| |
| from __future__ import annotations |
|
|
| import argparse |
| import json |
| import os |
|
|
| os.environ.setdefault("TRANSFORMERS_NO_TF", "1") |
| os.environ.setdefault("TRANSFORMERS_NO_FLAX", "1") |
| os.environ.setdefault("TRANSFORMERS_NO_TORCHVISION", "1") |
| os.environ["USE_TF"] = "0" |
| os.environ["USE_FLAX"] = "0" |
| os.environ["USE_TORCH"] = "1" |
|
|
| from common import decode_span_matrix, load_onnx_session, run_onnx_span, sigmoid_np |
|
|
|
|
| def replacement(label: str) -> str: |
| return f"[PII:{label}]" |
|
|
|
|
| def mask_text(text: str, spans: list[dict]) -> str: |
| out = text |
| for span in sorted(spans, key=lambda item: (item["start"], item["end"]), reverse=True): |
| out = out[: span["start"]] + replacement(span["label"]) + out[span["end"] :] |
| return out |
|
|
|
|
| def predict(text: str, session, tokenizer, config, min_score: float): |
| encoded = tokenizer(text, return_offsets_mapping=True, return_tensors="np", truncation=True) |
| offsets = [tuple(item) for item in encoded["offset_mapping"][0].tolist()] |
| span_logits = run_onnx_span(session, encoded) |
| span_scores = sigmoid_np(span_logits[0]) |
| spans = decode_span_matrix(text, offsets, span_scores, config, min_score) |
| for span in spans: |
| span["replacement"] = replacement(span["label"]) |
| return spans |
|
|
|
|
| def main() -> None: |
| parser = argparse.ArgumentParser() |
| parser.add_argument("--model", required=True) |
| parser.add_argument("--text", required=True) |
| parser.add_argument("--min-score", type=float, default=0.5) |
| parser.add_argument("--json", action="store_true") |
| args = parser.parse_args() |
|
|
| session, tokenizer, config = load_onnx_session(args.model, onnx_file="model_quantized.onnx", onnx_subfolder="onnx") |
| spans = predict(args.text, session, tokenizer, config, args.min_score) |
| result = { |
| "model": args.model, |
| "backend": "onnx_global_pointer_q8", |
| "min_score": args.min_score, |
| "spans": spans, |
| "masked_text": mask_text(args.text, spans), |
| } |
| if args.json: |
| print(json.dumps(result, indent=2, ensure_ascii=False)) |
| else: |
| print(result["masked_text"]) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
