File size: 3,197 Bytes
aa988a7 | 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 | from __future__ import annotations
import argparse
import ast
import json
import re
import sys
from collections import Counter
from pathlib import Path
_METRICS_DIR = Path(__file__).resolve().parent
if str(_METRICS_DIR) not in sys.path:
sys.path.insert(0, str(_METRICS_DIR))
from broken_code_generation import EVAL_FILE, FILE_CODE, FILE_JSON_VALIDITY, MODEL_ID # noqa: E402
from report_io import metrics_path, write_report # noqa: E402
def parse_args() -> argparse.Namespace:
parser = argparse.ArgumentParser(description=f"Code metrics for {MODEL_ID} only.")
parser.add_argument(
"--from-generation-report",
type=Path,
default=metrics_path(FILE_JSON_VALIDITY),
)
parser.add_argument("--output", type=Path, default=None)
return parser.parse_args()
def normalize_code(code: str) -> str:
return code.replace("\\n", "\n").replace('\\"', '"')
def is_valid_python(code: str) -> bool:
try:
ast.parse(normalize_code(code))
return True
except SyntaxError:
return False
def code_tokens(code: str) -> Counter:
return Counter(re.findall(r"[A-Za-z_][A-Za-z0-9_]*|\d+|[^\s]", code))
def code_token_f1(reference: str, hypothesis: str) -> float:
ref, hyp = code_tokens(reference), code_tokens(hypothesis)
if not ref and not hyp:
return 1.0
if not ref or not hyp:
return 0.0
overlap = sum((ref & hyp).values())
precision = overlap / sum(hyp.values())
recall = overlap / sum(ref.values())
if precision + recall == 0:
return 0.0
return 2 * precision * recall / (precision + recall)
def main() -> None:
args = parse_args()
gen_path = args.from_generation_report
if not gen_path.exists():
raise FileNotFoundError(f"Run 02_json_validity.py first. Missing: {gen_path}")
references = json.loads(EVAL_FILE.read_text(encoding="utf-8"))
gen_report = json.loads(gen_path.read_text(encoding="utf-8"))
if gen_report.get("model") != MODEL_ID:
raise ValueError(f"Report is not for {MODEL_ID}: {gen_report.get('model')}")
syntax_ok = 0
code_f1_scores: list[float] = []
total = len(gen_report.get("results", []))
for ref, row in zip(references, gen_report.get("results", [])):
if row.get("status") != "ok":
continue
gen_code = str(row["generated"].get("broken_code", ""))
if is_valid_python(gen_code):
syntax_ok += 1
code_f1_scores.append(code_token_f1(str(ref.get("broken_code", "")), gen_code))
n = max(total, 1)
f1_mean = round(sum(code_f1_scores) / max(len(code_f1_scores), 1), 4) if code_f1_scores else None
report = {
"metric_group": "code_metrics",
"model": MODEL_ID,
"source_report": str(gen_path),
"metrics": {
"broken_code_syntax_valid_rate": round(syntax_ok / n, 4),
"code_token_f1_broken_code": f1_mean,
"codebleu_broken_code": f1_mean,
},
}
write_report(args.output or metrics_path(FILE_CODE), report)
if __name__ == "__main__":
main()
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