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データ・研究 · SKILL.md

minivit

minivit

Routes MiniViT Mini-DeiT and Mini-Swin compression, distillation, command-construction, dataset-layout, and optional RPE/custom-op workflows.

Independent GitHub snapshot · Automated classification · Original documentation governs

スキルの説明

GitHub

name: minivit description: "Routes MiniViT Mini-DeiT and Mini-Swin compression, distillation, command-construction, dataset-layout, and optional RPE/custom-op workflows." disable-model-invocation: true metadata: disco-role: operating license: MIT

MiniViT

Use this sub-skill when the user asks about MiniViT workflows for Mini-DeiT or Mini-Swin: model/variant selection, ImageNet layout validation, MiniViT weight multiplexing, distillation command construction, evaluation command construction, 224-to-384 Mini-Swin finetuning, or optional RPE/custom-op status.

Route first

User taskRead/run
Build a Mini-DeiT or Mini-Swin command templatescripts/build_minivit_command.py, then references/command-reference.md
Choose a model variant, YAML config, or checkpoint familyreferences/api-reference.md and references/command-reference.md
Validate ImageNet folders or tar archivesreferences/workflows.md and root scripts/check_dataset_layout.py
Diagnose teacher checkpoints, rpe_ops, Mini-Swin configs, Apex, or layer-list mismatchesreferences/troubleshooting.md

Safe operating pattern

  1. Confirm whether the user means Mini-DeiT or Mini-Swin. Generic iRPE integration belongs to the irpe sub-skill; TinyViT and EfficientViT belong to their own sub-skills.

  2. Validate the ImageNet root before constructing expensive launchers:

    python ../../scripts/check_dataset_layout.py --root /path/to/ImageNet --kind imagenet1k
    
  3. Generate, review, and edit a command template instead of improvising distributed flags:

    python scripts/build_minivit_command.py --workflow mini-swin-train --variant tiny --data-path /path/to/ImageNet --output /path/to/output --teacher /path/to/teacher.pth --amp-opt-level O0
    
  4. Treat printed commands as templates. The helper never starts distributed training, downloads data, or writes checkpoints; commands printed by the helper may do those things if the user later runs them.

Native safe checks

  • Mini-DeiT parser help is safe in an environment with timm installed.
  • mini_deit_tiny_patch16_224 CPU instantiation is safe and was verified in the inspection environment.
  • Mini-Swin config parsing with an explicit --cfg is safe; full Mini-Swin training/evaluation requires CUDA, DistributedDataParallel, and NCCL setup.

Boundaries

  • Covered here: Mini-DeiT and Mini-Swin compression/distillation/evaluation command construction and troubleshooting.
  • Not covered here: generic iRPE API integration, TinyViT sparse-logit workflows, EfficientViT classification/downstream workflows, or Cream/AutoFormer NAS search.
  • Keep runtime guidance self-contained: use bundled references/helpers rather than source-repo documentation links.
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