[Model] Fix adaptation test fixture so the capacity cap does not bind

The fixture reported device capacity 100, making the 25% cap 25 — below
the learned budget of 37 — so the post-adaptation checks released again
and the test failed. Raise the fixture capacity to 400 so the cap stays
above the learned budget and the test isolates peak adaptation; verified
against the real suite on the L20X validation host (15 passed).

Signed-off-by: hsliuustc0106 <liuhongsheng4@huawei.com>

tests/diffusion/offloader/test_module_residency.py

@@ -305,7 +305,9 @@ def test_allocator_cache_budget_adapts_to_observed_peak(monkeypatch, patched_run
     monkeypatch.setattr(
         residency_module.current_omni_platform,
         "get_device_memory",
-        lambda _device: (telemetry["free"], 100),
+        # Capacity 400 keeps the 25% cap (100) above the learned budget so
+        # this test isolates the peak-adaptation behavior from the cap.
+        lambda _device: (telemetry["free"], 400),
     )
     retention = BoundedAllocatorCache(torch.device("cpu"))
     retention.grow_retention_budget(10)