Fix after review (2nd pass)

Author: irtrukhina

backends/nxp/backend/ir/converter/node_converters/ops_converters/softmax_converter.py

@@ -62,9 +62,9 @@ def _is_supported_on_target(
         if custom_delegation_options.use_new_flow_neutron_c:
             """New flow: Hardware constraints for the new flow:
             1. Input and Output must be INT8/UINT8
-            2. Channels < 4096 / num_pipes * 4
-            3. Total spatial size (N*H*W) <= 4096
-            4. (channels * spatial_size) / num_macs <= 65536
+            2. Channels <= 2040
+            3. Total spatial size (H*W) <= 4096
+            4. Total size (channels * spatial_size) <= 524288
             """
             # Constraint 1: Input and Output must be INT8/UINT8.
             supported_types = [torch.int8, torch.uint8]
@@ -74,9 +74,8 @@ def _is_supported_on_target(
                 return False
 
             # Constraint 2: Channel size limit
-            num_pipes = neutron_target_spec.get_num_pipes()
             channels = SoftmaxConverter._get_channels(node)
-            if channels >= 4096 / num_pipes * 4:
+            if channels > 2040:
                 return False
 
             # Constraint 3: Spatial size limit
@@ -85,8 +84,7 @@ def _is_supported_on_target(
                 return False
 
             # Constraint 4: Total processing size limit
-            num_macs = neutron_target_spec.get_num_macs()
-            if channels * total_spatial_size / num_macs > 65536:
+            if channels * total_spatial_size > 524288:
                 return False
 
             return True

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

@@ -18,7 +18,7 @@
     ToChannelLastPreprocess,
 )
 
-from executorch.backends.nxp.tests.graph_verifier import BaseGraphVerifier
+from executorch.backends.nxp.tests.graph_verifier import DetailedGraphVerifier
 
 from executorch.backends.nxp.tests.model_output_comparator import (
     NumericalStatsOutputComparator,
@@ -224,11 +224,12 @@ class TestSoftmaxNewNeutronFlow:
             pytest.param((5, 4, 3, 2, 180), -1, id="5D_dim_-1"),
         ],
     )
-    def test__basic_nsys_inference(self, input_shape, dim):
+    def test__basic_nsys_inference(self, mocker, input_shape, dim):
         model = SoftmaxModule(dim)
-        graph_verifier = BaseGraphVerifier(
-            exp_num_delegate_call_nodes=1,  # Delegated Softmax.
-            exp_non_delegated_nodes=[],
+        graph_verifier = DetailedGraphVerifier(
+            mocker,
+            expected_delegated_ops={Softmax: 1},
+            expected_non_delegated_ops={},
         )
         output_comparator = NumericalStatsOutputComparator(
             max_mse_error=0.001, is_classification_task=True