NXP backend: Add test cases for new Neutron C flow

Author: StrycekSimon

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

@@ -6,7 +6,6 @@
 import numpy as np
 import pytest
 import torch
-
 from executorch.backends.nxp.backend.edge_program_converter import (
     EdgeProgramToIRConverter,
 )
@@ -180,3 +179,48 @@ def test_convert_clamp__no_delegation__unsupported_bounds(min, max):
 
     # Make sure the `clamp` was NOT delegated.
     assert graph_contains_any_of_ops(delegated_ep.graph, [Clamp])
+
+
+@pytest.mark.parametrize(
+    "min, max",
+    [
+        pytest.param(10, 17, id="min = 10, max = 17 (Max/Min)"),
+        pytest.param(0, 1, id="min = 0, max = 1 (Relu0To1)"),
+        pytest.param(-1, 1, id="min = -1, max = 1 (ReluN1To1)"),
+        pytest.param(0, None, id="min = 0, max = None (Relu)"),
+        # Float bounds
+        pytest.param(10.0, 17.0, id="min = 10, max = 17 (Max/Min)"),
+        pytest.param(0.0, 1.0, id="min = 0, max = 1 (Relu0To1)"),
+        pytest.param(-1.0, 1.0, id="min = -1, max = 1 (ReluN1To1)"),
+        pytest.param(0.0, None, id="min = 0, max = None (Relu)"),
+    ],
+)
+def test_convert_clamp__new_neutron_c_flow(mocker, min, max):
+    input_shape = (23,)
+    model = AddClampModule(min, max)
+
+    converter_spy = mocker.spy(EdgeProgramToIRConverter, "convert_program")
+    delegated_ep = to_quantized_edge_program(
+        model, input_shape, use_new_flow_neutron_c=True
+    ).exported_program()
+
+    # Make sure the `clamp` was delegated.
+    assert graph_contains_any_of_ops(delegated_ep.graph, [ExecutorchDelegateCall])
+    assert not graph_contains_any_of_ops(delegated_ep.graph, [Clamp])
+
+    # Verify correct behavior of the converted NeutronIR model.
+    intermediate_ep = converter_spy.call_args.args[1]
+    neutron_ir_model, _ = converter_spy.spy_return
+
+    input_data = (
+        np.random.random(input_shape).astype(np.float32) * 256.0 - 128.0
+    ).astype(np.int8)
+
+    # Make sure the tested program contains the `clamp`.
+    assert graph_contains_any_of_ops(intermediate_ep.graph, [Clamp])
+
+    convert_run_compare(
+        intermediate_ep,
+        tfl_model=neutron_ir_model,
+        input_data=input_data,
+    )