openvino/model-optimizer/extensions/front/reduce_axis_normalizer.py

58 lines
2.3 KiB
Python

"""
Copyright (c) 2019 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.
"""
from extensions.ops.ReduceOps import reduce_map
from mo.front.common.replacement import FrontReplacementSubgraph
from mo.front.subgraph_matcher import SubgraphMatch
from mo.graph.graph import Graph
from mo.ops.const import Const
from mo.utils.error import Error
class ReduceAxisNormalizer(FrontReplacementSubgraph):
"""
Reduce operation requires information about axis, that is represented in original frameworks differently:
- by layer parameter
- by 1-port input value
ReduceAxisNormalizer reforms Reduce operations to store axis info in 1-port input.
"""
enabled = True
force_shape_inference = True
def pattern(self):
return dict(
nodes=[
('reduce', dict(kind='op', op=lambda op: op in reduce_map))
],
edges=[]
)
def replace_sub_graph(self, graph: Graph, match: [dict, SubgraphMatch]):
node = match['reduce']
connected_in_ports = [port for port in node.in_ports().values() if not port.disconnected()]
if len(connected_in_ports) == 1:
# if the 'axis' is None then we still add a second input to the layer with a 1D array with 1 element equal
# to None. The infer function handles this case because the input shape is known at this stage only
if node.has('axis'):
const = Const(graph, {'value': node.axis}).create_node()
node.add_input_port(1, skip_if_exist=True)
const.out_port(0).connect(node.in_port(1))
del graph.node[node.id]['axis']
else:
raise Error('Can not deduce `reduce_axis` for {}: only one in_port and no `axis` parameter.'
''.format(node.op))