Fixes based on PR comments.

Author: MartinPavella

backends/nxp/backend/ir/converter/quantization_utils.py

@@ -1,4 +1,4 @@
-# Copyright 2023-2025 NXP
+# Copyright 2023-2026 NXP
 #
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.

backends/nxp/tests/ir/converter/node_converter/test_clamp_converter.py

@@ -24,9 +24,6 @@
 )
 from executorch.backends.nxp.tests.executors import graph_contains_any_of_ops
 from executorch.backends.nxp.tests.graph_verifier import DetailedGraphVerifier
-from executorch.backends.nxp.tests.model_output_comparator import (
-    NumericalStatsOutputComparator,
-)
 from executorch.backends.nxp.tests.nsys_testing import lower_run_compare
 from executorch.backends.nxp.tests.ops_aliases import (
     AddTensor,
@@ -81,7 +78,6 @@ def test__qat(self, mocker, min, max, use_qat):
         model = AddClampModule(min, max)
 
         x_input_spec = ModelInputSpec(input_shape)
-        comparator = NumericalStatsOutputComparator()
         graph_verifier = DetailedGraphVerifier(
             mocker,
             expected_delegated_ops={
@@ -95,7 +91,6 @@ def test__qat(self, mocker, min, max, use_qat):
             model=model,
             input_spec=[x_input_spec],
             dlg_model_verifier=graph_verifier,
-            output_comparator=comparator,
         )
 
     @pytest.mark.parametrize(
@@ -125,7 +120,6 @@ def test_convert_clamp__full_pipeline(self, mocker, request, min, max):
         model = AddClampModule(min, max)
 
         x_input_spec = ModelInputSpec(input_shape)
-        comparator = NumericalStatsOutputComparator()
         graph_verifier = DetailedGraphVerifier(
             mocker,
             expected_delegated_ops={
@@ -140,7 +134,6 @@ def test_convert_clamp__full_pipeline(self, mocker, request, min, max):
             input_spec=[x_input_spec],
             dlg_model_verifier=graph_verifier,
             request=request,
-            output_comparator=comparator,
         )
 
     @pytest.mark.parametrize(

backends/nxp/tests/ir/converter/node_converter/test_hardtanh_converter.py

@@ -184,7 +184,7 @@ def test__invalid_bounds(self, activation_range):
             _ = HardTanhModule(*activation_range)
 
     @pytest.mark.parametrize(
-        "min, max, expected_tflite_ops",
+        "min, max, expected_neutron_ir_ops",
         [
             pytest.param(
                 0.1,
@@ -207,9 +207,23 @@ def test__invalid_bounds(self, activation_range):
                 [Ops.ADD, Ops.RELU],
                 id="min = 0, max = infinity (Relu)",
             ),
+            pytest.param(
+                0,
+                1.0,
+                [Ops.ADD, Ops.RELU_0_TO_1],
+                id="min = 0, max = 1 (Relu0To1)",
+            ),
+            pytest.param(
+                0,
+                6.0,
+                [Ops.ADD, Ops.RELU6],
+                id="min = 0, max = 6 (Relu6)",
+            ),
         ],
     )
-    def test_convert_clamp__relu_vs_maxmin(self, mocker, min, max, expected_tflite_ops):
+    def test_convert_clamp__relu_vs_maxmin(
+        self, mocker, min, max, expected_neutron_ir_ops
+    ):
         input_shape = (23,)
         model = AddHardTanhModule(min, max)
 
@@ -228,15 +242,17 @@ def test_convert_clamp__relu_vs_maxmin(self, mocker, min, max, expected_tflite_o
         intermediate_ep = converter_spy.call_args.args[1]
         quant_node = list(intermediate_ep.graph.nodes)[-2]
         dequant_node = list(intermediate_ep.graph.nodes)[-4]
-        tflite_internal_ops = [
+        neutron_ir_internal_ops = [
             op.builtin_code for op in neutron_ir_spy.spy_return.operator_codes.vector
         ]
 
         assert graph_contains_any_of_ops(intermediate_ep.graph, [HardTanh])
-        assert len(tflite_internal_ops) == len(expected_tflite_ops) + 1  # Transpose
-        assert all(op in tflite_internal_ops for op in expected_tflite_ops)
+        assert (
+            len(neutron_ir_internal_ops) == len(expected_neutron_ir_ops) + 1
+        )  # Transpose
+        assert all(op in neutron_ir_internal_ops for op in expected_neutron_ir_ops)
 
-        if len(expected_tflite_ops) == 3:
+        if len(expected_neutron_ir_ops) == 3:
             # Min/Max variant should have same input and output quantization
             assert all(
                 q == dq for q, dq in zip(quant_node.args[1:], dequant_node.args[1:])