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openvino/model-optimizer/extensions/ops/normalize_l2.py

61 lines
2.0 KiB
Python

"""
Copyright (C) 2018-2020 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 mo.graph.graph import Graph, Node
from mo.ops.op import Op
class NormalizeL2Op(Op):
op = 'NormalizeL2'
enabled = True
def __init__(self, graph: Graph, attrs: dict):
super().__init__(graph, {
'type': __class__.op,
'op': __class__.op,
'version': 'opset1',
'eps': None,
'p': None,
'eps_mode': None,
'in_ports_count': 2,
'out_ports_count': 1,
'infer': __class__.infer
}, attrs)
def supported_attrs(self):
return ['eps', 'eps_mode']
@staticmethod
def infer(node: Node):
input_shape = node.in_port(0).data.get_shape()
if input_shape is None:
return
input_value = node.in_port(0).data.get_value()
axes = node.in_port(1).data.get_value()
if input_value is not None and axes is not None:
norm_value = np.linalg.norm(input_value, node.p, axes, keepdims=True)
if node.eps_mode == 'add':
norm_value = norm_value + node.eps
elif node.eps_mode == 'max':
norm_value = np.max(norm_value, node.eps)
else:
assert False, 'Unsupported "eps_mode" = {}'.format(node.eps_mode)
node.out_port(0).data.set_value(input_value / norm_value)
else:
node.out_port(0).data.set_shape(input_shape)