计划执行与检查节点
executing-plans
按既定实施计划完成工作,保持过程检查和反馈。
model-internals【效率与协作】Explain and verify the photo2cartoon generator, discriminator, normalization layers, face-ID feature path, tensor utilities, and checkpoint structure.
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Use this sub-skill for the model core only: architecture, forward signatures, normalization layers, checkpoint contents, and safe synthetic verification.
UgatitSadalinHourglass, losses, optimizer setup, checkpoint keys, and save/load behavior.FaceFeatures, MobileFaceNet cropping, 112×112 embeddings, and cosine-distance loss.F.upsample, device mismatch, and missing face-ID assets.../portrait-inference/../preprocessing/../data-and-training/ResnetGenerator, Discriminator, HourGlass, HourGlassBlock, ResnetBlock, ResnetSoftAdaLINBlock, SoftAdaLIN, adaLIN, and LIN(out, cam_logit, heatmap)MobileFaceNet(512)python scripts/model_forward_smoke.py --help
python scripts/model_forward_smoke.py --repo-root /path/to/photo2cartoon
python scripts/model_forward_smoke.py --repo-root /path/to/photo2cartoon --checkpoint /path/to/checkpoint.pt --face-model /path/to/model_mobilefacenet.pth