def replace_op(self, graph: Graph, node: Node):
node_name = node.soft_get('name', node.id)
# broadcast default value to required shape
broadcast_node = Broadcast(graph, {'name': node_name + '/Broadcast_'}).create_node()
node.in_port(1).get_connection().set_destination(broadcast_node.in_port(1))
if not node.in_port(3).disconnected():
# TODO: remove casting once we start to support I64 model input
# cast default value to I32 due limitation about I64 input support
# so that input parameter and default value will be of the same I32 type as required ScatterNDUpdate
cast_default_value = Cast(graph, {'name': node_name + '/CastDefaultValue', 'dst_type': np.int32}).create_node()
node.in_port(3).get_connection().set_destination(cast_default_value.in_port(0))
broadcast_node.in_port(0).connect(cast_default_value.out_port(0))
else:
broadcast_node.in_port(0).connect(Const(graph, {'name': broadcast_node.name + '/FillValue_',
'value': np.float32(0)}
).create_node().out_port(0))
# update broadcasted tensor with required values at required locations
scatternd_node = ScatterNDUpdate(graph, {'name': node_name + '/ScatterNDUpdate_'}).create_node()
scatternd_node.in_port(0).connect(broadcast_node.out_port(0))
node.in_port(0).get_connection().set_destination(scatternd_node.in_port(1))
node.in_port(2).get_connection().set_destination(scatternd_node.in_port(2))
rename_nodes([(node, node_name + "/AbandonedName"), (scatternd_node, node_name)])
return [scatternd_node.id]
def replace_op(self, graph: Graph, node: Node):
node_name = node.soft_get('name', node.id)
# broadcast default value to required shape
broadcast_node = Broadcast(graph, {'name': node_name + '/Broadcast_'}).create_node()
node.in_port(1).get_connection().set_destination(broadcast_node.in_port(1))
if not node.in_port(3).disconnected():
node.in_port(3).get_connection().set_destination(broadcast_node.in_port(0))
else:
broadcast_node.in_port(0).connect(Const(graph, {'name': broadcast_node.name + '/FillValue_',
'value': np.float32(0)}
).create_node().out_port(0))
# update broadcasted tensor with required values at required locations
scatternd_node = ScatterNDUpdate(graph, {'name': node_name + '/ScatterNDUpdate_'}).create_node()
scatternd_node.in_port(0).connect(broadcast_node.out_port(0))
node.in_port(0).get_connection().set_destination(scatternd_node.in_port(1))
node.in_port(2).get_connection().set_destination(scatternd_node.in_port(2))
rename_nodes([(node, node_name + "/AbandonedName"), (scatternd_node, node_name)])
return [scatternd_node.id]