model-optimizer/extensions/middle/ShufflenetReshape_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
  19 import numpy as np
  20
  21 from extensions.middle.ShufflenetReshape import FeatureShuffleReshape, ReshapeSoftmaxReshape
  22 from mo.utils.unittest.graph import build_graph, compare_graphs
  23
  24 nodes_attributes = {
  25     'placeholder_1': {'shape': None, 'type': 'Placeholder', 'kind': 'op', 'op': 'Placeholder'},
  26     'placeholder_1_data': {'value': None, 'shape': None, 'kind': 'data', 'data_type': None},
  27     # Reshape layers
  28     'reshape_1': {'type': 'Reshape', 'kind': 'op', 'op': 'Reshape', 'dim': None},
  29     'reshape_1_data': {'name': 'reshape_1_data', 'value': None, 'shape': None, 'kind': 'data'},
  30     'reshape_2': {'type': 'Reshape', 'kind': 'op', 'op': 'Reshape'},
  31     'reshape_2_data': {'name': 'reshape_2_data', 'value': None, 'shape': None, 'kind': 'data'},
  32     'reshape_3': {'type': 'Reshape', 'kind': 'op', 'op': 'Reshape'},
  33     'reshape_3_data': {'name': 'reshape_3_data', 'value': None, 'shape': None, 'kind': 'data'},
  34     # Transpose layer
  35     'transpose_1': {'type': 'Permute', 'kind': 'op', 'op': 'Transpose'},
  36     'transpose_1_data': {'value': None, 'shape': None, 'kind': 'data'},
  37     # Softmax layer
  38     'softmax_1': {'type': 'SoftMax', 'kind': 'op', 'op': 'SoftMax'},
  39     'softmax_1_data': {'value': None, 'shape': None, 'kind': 'data'},
  40 }
  41
  42
  43 class FeatureShuffleReshapeTests(unittest.TestCase):
  44     def test_1(self):
  45         graph = build_graph(nodes_attributes,
  46                             [('placeholder_1', 'placeholder_1_data'),
  47                              ('placeholder_1_data', 'reshape_1'),
  48                              ('reshape_1', 'reshape_1_data'),
  49                              ('reshape_1_data', 'transpose_1'),
  50                              ('transpose_1', 'transpose_1_data'),
  51                              ('transpose_1_data', 'reshape_2'),
  52                              ('reshape_2', 'reshape_2_data')
  53                              ],
  54                             {'placeholder_1_data': {'shape': np.array([1, 227, 227, 112])},
  55                              'reshape_1_data': {'shape': np.array([227, 227, 4, 28])},
  56                              'transpose_1': {'order': np.array([0, 1, 3, 2])},
  57                              'transpose_1_data': {'shape': np.array([227, 227, 28, 4])},
  58                              'reshape_2_data': {'shape': np.array([1, 227, 227, 112])},
  59                              })
  60         graph.graph['layout'] = 'NHWC'
  61
  62         graph_ref = build_graph(nodes_attributes,
  63                                 [('placeholder_1', 'placeholder_1_data'),
  64                                  ('placeholder_1_data', 'reshape_1'),
  65                                  ('reshape_1', 'reshape_1_data'),
  66                                  ('reshape_1_data', 'transpose_1'),
  67                                  ('transpose_1', 'transpose_1_data'),
  68                                  ('transpose_1_data', 'reshape_2'),
  69                                  ('reshape_2', 'reshape_2_data')
  70                                  ],
  71                                 {'placeholder_1_data': {'shape': np.array([1, 227, 227, 112])},
  72                                  'reshape_1_data': {'shape': np.array([1, 4, 28, 227 * 227])},
  73                                  'transpose_1': {'order': np.array([0, 2, 1, 3])},
  74                                  'transpose_1_data': {'shape': np.array([1, 28, 4, 227 * 227])},
  75                                  'reshape_2_data': {'shape': np.array([1, 227, 227, 112])},
  76                                  'reshape_3_data': {'shape': np.array([1, 227, 227, 112])},
  77                                  })
  78
  79         pattern = FeatureShuffleReshape()
  80         pattern.find_and_replace_pattern(graph)
  81
  82         (flag, resp) = compare_graphs(graph, graph_ref, 'reshape_2_data', check_op_attrs=True)
  83         self.assertTrue(flag, resp)
  84
  85     def test_2(self):
  86         graph = build_graph(nodes_attributes,
  87                             [('placeholder_1', 'placeholder_1_data'),
  88                              ('placeholder_1_data', 'reshape_1'),
  89                              ('reshape_1', 'reshape_1_data'),
  90                              ('reshape_1_data', 'transpose_1'),
  91                              ('transpose_1', 'transpose_1_data'),
  92                              ('transpose_1_data', 'reshape_2'),
  93                              ('reshape_2', 'reshape_2_data')
  94                              ],
  95                             {'placeholder_1_data': {'shape': np.array([1, 112, 227, 227])},
  96                              'reshape_1_data': {'shape': np.array([1, 4, 28, 227, 227])},
  97                              'transpose_1': {'order': np.array([0, 2, 1, 3, 4])},
  98                              'transpose_1_data': {'shape': np.array([1, 28, 4, 227, 227])},
  99                              'reshape_2_data': {'shape': np.array([1, 112, 227, 227])},
 100                              })
 101         graph.graph['layout'] = 'NCHW'
 102
 103         graph_ref = build_graph(nodes_attributes,
 104                                 [('placeholder_1', 'placeholder_1_data'),
 105                                  ('placeholder_1_data', 'reshape_1'),
 106                                  ('reshape_1', 'reshape_1_data'),
 107                                  ('reshape_1_data', 'transpose_1'),
