Check all models with concat in tf / make changes in export_helpers.py to make test clearer

Author: daniil-lyakhov

nncf/common/pruning/export_helpers.py

@@ -144,14 +144,31 @@ def check_concat(cls, node: NNCFNode, graph: NNCFGraph) -> bool:
 
         for input_node in graph.get_previous_nodes(node):
             # If input has mask ->  it went from convolution (source of this node is a convolution)
+            node_has_mask = False
             if input_node.data.get('output_mask', None) is not None:
-                continue
+                node_has_mask = True
 
             source_nodes = get_sources_of_node(input_node, graph, cls.ConvolutionOp.get_all_op_aliases() +
                                                cls.StopMaskForwardOp.get_all_op_aliases() +
                                                cls.InputOp.get_all_op_aliases())
-            sources_types = [node.node_type for node in source_nodes] + [input_node.node_type]
-            if any(t in sources_types for t in cls.StopMaskForwardOp.get_all_op_aliases()):
+
+            source_types_old = [node.node_type for node in source_nodes]
+            sources_types_new = source_types_old + [input_node.node_type]
+
+            decision_old_on_sources = any(t in source_types_old for t in cls.StopMaskForwardOp.get_all_op_aliases())
+            decision_old = decision_old_on_sources and node_has_mask
+
+            decision_new_on_sources = any(t in sources_types_new for t in cls.StopMaskForwardOp.get_all_op_aliases())
+            decision_new = decision_new_on_sources and not node_has_mask
+
+            if decision_new != decision_old:
+                is_on_sources_equal = decision_new_on_sources == decision_old_on_sources
+                if not is_on_sources_equal:
+                    raise ValueError('ALERT')
+
+                print(f'is_on_sources_equal = {is_on_sources_equal}')
+                print('behaviour changed!!!')
+            if decision_new:
                 return False
         return True
 

tests/tensorflow/pruning/test_concat.py

@@ -0,0 +1,25 @@
+import pytest
+
+from tests.tensorflow.helpers import create_compressed_model_and_algo_for_test
+from tests.tensorflow.pruning.helpers import get_basic_pruning_config
+from tests.tensorflow import test_models
+
+
+MODELS = [
+    {'model': test_models.InceptionV3,
+     'input_shape': (75, 75, 3)},
+    {'model': test_models.InceptionResNetV2,
+     'input_shape': (75, 75, 3)},
+    {'model': test_models.NASNetMobile,
+     'input_shape': (32, 32, 3)},
+    {'model': test_models.DenseNet121,
+     'input_shape': (32, 32, 3)},
+]
+
+
+@pytest.mark.parametrize('model,input_shape', [list(elem.values()) for elem in MODELS])
+def test_concat(model, input_shape):
+    config = get_basic_pruning_config(input_shape[1])
+    model = model(list(input_shape))
+
+    model, _ = create_compressed_model_and_algo_for_test(model, config)