fix(gpu): admit benchmark loads through lifecycle broker

tests/test_app_benchmark_lifecycle.py

@@ -0,0 +1,67 @@
+"""GPU admission and cleanup contracts for application benchmark paths."""
+
+from __future__ import annotations
+
+import subprocess
+import sys
+
+
+def test_benchmark_gpu_lifecycle_contracts():
+    script = r'''
+from types import SimpleNamespace
+import inspect
+
+import app
+from obliteratus.gpu_lifecycle import MemoryUsage
+
+for entrypoint in (app.benchmark, app.benchmark_multi_model):
+    source = inspect.getsource(entrypoint)
+    assert source.index("_gpu_lifecycle.loading(model_id)") < source.index("worker.start()")
+    assert "result.status == \"done\"" in source
+    assert "_release_benchmark_pipeline(" in source
+
+class LifecycleRecorder:
+    def __init__(self):
+        self.events = []
+    def resize(self, memory):
+        self.events.append(("resize", memory))
+    def release(self, *, reason):
+        self.events.append(("release", reason))
+
+lifecycle = LifecycleRecorder()
+handle = SimpleNamespace(model=object(), tokenizer=object())
+pipeline_ref = [SimpleNamespace(handle=handle)]
+calls = []
+app._gpu_lifecycle = lifecycle
+app.gc.collect = lambda: calls.append("gc")
+app.torch.cuda.is_available = lambda: False
+app.dev.empty_cache = lambda: calls.append("empty_cache")
+app.measure_torch_memory = lambda _torch: MemoryUsage()
+app._release_benchmark_pipeline(pipeline_ref, reason="benchmark_complete")
+assert handle.model is None and handle.tokenizer is None
+assert calls == ["gc", "empty_cache"]
+assert lifecycle.events == [("release", "benchmark_complete")]
+
+lifecycle = LifecycleRecorder()
+app._gpu_lifecycle = lifecycle
+memory = MemoryUsage(allocated_bytes=1, reserved_bytes=2, device_count=1)
+app.measure_torch_memory = lambda _torch: memory
+try:
+    app._release_benchmark_pipeline(
+        [SimpleNamespace(handle=SimpleNamespace(model=object(), tokenizer=object()))],
+        reason="benchmark_complete",
+    )
+except RuntimeError as error:
+    assert "retaining GPU lease" in str(error)
+else:
+    raise AssertionError("cleanup must fail closed while CUDA allocations remain")
+assert lifecycle.events == [("resize", memory)]
+'''
+    result = subprocess.run(
+        [sys.executable, "-c", script],
+        capture_output=True,
+        text=True,
+        timeout=120,
+        check=False,
+    )
+    assert result.returncode == 0, result.stdout + result.stderr