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name: core-models description: "Use this repo skill for Swin Transformer model construction, architecture inspection, tensor-shape checks, and CPU model smoke tests across Swin V1, Swin V2, Swin-MLP, and SimMIM encoder variants." disable-model-invocation: true metadata: disco-role: operating license: MIT

core-models

Use this sub-skill when the task is about the model classes themselves: which constructor to use, how build_model dispatches on MODEL.TYPE, which config fields control architecture shape, how window partitioning works, or how to run a small CPU smoke check without touching the training loops.

What this sub-skill covers

• build_model(config, is_pretrain=False) dispatch for swin, swinv2, swin_moe, and swin_mlp.
• SwinTransformer, SwinTransformerV2, and SwinMLP signatures and the config fields they read.
• SimMIM encoder construction through models/simmim.py when the question is about the encoder object or a tiny reconstruction smoke.
• Window helper behavior: partition/reverse shapes, shifted windows, and why image size and window size must be compatible.
• CPU-only sanity checks: instantiate a small model, count parameters, and run a minimal forward pass.

What it does not cover

• ImageNet folder/zip/22K data-layout problems: use data-and-checkpoints.
• Training, fine-tuning, evaluation, throughput, DDP, or AMP command composition: use training-eval-cli.
• SimMIM end-to-end scripts and checkpoint remapping details: use simmim-workflows.
• MoE/Tutel/Apex/fused CUDA questions: use moe-and-acceleration.

Typical user triggers

• "Which config should I use for SwinV2-Tiny?"
• "What does MODEL.TYPE need for Swin-MLP?"
• "Why does my image/window size break the model constructor?"
• "How can I build a tiny CPU smoke test for build_model?"
• "What is the difference between Swin V1 and Swin V2 position bias behavior?"

Core workflow

1. Read the config family map in references/model-construction.md.
2. Confirm the model family from MODEL.TYPE and the config file path.
3. Check the relevant constructor signature in references/api-reference.md.
4. If the request is about safe inspection, run scripts/smoke_model_build.py with a repo checkout and a small config override.
5. If the request is about a constructor error, read references/troubleshooting.md for the shape mismatch or optional-backend warning.

Safe checks

• Building a tiny CPU model is safe when DATA.IMG_SIZE, MODEL.*.WINDOW_SIZE, and the stage depths are reduced consistently.
• The helper script does not download weights or start distributed training.
• Optional fused window-process warnings are expected when the CUDA extension is missing; they are not baseline failures.

Related references and scripts

• Read references/api-reference.md for verified signatures and the key architecture fields.
• Read references/model-construction.md when choosing a config family or reducing a config for smoke tests.
• Read references/troubleshooting.md for common constructor and shape errors.
• Run scripts/smoke_model_build.py when you want a tiny CPU construction check.