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808036c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 | #!/usr/bin/env python3
"""Static and file-layout preflight for the standalone Protenix package."""
from __future__ import annotations
import argparse
import ast
import hashlib
import os
from pathlib import Path
MODEL_SHA256 = "9ea20b0aba42f2256711da1d0cd081510a4b291e64375bff6b70ced70b87a5f1"
MODEL_SIZE = 1474265486
REQUIRED_PACKAGE_FILES = [
"README.md",
"configuration.json",
"configs/inference_config.yaml",
"weight/model_v0.5.0.pt",
"examples/7r6r.json",
"examples/7r6r/msa/1/pairing.a3m",
"examples/7r6r/msa/1/non_pairing.a3m",
"models/protenix/protenix.py",
"models/openfold/primitives.py",
"scripts/runner/inference_unified.py",
"scripts/run_inference.py",
"scripts/train.py",
"scripts/finetune.py",
]
REQUIRED_DATA_FILES = [
"components.v20240608.cif",
"components.v20240608.cif.rdkit_mol.pkl",
"seq_to_pdb_index.json",
"indices/weightedPDB_indices_before_2021-09-30_wo_posebusters_resolution_below_9.csv.gz",
"indices/recentPDB_low_homology_maxtoken1536.csv",
"indices/recentPDB_low_homology_maxtoken1024_sample384_pdb_id.txt",
"indices/posebusters_indices_mainchain_interface.csv",
"mmcif_msa",
]
def sha256(path: Path) -> str:
digest = hashlib.sha256()
with path.open("rb") as f:
for chunk in iter(lambda: f.read(1024 * 1024), b""):
digest.update(chunk)
return digest.hexdigest()
def module_to_path(model_root: Path, module: str) -> Path | None:
if not module.startswith(("configs.", "models.", "scripts.")):
return None
rel = Path(*module.split("."))
package_init = model_root / rel / "__init__.py"
module_file = model_root / rel.with_suffix(".py")
if package_init.exists():
return package_init
if module_file.exists():
return module_file
return module_file
def check_local_imports(model_root: Path) -> list[str]:
missing: list[str] = []
scan_roots = ["configs", "models", "scripts"]
py_files = []
for scan_root in scan_roots:
py_files.extend((model_root / scan_root).rglob("*.py"))
for py_file in sorted(py_files):
tree = ast.parse(py_file.read_text(encoding="utf-8"), filename=str(py_file))
for node in ast.walk(tree):
module = None
if isinstance(node, ast.Import):
for alias in node.names:
module = alias.name
if module == "modules" or module.startswith("modules."):
missing.append(f"{py_file.relative_to(model_root)} imports removed package {module}")
continue
if module == "config" or module.startswith("config."):
missing.append(f"{py_file.relative_to(model_root)} imports renamed package {module}")
continue
target = module_to_path(model_root, module)
if target is not None and not target.exists():
missing.append(f"{py_file.relative_to(model_root)} imports missing {module}")
elif isinstance(node, ast.ImportFrom) and node.module:
module = node.module
if node.level == 0:
if module == "modules" or module.startswith("modules."):
missing.append(f"{py_file.relative_to(model_root)} imports removed package {module}")
continue
if module == "config" or module.startswith("config."):
missing.append(f"{py_file.relative_to(model_root)} imports renamed package {module}")
continue
target = module_to_path(model_root, module)
if target is not None and not target.exists():
missing.append(f"{py_file.relative_to(model_root)} imports missing {module}")
return missing
def main() -> int:
parser = argparse.ArgumentParser(description="Protenix standalone package preflight")
parser.add_argument("--model-root", default=".", help="Package root")
parser.add_argument(
"--data-root",
default=os.environ.get("DATA_ROOT_DIR", "../bio_protenix_dataset"),
help="Prepared Protenix dataset root",
)
parser.add_argument("--strict-weights", action="store_true", help="Validate weight size and LFS pointer state")
parser.add_argument("--full-checksum", action="store_true", help="Compute SHA256 for the 1.4GB model file")
parser.add_argument("--strict-imports", action="store_true", help="Statically verify local imports and removed modules.* imports")
parser.add_argument("--strict-data", action="store_true", help="Require the external dataset files")
args = parser.parse_args()
model_root = Path(args.model_root).resolve()
data_root = Path(args.data_root).resolve()
errors: list[str] = []
for rel in REQUIRED_PACKAGE_FILES:
path = model_root / rel
if not path.exists():
errors.append(f"Missing package file: {path}")
config = model_root / "configs/inference_config.yaml"
if config.exists():
text = config.read_text(encoding="utf-8")
required_fragments = [
'input_json_path: "./examples/7r6r.json"',
'load_checkpoint_path: "./weight/model_v0.5.0.pt"',
'ccd_components_file: "${DATA_ROOT_DIR}/components.v20240608.cif"',
'ccd_components_rdkit_mol_file: "${DATA_ROOT_DIR}/components.v20240608.cif.rdkit_mol.pkl"',
'pdb_mmseqs_dir: "${DATA_ROOT_DIR}/mmcif_msa"',
"${oc.env:PWD}/examples/7r6r/msa/1",
]
for fragment in required_fragments:
if fragment not in text:
errors.append(f"Config missing fragment: {fragment}")
checkpoint = model_root / "weight/model_v0.5.0.pt"
if args.strict_weights and checkpoint.exists():
size = checkpoint.stat().st_size
if size != MODEL_SIZE:
errors.append(f"Weight size mismatch: {checkpoint} size={size} expected={MODEL_SIZE}")
with checkpoint.open("rb") as f:
prefix = f.read(64)
if prefix.startswith(b"version https://git-lfs.github.com/spec"):
errors.append(f"Weight is a Git LFS pointer, not the real checkpoint: {checkpoint}")
if args.full_checksum:
digest = sha256(checkpoint)
if digest != MODEL_SHA256:
errors.append(f"Weight SHA256 mismatch: {checkpoint} sha256={digest}")
if args.strict_data:
for rel in REQUIRED_DATA_FILES:
path = data_root / rel
if not path.exists():
errors.append(f"Missing dataset file or directory: {path}")
if args.strict_imports:
errors.extend(check_local_imports(model_root))
residue_patterns = [
"from modules.",
"import modules.",
"modules.models.",
"modules.runner.",
"/public/share/sugonhpcapp01/onestore/" + "onemodels",
"/public/home/liuyx19/" + "one" + "science",
"checkpoints/" + "model_v0.5.0.pt",
"infer_" + "datasets/" + "7r6r",
"url" + "retrieve",
]
for path in sorted(model_root.rglob("*")):
if not path.is_file() or "weight" in path.parts:
continue
if "modules" in path.relative_to(model_root).parts:
continue
if path.relative_to(model_root).as_posix() == "scripts/preflight.py":
continue
try:
text = path.read_text(encoding="utf-8")
except UnicodeDecodeError:
continue
for pattern in residue_patterns:
if pattern in text:
errors.append(f"Residual pattern {pattern!r} in {path.relative_to(model_root)}")
print(f"model_root={model_root}")
print(f"data_root={data_root}")
if errors:
print("Preflight failed:")
for error in errors:
print(f"- {error}")
return 1
print("Preflight passed.")
return 0
if __name__ == "__main__":
raise SystemExit(main())
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