Publishing 2019 R1 content
[platform/upstream/dldt.git] / model-optimizer / extensions / front / caffe / simplernms_ext_test.py
1 """
2  Copyright (c) 2018-2019 Intel Corporation
3
4  Licensed under the Apache License, Version 2.0 (the "License");
5  you may not use this file except in compliance with the License.
6  You may obtain a copy of the License at
7
8       http://www.apache.org/licenses/LICENSE-2.0
9
10  Unless required by applicable law or agreed to in writing, software
11  distributed under the License is distributed on an "AS IS" BASIS,
12  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13  See the License for the specific language governing permissions and
14  limitations under the License.
15 """
16
17 import unittest
18 from unittest.mock import patch
19
20 from extensions.front.caffe.simplernms_ext import SimplerNMSFrontExtractor
21 from extensions.ops.simplernms import SimplerNMSOp
22 from mo.utils.unittest.extractors import FakeMultiParam
23 from mo.utils.unittest.graph import FakeNode
24 from mo.ops.op import Op
25
26
27 class FakeSimplerNMSProtoLayer:
28     def __init__(self, val):
29         self.simpler_nms_param = val
30
31
32 class TestSimplerNMSExt(unittest.TestCase):
33     @classmethod
34     def setUpClass(cls):
35         Op.registered_ops['SimplerNMS'] = SimplerNMSOp
36
37     def test_simplernms_no_pb_no_ml(self):
38         self.assertRaises(AttributeError, SimplerNMSFrontExtractor.extract, None)
39
40     @patch('extensions.front.caffe.simplernms_ext.merge_attrs')
41     def test_simplernms_ext_ideal_numbers(self, merge_attrs_mock):
42         params = {
43             'cls_threshold': 0.5,
44             'max_num_proposals': 300,
45             'iou_threshold': 0.7,
46             'min_bbox_size': 16,
47             'feat_stride': 16,
48             'pre_nms_topn': 6000,
49             'post_nms_topn': 150,
50             'scale': [1, 2, 3]
51         }
52         merge_attrs_mock.return_value = {
53             **params
54         }
55
56         fake_pl = FakeSimplerNMSProtoLayer(FakeMultiParam(params))
57         fake_node = FakeNode(fake_pl, None)
58
59         SimplerNMSFrontExtractor.extract(fake_node)
60
61         exp_res = {
62             'cls_threshold': 0.5,
63             'max_num_proposals': 300,
64             'iou_threshold': 0.7,
65             'min_bbox_size': 16,
66             'feat_stride': 16,
67             'pre_nms_topn': 6000,
68             'post_nms_topn': 150,
69             'scale': [1, 2, 3],
70             'infer': SimplerNMSOp.simplernms_infer
71         }
72
73         for key in exp_res.keys():
74             self.assertEqual(fake_node[key], exp_res[key])