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reproduce.py

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+#!/usr/bin/env python3
+"""Reproduce ExecuTorch .pte trigger-specific output manipulation."""
+
+from __future__ import annotations
+
+import argparse
+import json
+from pathlib import Path
+
+import torch
+from executorch.runtime import Runtime
+
+
+def run_pte(path: Path, rows: list[list[float]]) -> list[dict]:
+    runtime = Runtime.get()
+    program = runtime.load_program(path)
+    forward = program.load_method("forward")
+    if forward is None:
+        raise RuntimeError("forward method missing")
+    x = torch.tensor(rows, dtype=torch.float32)
+    logits = forward.execute((x,))[0]
+    return [
+        {
+            "input": row,
+            "logits": [float(v) for v in logits[i].reshape(-1)],
+            "class": int(torch.argmax(logits[i]).item()),
+        }
+        for i, row in enumerate(rows)
+    ]
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser()
+    parser.add_argument("--control", default="control_executorch_classifier.pte")
+    parser.add_argument("--malicious", default="malicious_executorch_trigger.pte")
+    args = parser.parse_args()
+
+    rows = [[0.0, 0.0], [1.0, 2.0], [10.0, -10.0], [1337.0, -1337.0]]
+    control = run_pte(Path(args.control), rows)
+    malicious = run_pte(Path(args.malicious), rows)
+    result = {
+        "format": "ExecuTorch .pte",
+        "loader": "Runtime.get().load_program(...).load_method('forward').execute(...)",
+        "torch_version": torch.__version__,
+        "rows": rows,
+        "control": control,
+        "malicious": malicious,
+        "benign_classes_match": [
+            c["class"] == m["class"] for c, m in zip(control[:-1], malicious[:-1])
+        ],
+        "trigger_flips": control[-1]["class"] == 1 and malicious[-1]["class"] == 0,
+    }
+    print(json.dumps(result, indent=2, sort_keys=True))
+    if not all(result["benign_classes_match"]) or not result["trigger_flips"]:
+        raise SystemExit(2)
+
+
+if __name__ == "__main__":
+    main()