def test_is_connected_component_edges_direction_is_ignored(self):
"""
Check that edges direction is ignored when checking for the connectivity.
"""
graph = Graph()
node_names = list(range(1, 5))
graph.add_nodes_from(node_names)
graph.add_edges_from([(2, 1), (2, 3), (4, 3)])
self.assertTrue(is_connected_component(graph, node_names))
self.assertTrue(is_connected_component(graph, [2, 1]))
self.assertTrue(is_connected_component(graph, [4, 2, 3]))
def test_is_connected_component_two_separate_sub_graphs(self):
"""
Check that if there are two separate sub-graphs the function returns False.
"""
graph = Graph()
graph.add_nodes_from(list(range(1, 7)))
graph.add_edges_from([(1, 2), (2, 3), (4, 5), (5, 6)])
self.assertFalse(is_connected_component(graph, list(range(1, 7))))
self.assertFalse(is_connected_component(graph, [1, 3]))
self.assertFalse(is_connected_component(graph, [6, 4]))
self.assertFalse(is_connected_component(graph, [2, 5]))
def test_is_connected_component_edges_direction_is_ignored_not_connected(self):
"""
Check that edges direction is ignored when checking for the connectivity. In this case the graph is not
connected.
"""
graph = Graph()
graph.add_nodes_from(list(range(1, 5)))
graph.add_edges_from([(2, 1), (2, 3), (4, 3)])
self.assertFalse(is_connected_component(graph, [1, 2, 4]))
self.assertFalse(is_connected_component(graph, [1, 4]))
self.assertFalse(is_connected_component(graph, [2, 4]))
self.assertFalse(is_connected_component(graph, [3, 4, 1]))
def find_and_replace_pattern(self, graph: Graph):
replacement_descriptions = CustomReplacementRegistry(
).get_custom_replacement_description(self.replacement_id)
if replacement_descriptions is None:
log.info(
"Failed to find custom replacement description with id '{}'".
format(self.replacement_id))
return
# there are a list of custom replacements descriptions that have the same replacement id
for replacement_description in replacement_descriptions:
sub_graph_matcher = SubgraphMatcher(replacement_description)
matched_instances = list(
sub_graph_matcher.matched_sub_graph_instances(graph))
if not len(matched_instances):
log.error(
"Failed to match nodes from custom replacement description with id '{}':\nIt means model and "
"custom replacement description are incompatible.\nTry to correct custom replacement "
"description according to documentation with respect to model node names"
"".format(self.replacement_id))
for match in matched_instances:
if not is_connected_component(graph,
match.matched_nodes_names()):
log.warning(
"The following nodes don't form connected sub-graph: {}"
.format(match.matched_nodes_names()))
# graph.dump_graph_for_graphviz(match.matched_nodes_names())
self.replace_sub_graph(graph, match)
def test_is_connected_component_connected(self):
"""
Check that if the sub-graph is connected.
"""
graph = Graph()
node_names = list(range(1, 8))
graph.add_nodes_from(node_names)
graph.add_edges_from([(1, 2), (2, 3), (4, 5), (5, 6), (1, 7), (7, 4)])
self.assertTrue(is_connected_component(graph, list(range(1, 8))))
def test_is_connected_component_two_separate_sub_graphs_divided_by_ignored_node(self):
"""
Check that if there are two separate sub-graphs the function connected by an edge going through the ignored node
then the function returns False.
"""
graph = Graph()
node_names = list(range(1, 8))
graph.add_nodes_from(node_names)
graph.add_edges_from([(1, 2), (2, 3), (4, 5), (5, 6), (1, 7), (7, 4)])
self.assertFalse(is_connected_component(graph, list(range(1, 7))))
def find_and_replace_pattern(self, graph: Graph):
replacement_descriptions = CustomReplacementRegistry(
).get_custom_replacement_description(self.replacement_id)
if replacement_descriptions is None:
log.info(
"Failed to find custom replacement description with id '{}'".
format(self.replacement_id))
return
# there are a list of custom replacements descriptions that have the same replacement id
for replacement_description in replacement_descriptions:
sub_graph_matcher = SubgraphMatcher(replacement_description)
for match in sub_graph_matcher.matched_sub_graph_instances(graph):
if not is_connected_component(graph,
match.matched_nodes_names()):
log.warning(
"The following nodes don't form connected sub-graph: {}"
.format(match.matched_nodes_names()))
graph.dump_graph_for_graphviz(match.matched_nodes_names())
self.replace_sub_graph(graph, match)
def merge_nodes(graph: Graph, nodes_to_merge_names: list, inputs_desc: list = None,
outputs_desc: list = None):
"""
Merges nodes specified in the set 'nodes_to_merge_names' into one mega-node, creating new edges between mega-node
and inputs/outputs nodes of the mega-node. The added edges contain name of input/output nodes which will be used for
generation of placeholders and will be saved to the IR xml so IE plug-in know how to map input/output data for the
layer. Also the function adds protobufs of the nodes of the sub-graph and 'Const' ops consumed by nodes in the
sub-graph to the node's attribute 'pbs'.
