model-optimizer/extensions/front/onnx/priorbox_ext_test.py

   1 """
   2  Copyright (c) 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 onnx
  18 import unittest
  19
  20 import numpy as np
  21
  22 from extensions.front.onnx.priorbox_ext import PriorBoxFrontExtractor
  23 from extensions.ops.priorbox import PriorBoxOp
  24 from mo.ops.op import Op
  25 from mo.utils.unittest.extractors import PB
  26
  27
  28 class TestPriorBoxExt(unittest.TestCase):
  29     @staticmethod
  30     def _create_priorbox_node(aspect_ratio=[], min_size=np.array([]), max_size=np.array([]),
  31                               flip=False, clip=False, variance=None, img_size=0, img_h=0,
  32                               img_w=0, step=0, step_h=0, step_w=0, offset=0):
  33         pb = onnx.helper.make_node(
  34             'PriorBox',
  35             inputs=['x'],
  36             outputs=['y'],
  37             aspect_ratio=aspect_ratio,
  38             min_size=min_size,
  39             max_size=max_size,
  40             flip=flip,
  41             clip=clip,
  42             variance=variance,
  43             img_size=img_size,
  44             img_h=img_h,
  45             img_w=img_w,
  46             step=step,
  47             step_h=step_h,
  48             step_w=step_w,
  49             offset=offset,
  50         )
  51
  52         node = PB({'pb': pb})
  53         return node
  54
  55     @classmethod
  56     def setUpClass(cls):
  57         Op.registered_ops['PriorBox'] = PriorBoxOp
  58
  59     def test_priorbox_no_pb_no_ml(self):
  60         self.assertRaises(AttributeError, PriorBoxFrontExtractor.extract, None)
  61
  62     def test_priorbox_ext_ideal_numbers(self):
  63         node = self._create_priorbox_node(aspect_ratio=np.array([2, 3], dtype=np.float),
  64                                           variance=np.array([0.2, 0.3, 0.2, 0.3]),
  65                                           img_size=300, step=5.0, offset=0.6, flip=True)
  66
  67         PriorBoxFrontExtractor.extract(node)
  68
  69         exp_res = {
  70             'op': 'PriorBox',
  71             'type': 'PriorBox',
  72             'clip': 0,
  73             'flip': 1,
  74             'aspect_ratio': np.array([2, 3], dtype=np.float),
  75             'variance': [0.2, 0.3, 0.2, 0.3],
  76             'img_size': 300,
  77             'img_h': 0,
  78             'img_w': 0,
  79             'step': 5,
  80             'step_h': 0,
  81             'step_w': 0,
  82             'offset': 0.6
  83         }
  84
  85         for key in exp_res.keys():
  86             if key in ['variance', 'aspect_ratio', 'step_h', 'step_w', 'offset']:
  87                 np.testing.assert_almost_equal(node[key], exp_res[key])
  88             else:
  89                 self.assertEqual(node[key], exp_res[key])