans to review before running.

Route first

• For model constructors, weight enums, or weights.transforms() usage, route to ../models-and-weights/.
• For transform implementation details, TVTensors, masks, boxes, videos, or custom v2 pipelines, route to ../transforms-and-tv-tensors/.
• For dataset constructors, downloads, codecs, and tiny fixtures, route to ../datasets-io-utils/.
• For box utilities, NMS, ROI ops, and detection postprocessing internals, route to ../ops-and-detection/.

Safe workflow

1. Identify the task family: classification, quantization, detection, segmentation, video classification, optical flow, similarity learning, or stereo depth.
2. Read references/task-command-recipes.md for concrete command skeletons and safety labels.
3. Check references/data-layouts-and-presets.md for expected dataset layout, preset, and preprocessing assumptions.
4. Use scripts/inspect_reference_args.py --list or --task <name> to inspect known argument families without importing or running training code.
5. Read references/troubleshooting.md before advising a user to run any command that needs datasets, GPUs, distributed launch, checkpoints, or weight downloads.

Safety labels

• Safe: listing arguments, producing command plans, and reviewing flags.
• Review required: single-process evaluation on already-prepared local data, especially when it may download weights.
• Unsafe by default: full training, distributed torchrun, dataset downloads, model-url download checks, release scripts, and benchmarks.

Bundled helper

Run the helper from this sub-skill directory or provide its path explicitly:

python scripts/inspect_reference_args.py --list
python scripts/inspect_reference_args.py --task detection
python scripts/inspect_reference_args.py --task classification --format shell

The helper is a static summary adapted from the reference parsers. It does not import TorchVision, import the original scripts, read datasets, download weights, launch distributed jobs, or run training.