model-optimizer/extensions/front/caffe/spatial_transformer_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.spatial_transformer_ext import SpatialTransformFrontExtractor
  21 from extensions.ops.spatial_transformer import SpatialTransformOp
  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 FakeSpatialTransformProtoLayer:
  28     def __init__(self, val):
  29         self.st_param = val
  30
  31
  32 class TestSpatialTransformExt(unittest.TestCase):
  33     @classmethod
  34     def setUpClass(cls):
  35         Op.registered_ops['SpatialTransformer'] = SpatialTransformOp
  36
  37     def test_st_no_pb_no_ml(self):
  38         self.assertRaises(AttributeError, SpatialTransformFrontExtractor.extract, None)
  39
  40     @patch('extensions.front.caffe.spatial_transformer_ext.merge_attrs')
  41     def test_st_ext_ideal_numbers(self, merge_attrs_mock):
  42         params = {
  43             'transform_type': "ffff",
  44             'sampler_type': "gggg",
  45             'output_H': 56,
  46             'output_W': 78,
  47             'to_compute_dU': True,
  48             'theta_1_1': 0.1,
  49             'theta_1_2': 0.2,
  50             'theta_1_3': 0.3,
  51             'theta_2_1': 0.4,
  52             'theta_2_2': 0.5,
  53             'theta_2_3': 0.6
  54         }
  55         merge_attrs_mock.return_value = {
  56             **params
  57         }
  58
  59         fake_pl = FakeSpatialTransformProtoLayer(FakeMultiParam(params))
  60         fake_node = FakeNode(fake_pl, None)
  61
  62         SpatialTransformFrontExtractor.extract(fake_node)
  63
  64         exp_res = {
  65             'type': "SpatialTransformer",
  66             'transform_type': "ffff",
  67             'sampler_type': "gggg",
  68             'output_H': 56,
  69             'output_W': 78,
  70             'to_compute_dU': 1,
  71             'theta_1_1': 0.1,
  72             'theta_1_2': 0.2,
  73             'theta_1_3': 0.3,
  74             'theta_2_1': 0.4,
  75             'theta_2_2': 0.5,
  76             'theta_2_3': 0.6,
  77             'infer': SpatialTransformOp.sp_infer
  78         }
  79
  80         for key in exp_res.keys():
  81             self.assertEqual(fake_node[key], exp_res[key])