[AZ-300] Implement PytorchFp16Runtime — C7 simple-baseline strategy

AZ-300 mandatory simple-baseline InferenceRuntime (eager FP16 PyTorch).
Implements the AZ-297 Protocol; current_runtime_label returns
"pytorch_fp16". Numerical reference every fancier C7 strategy (AZ-298
TRT, AZ-299 ORT) is measured against, and the only viable runtime for
Tier-1 workstation Docker where TRT is non-trivial to install.

Production code (new):
 - components/c7_inference/pytorch_fp16_runtime.py — runtime +
   PytorchEngineHandle + output-shape adapter
 - components/c7_inference/architecture_registry.py — torch-free
   register_architecture / default_registry / ArchitectureFactory
   (Risk-1 mitigation: no L2->L3 back-edge from C7 into per-backbone
   code)
 - components/c7_inference/__init__.py — re-exports the registry
   mechanism. Still does NOT import the concrete strategy module
   (Invariant I-5)
 - components/c7_inference/config.py — adds per_frame_debug_log bool
   field (gates the DEBUG per-frame latency log)

Tests (new): tests/unit/c7_inference/test_pytorch_fp16_runtime.py
covers AC-1..AC-8 + NFRs. AC-1/2/6/7 + thermal/release/registry
guards run unconditionally (17 tests); AC-3/4/5/8 +
NFR-perf-deserialize + NFR-reliability-eval-mode require CUDA and
skip on Tier-1 CI / macOS dev.

Tests (modified):
 - test_protocol_conformance.py — narrowed
   test_ac5_build_inference_runtime_flag_on_but_module_missing
   parametrisation to exclude pytorch_fp16 (now-built); TRT / ORT
   still covered until AZ-298 / AZ-299 ship.

CI: .github/workflows/ci.yml lint + unit jobs now install
'-e .[dev,inference]' because mypy + pytest need torch + torchvision +
onnxruntime on the runner.

Three task-spec -> as-built deltas documented in
_docs/02_tasks/done/AZ-300_c7_pytorch_baseline.md Implementation Notes:
 1. Constructor conforms to AZ-297 factory shape (config positional;
    thermal_publisher + registry + clock keyword-only optionals).
    AZ-302 will update the factory to thread thermal_publisher.
 2. Architecture registry uses extras["model_name"] as lookup key
    (avoids touching the frozen BuildConfig / EngineCacheEntry DTOs).
 3. Warm-up forward deferred to AZ-300 tier-2 follow-up — the zero-arg
    registry has no per-backbone input-shape metadata.

Suite: 1120 passed / 10 skipped (CUDA + Tier-2 + cmake / actionlint
environment gates). No regressions in non-c7_inference areas.

Co-authored-by: Cursor <cursoragent@cursor.com>

_docs/_autodev_state.md

@@ -6,9 +6,9 @@ step: 7
 name: Implement
 status: in_progress
 sub_step:
-  phase: 3
-  name: compute-next-batch
-  detail: "batch 24/cycle1 computed but BLOCKED on env: AZ-300 (C7 PytorchFp16Runtime, 2pt) needs the [inference] optional extra (torch>=2.2 + torchvision>=0.17 + onnxruntime>=1.17, ~700 MB on macOS). Dev venv currently only has [dev]. Resolve: either (a) pip install -e .[inference] before resuming, or (b) skip AZ-300 in this cycle (move it to backlog) and pick the next-smallest ready task that does not need torch — AZ-301 EngineGate (3pt, no torch dep), AZ-302 ThermalState Publisher (3pt, jetson-stats/pynvml — also heavy but tier2-only), AZ-304 C6 Postgres schema (2pt, no native deps). 18 tasks total ready overall."
+  phase: 13
+  name: archive-and-loop
+  detail: "batch 24/cycle1 complete: AZ-300 → In Testing, archived to done/. Installed [inference] extras (torch 2.11.0 + torchvision 0.26.0 + onnxruntime 1.23.2) into the dev venv. 17 ACs + NFRs covered (6 CUDA-skipped on macOS). Suite: 1120 passed / 10 skipped. Next: recompute batch 25 — candidates AZ-301 (EngineGate, 3pt) + AZ-302 (ThermalStatePublisher, 3pt) + AZ-304 (C6 Postgres schema, 2pt). 17 tasks total ready overall (AZ-300 removed; AZ-345 still gated)."
 retry_count: 0
 cycle: 1
 tracker: jira