Publishing 2019 R1 content
[platform/upstream/dldt.git] / model-optimizer / mo / front / kaldi / extractors / affine_transform_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 types
18
19 import numpy as np
20
21 from mo.front.kaldi.extractors.affine_transform_ext import AffineTransformFrontExtractor
22 from mo.front.kaldi.extractors.common_ext_test import KaldiFrontExtractorTest
23 from mo.front.kaldi.loader.utils_test import TestKaldiUtilsLoading
24 from mo.ops.inner_product import InnerProduct
25 from mo.ops.op import Op
26
27
28 class AffineTransformFrontExtractorTest(KaldiFrontExtractorTest):
29     @classmethod
30     def register_op(cls):
31         Op.registered_ops['FullyConnected'] = InnerProduct
32
33     @classmethod
34     def create_pb_for_test_node(cls):
35         pb = KaldiFrontExtractorTest.generate_learn_info()
36         pb += KaldiFrontExtractorTest.generate_matrix([10, 10])
37         pb += KaldiFrontExtractorTest.generate_vector(10)
38         cls.test_node['parameters'] = TestKaldiUtilsLoading.bytesio_from(pb)
39         AffineTransformFrontExtractor.extract(cls.test_node)
40
41     def test_assertion(self):
42         self.assertRaises(AttributeError, AffineTransformFrontExtractor.extract, None)
43
44     def test_attrs(self):
45         self.assertEqual(self.test_node['out-size'], 10)
46         self.assertEqual(self.test_node['layout'], 'NCHW')
47
48     def test_out_blobs(self):
49         self.assertTrue(np.array_equal(self.test_node.weights, range(10 * 10)))
50         self.assertTrue(np.array_equal(self.test_node.biases, range(10)))
51
52