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name: simmim-workflows description: "Use this repo skill for Swin-Transformer SimMIM masked image modeling pretraining, fine-tuning, evaluation, mask generation, checkpoint remapping, and safe synthetic smoke checks." disable-model-invocation: true metadata: disco-role: operating license: MIT

simmim-workflows

Use this sub-skill when a task involves SimMIM in the Swin-Transformer repository: masked image modeling pretraining, fine-tuning a SimMIM-pretrained checkpoint, evaluating a SimMIM fine-tuned model, mask generation, or checkpoint remapping.

Covers

• main_simmim_pt.py pretraining command shape.
• main_simmim_ft.py fine-tuning/evaluation command shape.
• MaskGenerator, SimMIMTransform, SimMIM, and build_simmim behavior.
• SimMIM config pairs under configs/simmim/.
• Safe mask/loss CPU smoke checks.

Routes elsewhere

• Baseline supervised main.py commands: training-eval-cli.
• Generic ImageNet layouts: data-and-checkpoints.
• Swin V1/V2 constructor details: core-models.
• MoE/Tutel/fused CUDA: moe-and-acceleration.

Workflow

1. Decide if the task is pretraining, fine-tuning, or evaluation.
2. Read references/simmim-workflows.md for command shape and config pairing.
3. Read references/api-reference.md for mask/loss behavior.
4. Validate the proposed command with scripts/validate_simmim_command.py.
5. Run scripts/smoke_simmim_loss.py only for a tiny CPU synthetic check; it is not a training substitute.

Linked files

• references/simmim-workflows.md - task recipes and config pair guidance.
• references/api-reference.md - mask and SimMIM model APIs.
• references/troubleshooting.md - common mask, checkpoint, and command mistakes.
• scripts/validate_simmim_command.py - safe command validator.
• scripts/smoke_simmim_loss.py - tiny synthetic CPU loss smoke.