File size: 2,204 Bytes
9c98083 | 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 | """Inspect a LoRA .safetensors file: embedded training metadata + inferred
rank/target modules from tensor shapes. Read-only, no GPU/torch needed --
just parses the safetensors header, so it's fast and safe to run on any
LoRA file (including ones you didn't train yourself).
Usage:
python_embeded\\python.exe dataset_builder\\inspect_lora.py path\\to\\lora.safetensors
"""
import argparse
import json
import re
from collections import Counter
from safetensors import safe_open
def parse_args():
p = argparse.ArgumentParser(description="Inspect a LoRA safetensors file's metadata")
p.add_argument("lora_path")
return p.parse_args()
def infer_rank(keys, shapes):
for k in keys:
if k.endswith("lora_A.weight") or k.endswith("lora_down.weight"):
return shapes[k][0]
return None
def summarize_target_modules(keys):
"""Collapses per-block keys (blocks.0, blocks.1, ...) into module families
so you can see what parts of the model were trained without a 800-line dump."""
families = Counter()
for k in keys:
base = re.sub(r"\.(lora_A|lora_B|lora_down|lora_up|alpha)(\.weight)?$", "", k)
base = re.sub(r"\.\d+\.", ".N.", base)
families[base] += 1
return families
def main():
args = parse_args()
with safe_open(args.lora_path, framework="pt") as f:
meta = f.metadata() or {}
keys = list(f.keys())
shapes = {k: f.get_slice(k).get_shape() for k in keys}
print(f"=== {args.lora_path} ===")
print(f"Tensor count: {len(keys)}")
print(f"Inferred rank (lora_A/lora_down first dim): {infer_rank(keys, shapes)}")
print("\n--- Embedded metadata ---")
if not meta:
print("(none)")
for k, v in meta.items():
try:
parsed = json.loads(v)
print(f"{k}:")
print(json.dumps(parsed, indent=2, ensure_ascii=False)[:3000])
except (json.JSONDecodeError, TypeError):
print(f"{k}: {v}")
print("\n--- Target module families (per-block keys collapsed) ---")
for base, count in summarize_target_modules(keys).most_common(30):
print(f" {base} x{count}")
if __name__ == "__main__":
main()
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