fix(perf): honor configured input value ranges

src/winml/modelkit/commands/perf.py

@@ -538,6 +538,7 @@ def generate_random_inputs(
     symbolic_shapes = io_config.get("input_symbolic_shapes") or [
         [None] * len(s) for s in io_config["input_shapes"]
     ]
+    value_ranges = io_config.get("input_value_ranges") or {}
     overrides = shape_config or {}
 
     specs: dict[str, dict[str, Any]] = {}
@@ -566,6 +567,8 @@ def generate_random_inputs(
             "dtype": gen_dtype,
             "shape": list(resolved_shape),
         }
+        if name in value_ranges:
+            specs[name]["range"] = value_ranges[name]
 
     return generate_dummy_inputs_from_specs(specs)
 

src/winml/modelkit/session/session.py

@@ -1676,7 +1676,7 @@ def io_config(self) -> dict:
             self._io_config["precision"] = self._get_precision(model)
         return self._io_config
 
-    def _load_input_value_ranges(self) -> dict[str, list[int]]:
+    def _load_input_value_ranges(self) -> dict[str, list[float]]:
         """Load input value ranges from the winml_build_config.json.
 
         Searches for the build config file in the same directory as the
@@ -1688,7 +1688,7 @@ def _load_input_value_ranges(self) -> dict[str, list[int]]:
         """
         import json
 
-        value_ranges: dict[str, list[int]] = {}
+        value_ranges: dict[str, list[float]] = {}
         model_dir = self._onnx_path.parent
 
         # Try exact name first, then glob for prefixed variants

tests/unit/commands/test_perf_cli.py

@@ -36,6 +36,7 @@
     PerfBenchmark,
     display_console_report,
     generate_output_path,
+    generate_random_inputs,
     perf,
 )
 from winml.modelkit.utils.console import SafeConsole
@@ -255,6 +256,21 @@ def test_path_is_under_user_home(self) -> None:
         assert self._cache_root in result.parents
 
 
+class TestGenerateRandomInputs:
+    def test_uses_persisted_floating_value_range(self) -> None:
+        io_config = {
+            "input_names": ["image"],
+            "input_shapes": [[1, 3, 8, 8]],
+            "input_types": ["float32"],
+            "input_value_ranges": {"image": [-2.1179039478302, 2.640000343322754]},
+        }
+
+        inputs = generate_random_inputs(io_config)
+
+        assert inputs["image"].min() >= io_config["input_value_ranges"]["image"][0]
+        assert inputs["image"].max() < io_config["input_value_ranges"]["image"][1]
+
+
 # =============================================================================
 # UNIFIED PIPELINE TESTS (ONNX and HF both through PerfBenchmark)
 # =============================================================================