ReverseInputChannels mapping fix

model-optimizer/extensions/back/ReverseInputChannels.py

@@ -310,7 +310,13 @@ def lift_up_through_eltwise(node: Node, reverse_channels: Node):
             reverse_channels_copy = reverse_channels.copy_node({'axis': np.array(axis)})
 
             src = port.get_connection().get_source()
-            port.get_connection().set_source(reverse_channels_copy.out_port(0))
+            if src.node.soft_get('type') == 'Parameter':
+                # For Parameter nodes tensor debug attributes should not move to the last node
+                # of subgraph. It is needed for the proper mapping of input framework name.
+                # For this reason "source" mode is used to keep tensor debug attributes at Parameter node.
+                port.get_connection().set_source(reverse_channels_copy.out_port(0), attributes_save_mode="source")
+            else:
+                port.get_connection().set_source(reverse_channels_copy.out_port(0))
             src.connect(reverse_channels_copy.in_port(0))
 
             copies.append(reverse_channels_copy)

model-optimizer/unit_tests/extensions/back/ReverseInputChannels_test.py

@@ -0,0 +1,49 @@
+# Copyright (C) 2018-2021 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+import unittest
+
+from extensions.back.ReverseInputChannels import ReverseChannelsPropagationUp
+from mo.graph.graph import Node, Graph
+from unit_tests.utils.graph import build_graph, result, connect, regular_op_with_shaped_data
+
+nodes = {
+    **regular_op_with_shaped_data('placeholder1', [1, 3, 10, 10], {'type': 'Parameter'}),
+    **regular_op_with_shaped_data('placeholder2', [1, 1, 1, 1], {'type': 'Parameter'}),
+
+    **regular_op_with_shaped_data('mul', [1, 3, 10, 10], {'type': 'Multiply'}),
+    **regular_op_with_shaped_data('reverse_channels', [1, 3, 10, 10], {'type': 'ReverseChannels', 'axis': 1}),
+
+    **result('result'),
+}
+
+
+class ReverseInputChannelsTest(unittest.TestCase):
+    def check_graph_attrs(self, graph: Graph, parameter_node_names: list):
+        for node in graph.get_op_nodes():
+            if node.soft_get('name') in parameter_node_names:
+                self.assertTrue(node.soft_get('type') == 'Parameter')
+                out_node = node.out_node(0)
+                self.assertTrue(out_node['fw_tensor_debug_info'] == ['fw_name', 0])
+            else:
+                for idx in node.out_nodes():
+                    out_node = node.out_node(idx)
+                    self.assertFalse('fw_tensor_debug_info' in out_node)
+
+    def set_graph_attrs(self, graph: Graph, parameter_node_names: list):
+        for node in graph.get_op_nodes():
+            if node.soft_get('name') in parameter_node_names:
+                self.assertTrue(node.soft_get('type') == 'Parameter')
+                out_node = node.out_node(0)
+                out_node['fw_tensor_debug_info'] = ['fw_name', 0]
+
+    def test_lift_up_through_eltwise(self):
+        graph = build_graph(nodes, [*connect('placeholder1', '0:mul'), *connect('placeholder2', '1:mul'),
+                                    *connect('mul', 'reverse_channels'), *connect('reverse_channels', 'result')])
+        self.set_graph_attrs(graph, ['placeholder1', 'placeholder2'])
+
+        node = Node(graph, 'mul')
+        reverse_channels = Node(graph, 'reverse_channels')
+
+        ReverseChannelsPropagationUp.lift_up_through_eltwise(node, reverse_channels)
+        self.check_graph_attrs(graph, ['placeholder1', 'placeholder2'])