:param graph: the graph object to operate on.
:param nodes_to_merge_names: list of nodes names that should be merged into a single node.
:param inputs_desc: optional list describing input nodes order.
:param outputs_desc: optional list describing output nodes order.
"""
if not is_connected_component(graph, nodes_to_merge_names):
log.warning("The following nodes do not form connected sub-graph: {}".format(nodes_to_merge_names))
graph.dump_graph_for_graphviz(nodes_to_dump=nodes_to_merge_names)
new_node_name = graph.unique_id("TFSubgraphCall_")
log.info("Create new node with name '{}' for nodes '{}'".format(new_node_name, ', '.join(nodes_to_merge_names)))
graph.add_node(new_node_name)
new_node_attrs = graph.node[new_node_name]
new_node_attrs['name'] = new_node_name
set_tf_custom_call_node_attrs(new_node_attrs)
new_node = Node(graph, new_node_name)
added_input_tensors_names = set() # set of tensors that are were added as input to the sub-graph
added_new_node_output_tensors = dict() # key - tensor name, value - out port
for node_name in nodes_to_merge_names:
node = Node(graph, node_name)
add_node_pb_if_not_yet_added(node, new_node)
# TODO: any improvements?
for in_node_name, edge_attrs in Node(graph, node_name).get_inputs():
in_node = Node(graph, in_node_name)
# internal edges between nodes of the sub-graph
if in_node_name in nodes_to_merge_names:
add_node_pb_if_not_yet_added(in_node, new_node)
continue
# edge outside of sub-graph into sub-graph
if in_node_name not in nodes_to_merge_names:
# we cannot use the 'in_node_name' as a protobuf operation name here
# because the 'in_node_name' could be a sub-graph matched before.
input_tensor_name = node.pb.input[edge_attrs['in']]
if input_tensor_name not in added_input_tensors_names:
graph.add_edge(in_node_name, new_node_name,
**merge_edge_props(
{'in': find_input_port(new_node, inputs_desc, node_name, edge_attrs['in']),
'out': edge_attrs['out'],
'internal_input_node_name': input_tensor_name,
'original_dst_node_name': node_name,
'original_dst_port': edge_attrs['in'],
'in_attrs': ['in', 'internal_input_node_name', 'original_dst_node_name',
'original_dst_port', 'placeholder_name'],
'out_attrs': ['out']},
edge_attrs)
)
log.debug("Creating edge from outside of sub-graph to inside sub-graph: {} -> {}".format(
in_node_name, new_node_name))
added_input_tensors_names.add(input_tensor_name)
# edge from inside sub-graph to outside sub-graph
for out_node_name, edge_attrs in Node(graph, node_name).get_outputs():
if out_node_name not in nodes_to_merge_names:
log.debug("Creating edge from inside of sub-graph to outside sub-graph: {} -> {}".format(
new_node_name, out_node_name))
out_name = internal_output_name_for_node(node_name, edge_attrs['out'])
if out_name not in added_new_node_output_tensors.keys():
added_new_node_output_tensors[out_name] = find_output_port(new_node, outputs_desc, node_name,
edge_attrs['out'])
graph.add_edge(new_node_name, out_node_name,
**merge_edge_props(
{'in': edge_attrs['in'],
'out': added_new_node_output_tensors[out_name],
'internal_output_node_name': out_name,
'in_attrs': ['in', 'internal_input_node_name'],
'out_attrs': ['out', 'internal_output_node_name']},
edge_attrs)
)
new_node['output_tensors_names'] = [val for val in
{v: k for k, v in added_new_node_output_tensors.items()}.values()]
# add nodes using the same order as in initial GraphDef so we can dump them to IR in "correct" order
new_node['nodes_order'] = [node for node in graph.graph['initial_nodes_order'] if node in new_node['pbs'].keys()]
for n in nodes_to_merge_names:
if graph.has_node(n): # check if not deleted by another (similar) pattern
graph.remove_node(n)
return Node(graph, new_node_name)
