model-optimizer/mo/front/kaldi/extractors/convolutional_component_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 import numpy as np
  17
  18 from mo.front.kaldi.extractors.common_ext_test import KaldiFrontExtractorTest
  19 from mo.front.kaldi.extractors.convolutional_component_ext import ConvolutionalComponentFrontExtractor
  20 from mo.front.kaldi.loader.utils_test import TestKaldiUtilsLoading
  21 from mo.ops.convolution import Convolution
  22 from mo.ops.op import Op
  23
  24
  25 class ConvolutionalComponentFrontExtractorTest(KaldiFrontExtractorTest):
  26     @classmethod
  27     def register_op(cls):
  28         Op.registered_ops['Convolution'] = Convolution
  29
  30     @classmethod
  31     def create_pb_for_test_node(cls):
  32         pb = KaldiFrontExtractorTest.write_tag_with_value('<PatchDim>', 2)
  33         pb += KaldiFrontExtractorTest.write_tag_with_value('<PatchStep>', 2)
  34         pb += KaldiFrontExtractorTest.write_tag_with_value('<PatchStride>', 4)
  35         pb += KaldiFrontExtractorTest.generate_learn_info()
  36         pb += b'<Filters> '
  37         pb += KaldiFrontExtractorTest.generate_matrix([2, 1])
  38         pb += b'<Bias> '
  39         pb += KaldiFrontExtractorTest.generate_vector(2)
  40         cls.test_node['parameters'] = TestKaldiUtilsLoading.bytesio_from(pb)
  41         ConvolutionalComponentFrontExtractor.extract(cls.test_node)
  42
  43     def test_assertion(self):
  44         self.assertRaises(AttributeError, ConvolutionalComponentFrontExtractor.extract, None)
  45
  46     def test_attrs(self):
  47         val_attrs = {
  48             'kernel': [1, 1, 1, 2],
  49             'stride': [1, 1, 1, 2],
  50             'pad': [[[0, 0], [0, 0], [0, 0], [0, 0]]],
  51             'output': 2,
  52             'patch_stride': 4,
  53             'spatial_dims': [2, 3],
  54             'channel_dims': [1],
  55             'batch_dims': [0],
  56             'dilation': [1, 1, 1, 1]
  57         }
  58         for attr in val_attrs:
  59             if isinstance(val_attrs[attr], list):
  60                 self.assertTrue((self.test_node[attr] == val_attrs[attr]).all())
  61             else:
  62                 self.assertEqual(self.test_node[attr], val_attrs[attr])
  63
  64     def test_convolution_blobs(self):
  65         self.assertTrue(np.array_equal(self.test_node.weights, [0, 1]))
  66         self.assertTrue(np.array_equal(self.test_node.biases, [0, 1]))
  67