def use_shapes_from_ir(node: Node):
# This function used instead of operation shape inference function to set all output shapes the same as
# restored from IR. Firstly, check equality of old (restored from IR) and
# new (calculated while shape inference) input shapes
node['new_input_shapes'] = list()
for n in node.in_ports():
if not node.in_port(n).disconnected(
): # We use such condition to handle optional inputs
node.new_input_shapes.append(node.in_port(n).data.get_shape())
assert len(node.new_input_shapes) == len(node.old_input_shapes), \
'Something wrong happened while {} node with type {} copy shape inference!'.format(node.name, node.type)
for new_input_shape, old_input_shape in zip(node.new_input_shapes,
node.old_input_shapes):
assert np.array_equal(new_input_shape, old_input_shape), \
'Something wrong happened while {} node with type {} copy shape inference!'.format(node.name, node.type)
# We need to use number of connected input ports to avoid errors with numbering
# in node.ports dictionary, where used numbers of input nodes
connected_input_ports = []
for n in node.in_ports():
if not node.in_port(n).disconnected():
connected_input_ports.append(node.in_port(n))
i = len(connected_input_ports)
# Set all output shapes the same as restored from IR
for num in node.out_ports():
node.out_port(num).data.set_shape(int64_array(node.ports[i][0]))
i += 1
def replace_with_hsigmoid(graph: Graph, first_node: Node, last_node: Node):
# determine the input port of first and last nodes which gets the 'input' node output
add_input_port_idx = int(
first_node.in_port(0).get_connection().get_source().node.soft_get('op')
== 'Const')
last_node_name = last_node.soft_get('name', last_node.id)
hsigmoid = HSigmoid(graph, {}).create_node()
hsigmoid.in_port(0).connect(
first_node.in_port(add_input_port_idx).get_source())
last_node.out_port(0).get_connection().set_source(hsigmoid.out_port(0))
rename_nodes([(last_node, last_node_name + '/TBR'),
(hsigmoid, last_node_name)])