Support TF2 Keras ConvLSTM2D operation

Signed-off-by: Roman Kazantsev <[email protected]>

model-optimizer/extensions/middle/ApplyNHWCtoNCHWpermutation.py

@@ -44,7 +44,7 @@ def find_and_replace_pattern(self, graph: Graph):
                 if 'permutation' in edge_attrs:
                     skip_permutation = True
             for out_node in node.out_nodes():
-                edge_attrs = node.graph.get_edge_data(node.id, out_node.id)[0]
+                edge_attrs = list(node.graph.get_edge_data(node.id, out_node.id).values())[0]
                 if 'permutation' in edge_attrs:
                     skip_permutation = True
 

model-optimizer/extensions/middle/ApplyPermutations.py

@@ -70,7 +70,7 @@ def merge_nodes_permutations(graph: Graph):
 
             # Get all permutations from out edges
             for out_node in node.out_nodes():
-                edge_attrs = node.graph.get_edge_data(node.id, out_node.id)[0]
+                edge_attrs = list(node.graph.get_edge_data(node.id, out_node.id).values())[0]
                 if 'permutation' in edge_attrs:
                     permutations.append(edge_attrs['permutation'])
 

model-optimizer/extensions/middle/MoveConstToLoopBody.py

@@ -0,0 +1,47 @@
+"""
+ Copyright (C) 2017-2021 Intel Corporation
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+      http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
+"""
+
+import numpy as np
+
+from extensions.ops.loop import Loop
+from mo.middle.replacement import MiddleReplacementPattern
+from mo.graph.graph import Graph, Node
+from mo.ops.const import Const
+
+
+class MoveConstToLoopBody(MiddleReplacementPattern):
+    """
+    """
+    enabled = True
+
+    def run_after(self):
+        from extensions.middle.PartialInfer import PartialInfer
+        return [PartialInfer]
+
+    def run_before(self):
+        from extensions.middle.ApplyPermutations import ApplyPermutation
+        return [ApplyPermutation]
+
+    def find_and_replace_pattern(self, graph: Graph):
+        cleanup_called_once = False
+        # walk through all Loop nodes and find Const inputs
+        for loop_node in graph.get_op_nodes(op='Loop'):
+            if not cleanup_called_once:
+                graph.clean_up()
+                cleanup_called_once = True
+            Loop.pull_constant_inputs_into_body(loop_node)
+            Loop.normalize_input_output_ports(loop_node)
+            Loop.infer(loop_node)

model-optimizer/extensions/middle/fusings.py

@@ -96,7 +96,7 @@ def find_and_replace_pattern(self, graph: Graph):
                 for_graph_and_each_sub_graph_recursively(graph, fuse_linear_ops)
                 for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
-        normalize_eltwise_inputs(graph)
+        for_graph_and_each_sub_graph_recursively(graph, normalize_eltwise_inputs)
         for_graph_and_each_sub_graph_recursively(graph, lambda G: G.clean_up())
 
         MarkNodesToFuseUpToFakeQuantize().find_and_replace_pattern(graph)

model-optimizer/extensions/ops/loop.py

@@ -315,8 +315,7 @@ def add_back_edge(loop_node: Node, internal_parameter: Node, internal_result: No
     @staticmethod
     def pull_constant_inputs_into_body(loop_node: Node):
         for port_idx, in_port in reversed(loop_node.in_ports().items()):
-            # TODO add a check that the input does not correspond to execution_condition
-            if not in_port.disconnected() and in_port.get_source().node.soft_get('type') == 'Const':
+            if port_idx > 1 and not in_port.disconnected() and in_port.get_source().node.soft_get('type') == 'Const':
                 original_const_node = in_port.get_source().node
                 new_const_node = Const(loop_node.body, original_const_node.attrs()).create_node()
 
@@ -463,7 +462,7 @@ def remove_unused_ops_from_port_map(loop_node: Node, port_map: dict, port_map_at
                 port_to_remove = port_map[record_id_to_remove]['external_port_id']
                 if port_to_remove != -1:
                     if dir == 'in':
-                        if port_to_remove not in [0, 1]:  # input port 0 and 1 are mandatory for the Loop node
+                        if port_to_remove not in [0, 1] and port_to_remove in loop_node.in_ports().keys():  # input port 0 and 1 are mandatory for the Loop node
                             loop_node.delete_input_port(port_to_remove)
                     elif dir == 'out' and port_to_remove in loop_node.out_ports():
                         loop_node.delete_output_port(port_to_remove)

model-optimizer/mo/ops/op.py

@@ -419,7 +419,7 @@ def create_permute_attrs(node, attrs=None):
     @staticmethod
     def set_permutation(node1, node2, permutation, override=False):
         # This function creates permutation on edge between node1->node2
-        edge_attrs = node1.graph.get_edge_data(node1.id, node2.id)[0]
+        edge_attrs = list(node1.graph.get_edge_data(node1.id, node2.id).values())[0]
         if 'permutation' not in edge_attrs or override:
             nx.set_edge_attributes(G=node1.graph, values={(node1.id, node2.id, 0): permutation}, name='permutation')
         else: