Track and verify the validated QNN context binary

README.md

@@ -198,6 +198,12 @@ Complete provenance and linked-graph validation are stored in:
 
 `reports/qualcomm_qnn_v0_1.json`
 
+The exact linked multi-graph QNN context binary is tracked at
+`artifacts/qualcomm_ai_hub/current_model/edgegenbench_multigraph.bin`. The
+portfolio acceptance builder verifies its committed Git-blob SHA-256 and size
+against the Qualcomm report, so CI fails closed if the deployment artifact is
+missing or altered.
+
 The authenticated current-model run is reproducible with:
 
 ```bash

docs/qualcomm_ai_hub_qnn.md

@@ -209,6 +209,13 @@ The complete machine-readable result is stored in:
 
 `reports/qualcomm_qnn_v0_1.json`
 
+The linked QNN context binary used by that report is stored in:
+
+`artifacts/qualcomm_ai_hub/current_model/edgegenbench_multigraph.bin`
+
+`scripts/build_portfolio_acceptance.py` validates the committed binary's size
+and SHA-256 before accepting the Qualcomm lane.
+
 ## Credential boundary
 
 The Qualcomm AI Hub token is configured outside the repository.

reports/portfolio_acceptance.json

@@ -18,6 +18,11 @@
       "backend": "QNN HTP",
       "qairt_version": "2.45.0.260326154327",
       "context_model_id": "mnjjex79n",
+      "context_path": "artifacts/qualcomm_ai_hub/current_model/edgegenbench_multigraph.bin",
+      "context_sha256": "43d7cb889b0dd97d8de3a48557fdc7dceb322e6c7b72fdb91b19e5473f84b0df",
+      "context_size_bytes": 106496,
+      "context_hash_origin": "committed_git_blob",
+      "context_matches_repository": true,
       "link_job_id": "jgk4d8lvp",
       "graphs": [
         {

reports/portfolio_acceptance.md

@@ -13,6 +13,7 @@
 
 Device: **Snapdragon 8 Elite QRD**; backend: **QNN HTP**; QAIRT: `2.45.0.260326154327`.
 Source-model provenance match: **True**.
+Tracked QNN context provenance match: **True** (`artifacts/qualcomm_ai_hub/current_model/edgegenbench_multigraph.bin`, `43d7cb889b0dd97d8de3a48557fdc7dceb322e6c7b72fdb91b19e5473f84b0df`).
 
 | Batch | AI Hub latency (ms) | Throughput (samples/s) | Peak memory (bytes) | Placement | Max normalized drift |
 |---:|---:|---:|---:|---|---:|

reports/qualcomm_qnn_v0_1.json

@@ -44,6 +44,7 @@
     "link_status": "JobStatus\n---------\ncode    : SUCCESS\nmessage : \n",
     "target_model_id": "mnjjex79n",
     "target_model_type": "SourceModelType.QNN_CONTEXT_BINARY",
+    "serialized_model_path": "artifacts/qualcomm_ai_hub/current_model/edgegenbench_multigraph.bin",
     "serialized_model_size_bytes": 106496,
     "serialized_model_sha256": "43d7cb889b0dd97d8de3a48557fdc7dceb322e6c7b72fdb91b19e5473f84b0df",
     "target_metadata": {

scripts/build_portfolio_acceptance.py

@@ -65,6 +65,14 @@ def validate_ai_hub_qnn(report_path: Path, repository_root: Path) -> dict[str, A
         raise ValueError("Qualcomm report must identify the HTP backend and QAIRT version")
     if "SUCCESS" not in str(linked.get("link_status")):
         raise ValueError("linked QNN context job did not succeed")
+    context_path = repository_root / str(linked.get("serialized_model_path"))
+    context_sha256, context_hash_origin = _repository_sha256(repository_root, context_path)
+    context_size = context_path.stat().st_size if context_path.is_file() else None
+    context_matches = context_sha256 == linked.get(
+        "serialized_model_sha256"
+    ) and context_size == linked.get("serialized_model_size_bytes")
+    if not context_matches:
+        raise ValueError("tracked QNN context binary does not match its reported hash and size")
     validation = linked.get("validation")
     if not isinstance(validation, dict) or validation.get("device") != hardware.get("device"):
         raise ValueError("linked QNN validation device does not match the report")
@@ -111,6 +119,11 @@ def validate_ai_hub_qnn(report_path: Path, repository_root: Path) -> dict[str, A
         "backend": "QNN HTP",
         "qairt_version": hardware["qairt_version"],
         "context_model_id": linked["target_model_id"],
+        "context_path": linked["serialized_model_path"],
+        "context_sha256": context_sha256,
+        "context_size_bytes": context_size,
+        "context_hash_origin": context_hash_origin,
+        "context_matches_repository": context_matches,
         "link_job_id": linked["link_job_id"],
         "graphs": sorted(graph_summaries, key=lambda value: value["batch_size"]),
         "reported_source_model_sha256": source.get("sha256"),
@@ -176,6 +189,8 @@ def build_portfolio_acceptance(
             f"Device: **{qnn['device']}**; backend: **{qnn['backend']}**; "
             f"QAIRT: `{qnn['qairt_version']}`.",
             f"Source-model provenance match: **{qnn['source_model_matches_repository']}**.",
+            f"Tracked QNN context provenance match: **{qnn['context_matches_repository']}** "
+            f"(`{qnn['context_path']}`, `{qnn['context_sha256']}`).",
             "",
             "| Batch | AI Hub latency (ms) | Throughput (samples/s) | "
             "Peak memory (bytes) | Placement | Max normalized drift |",

scripts/rerun_qualcomm_qnn_current_model.py

@@ -319,6 +319,7 @@ def main() -> None:
             "link_status": str(link_job.get_status()),
             "target_model_id": target_model.model_id,
             "target_model_type": str(target_model.model_type),
+            "serialized_model_path": str(CONTEXT_PATH),
             "serialized_model_size_bytes": CONTEXT_PATH.stat().st_size,
             "serialized_model_sha256": _sha256(CONTEXT_PATH),
             "target_metadata": metadata,

tests/test_portfolio_acceptance.py

@@ -19,6 +19,8 @@ def test_validates_tracked_ai_hub_qnn_evidence() -> None:
     assert result["backend"] == "QNN HTP"
     assert result["source_model_matches_repository"] is True
     assert result["source_model_hash_origin"] == "committed_git_blob"
+    assert result["context_matches_repository"] is True
+    assert result["context_hash_origin"] == "committed_git_blob"
     assert len(cast(list[object], result["graphs"])) == 3
 
 
@@ -32,3 +34,13 @@ def test_rejects_cpu_compute_unit_in_qnn_report(tmp_path: Path) -> None:
     path.write_text(json.dumps(report))
     with pytest.raises(ValueError, match="exclusive NPU"):
         validate_ai_hub_qnn(path, root)
+
+
+def test_rejects_mismatched_qnn_context_hash(tmp_path: Path) -> None:
+    root = Path(__file__).parents[1]
+    report = json.loads((root / "reports/qualcomm_qnn_v0_1.json").read_text())
+    report["linked_multigraph"]["serialized_model_sha256"] = "0" * 64
+    path = tmp_path / "qnn.json"
+    path.write_text(json.dumps(report))
+    with pytest.raises(ValueError, match="context binary"):
+        validate_ai_hub_qnn(path, root)