 108                                  ('transpose_1', 'transpose_1_data'),
 109                                  ('transpose_1_data', 'reshape_2'),
 110                                  ('reshape_2', 'reshape_2_data')
 111                                  ],
 112                                 {'placeholder_1_data': {'shape': np.array([1, 112, 227, 227])},
 113                                  'reshape_1_data': {'shape': np.array([1, 4, 28, 227 * 227])},
 114                                  'transpose_1': {'order': np.array([0, 2, 1, 3])},
 115                                  'transpose_1_data': {'shape': np.array([1, 28, 4, 227 * 227])},
 116                                  'reshape_2_data': {'shape': np.array([1, 112, 227, 227])},
 117                                  })
 118
 119         pattern = FeatureShuffleReshape()
 120         pattern.find_and_replace_pattern(graph)
 121
 122         (flag, resp) = compare_graphs(graph, graph_ref, 'reshape_2_data', check_op_attrs=True)
 123         self.assertTrue(flag, resp)
 124
 125
 126 class ReshapeSoftmaxReshapeTests(unittest.TestCase):
 127     def test_1(self):
 128         graph = build_graph(nodes_attributes,
 129                             [('placeholder_1', 'placeholder_1_data'),
 130                              ('placeholder_1_data', 'reshape_1'),
 131                              ('reshape_1', 'reshape_1_data'),
 132                              ('reshape_1_data', 'softmax_1'),
 133                              ('softmax_1', 'softmax_1_data'),
 134                              ('softmax_1_data', 'reshape_2'),
 135                              ('reshape_2', 'reshape_2_data')
 136                              ],
 137                             {'placeholder_1_data': {'shape': np.array([1, 227, 227, 2])},
 138                              'reshape_1': {'dim': np.array([1, 227 * 227, 2])},
 139                              'reshape_1_data': {'shape': np.array([1 * 227 * 227, 2])},
 140                              'reshape_2_data': {'shape': np.array([1, 227, 227, 2])},
 141                              })
 142         graph.graph['layout'] = 'NHWC'
 143
 144         graph_ref = build_graph(nodes_attributes,
 145                                 [('placeholder_1', 'placeholder_1_data'),
 146                                  ('placeholder_1_data', 'reshape_1'),
 147                                  ('reshape_1', 'reshape_1_data'),
 148                                  ('reshape_1_data', 'softmax_1'),
 149                                  ('softmax_1', 'softmax_1_data'),
 150                                  ('softmax_1_data', 'reshape_3'),
 151                                  ('reshape_3', 'reshape_3_data'),
 152                                  ('reshape_3_data', 'reshape_2'),
 153                                  ('reshape_2', 'reshape_2_data')
 154                                  ],
 155                                 {'placeholder_1_data': {'shape': np.array([1, 227, 227, 2])},
 156                                  'reshape_1_data': {'shape': np.array([1, 2, 227 * 227])},
 157                                  'reshape_2_data': {'shape': np.array([1, 227, 227, 2])},
 158                                  })
 159
 160         pattern = ReshapeSoftmaxReshape()
 161         pattern.find_and_replace_pattern(graph)
 162
 163         (flag, resp) = compare_graphs(graph, graph_ref, 'reshape_2_data', check_op_attrs=True)
 164         self.assertTrue(flag, resp)
 165
 166     def test_2(self):
 167         graph = build_graph(nodes_attributes,
 168                             [('placeholder_1', 'placeholder_1_data'),
 169                              ('placeholder_1_data', 'reshape_1'),
 170                              ('reshape_1', 'reshape_1_data'),
 171                              ('reshape_1_data', 'softmax_1'),
 172                              ('softmax_1', 'softmax_1_data'),
 173                              ('softmax_1_data', 'reshape_2'),
 174                              ('reshape_2', 'reshape_2_data')
 175                              ],
 176                             {'placeholder_1_data': {'shape': np.array([1, 227, 227, 2])},
 177                              'reshape_1_data': {'shape': np.array([1 * 227 * 227, 2])},
 178                              'reshape_2_data': {'shape': np.array([1, 227, 227, 2])},
 179                              })
 180         graph.graph['layout'] = 'NCHW'
 181
 182         graph_ref = build_graph(nodes_attributes,
 183                                 [('placeholder_1', 'placeholder_1_data'),
 184                                  ('placeholder_1_data', 'reshape_1'),
 185                                  ('reshape_1', 'reshape_1_data'),
 186                                  ('reshape_1_data', 'softmax_1'),
 187                                  ('softmax_1', 'softmax_1_data'),
 188                                  ('softmax_1_data', 'reshape_2'),
 189                                  ('reshape_2', 'reshape_2_data')
 190                                  ],
 191                                 {'placeholder_1_data': {'shape': np.array([1, 227, 227, 2])},
 192                                  'reshape_1_data': {'shape': np.array([1 * 227 * 227, 2])},
 193                                  'reshape_2_data': {'shape': np.array([1, 227, 227, 2])},
 194                                  })
 195
 196         pattern = ReshapeSoftmaxReshape()
 197         pattern.find_and_replace_pattern(graph)
 198
 199         (flag, resp) = compare_graphs(graph, graph_ref, 'reshape_2_data', check_op_attrs=True)
 200         self.assertTrue(flag, resp)