| #!/usr/bin/env bash |
| |
| |
| |
| set -euo pipefail |
| VARIANT=$1; MODEL_ID=$2 |
| COMMIT=7c724d9d7d19190e9bd33fe62fb656f1df87cd8e |
| mkdir -p third_party/uce && cd third_party/uce |
| [ -f uce_sd_erase.py ] || curl -sfLO "https://raw.githubusercontent.com/rohitgandikota/unified-concept-editing/$COMMIT/trainscripts/uce_sd_erase.py" |
| cd ../.. |
| NEIGHBOURS="Claude Monet;Pablo Picasso;Rembrandt;Andy Warhol;Caravaggio;Paul Cezanne;Paul Gauguin" |
| OUT=runs/edits/c2-uce-$VARIANT-vangogh |
| python third_party/uce/uce_sd_erase.py --model_id "$MODEL_ID" --edit_concepts "Van Gogh" --concept_type art \ |
| --save_dir $OUT/raw --exp_name uce-default |
| python third_party/uce/uce_sd_erase.py --model_id "$MODEL_ID" --edit_concepts "Van Gogh" --concept_type art \ |
| --preserve_concepts "$NEIGHBOURS" --save_dir $OUT/raw --exp_name uce-preserve |
| for SCALE in 2 4 8; do |
| python third_party/uce/uce_sd_erase.py --model_id "$MODEL_ID" --edit_concepts "Van Gogh" --concept_type art \ |
| --preserve_concepts "$NEIGHBOURS" --erase_scale $SCALE --save_dir $OUT/raw --exp_name uce-preserve-x$SCALE |
| done |
| python - "$OUT" <<'PY' |
| import json, sys |
| from pathlib import Path |
| from safetensors.torch import load_file, save_file |
| from uvw.provenance import tensor_digest |
| out = Path(sys.argv[1]) |
| for f in sorted((out / "raw").glob("*.safetensors")): |
| t = {f"unet.{k}": v.contiguous() for k, v in load_file(str(f)).items()} |
| d = out / "candidates" / f.stem |
| d.mkdir(parents=True, exist_ok=True) |
| save_file(t, str(d / "edited_tensors.safetensors")) |
| (d / "meta.json").write_text(json.dumps({"name": f.stem, "condition": "C2", "method": "UCE (official, unmodified)", |
| "commit": "7c724d9d7d19190e9bd33fe62fb656f1df87cd8e", |
| "tensors": {k: tensor_digest(v) for k, v in t.items()}})) |
| print(f.stem, len(t), "tensors") |
| PY |
|
|
