model-optimizer/extensions/ops/resample_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.ops.resample import ResampleOp
  22 from mo.graph.graph import Node
  23 from mo.utils.unittest.graph import build_graph
  24
  25 nodes_attributes = {'node_1': {'type': 'Identity', 'kind': 'op'},
  26                     'resample': {'type': 'Resample', 'kind': 'op'},
  27                     'node_3': {'type': 'Identity', 'kind': 'op'},
  28                     'op_output': {'kind': 'op', 'op': 'OpOutput'},
  29                     }
  30
  31
  32 class TestResampleOp(unittest.TestCase):
  33     def test_tf_resample_infer(self):
  34         graph = build_graph(nodes_attributes,
  35                             [('node_1', 'resample'),
  36                              ('resample', 'node_3'),
  37                              ('node_3', 'op_output')
  38                              ],
  39                             {'node_3': {'shape': None},
  40                              'node_1': {'shape': np.array([1, 3, 227, 227])},
  41                              'resample': {'antialias': 1,
  42                                           'height': 384,
  43                                           'width': 512,
  44                                           'resample_type': 'LINEAR',
  45                                           'factor': 1.0}
  46                              })
  47
  48         graph.graph['layout'] = 'NCHW'
  49         resample_node = Node(graph, 'resample')
  50         ResampleOp.resample_infer(resample_node)
  51         exp_shape = np.array([1, 3, 384, 512])
  52         res_shape = graph.node['node_3']['shape']
  53         for i in range(0, len(exp_shape)):
  54             self.assertEqual(exp_shape[i], res_shape[i])
  55
  56     def test_caffe_factor_infer(self):
  57         factor = 3.0
  58         graph = build_graph(nodes_attributes,
  59                             [('node_1', 'resample'),
  60                              ('resample', 'node_3'),
  61                              ('node_3', 'op_output')
  62                              ],
  63                             {'node_3': {'shape': None},
  64                              'node_1': {'shape': np.array([1, 3, 224, 227])},
  65                              'resample': {'antialias': 1,
  66                                           'resample_type': 'LINEAR',
  67                                           'factor': factor}
  68                              })
  69         graph.graph['layout'] = 'NCHW'
  70         resample_node = Node(graph, 'resample')
  71         ResampleOp.resample_infer(resample_node)
  72         exp_shape = np.array([1, 3, 224 * factor, 227 * factor])
  73         res_shape = graph.node['node_3']['shape']
  74         for i in range(0, len(exp_shape)):
  75             self.assertEqual(exp_shape[i], res_shape[i])
  76
  77     def test_tf_infer(self):
  78         new_width = 100
  79         new_height = 125
  80         new_attrs = nodes_attributes.copy()
  81         new_attrs.update({'new_shape': {'value': np.array([new_height, new_width]), 'type': 'Const', 'kind': 'op'}})
  82         graph = build_graph(new_attrs,
  83                             [('node_1', 'resample'),
  84                              ('new_shape', 'resample'),
  85                              ('resample', 'node_3'),
  86                              ('node_3', 'op_output')
  87                              ],
  88                             {'node_3': {'shape': None},
  89                              'node_1': {'shape': np.array([1, 224, 227, 3])},
  90                              'resample': {'antialias': 1,
  91                                           'resample_type': 'LINEAR',
  92                                           'factor': 1.0,
  93                                           'fw': 'tf'}
  94                              })
  95         graph.graph['layout'] = 'NHWC'
  96         resample_node = Node(graph, 'resample')
  97         ResampleOp.resample_infer(resample_node)
  98         exp_shape = np.array([1, new_height, new_width, 3])
  99         res_shape = graph.node['node_3']['shape']
 100         for i in range(0, len(exp_shape)):
 101             self.assertEqual(exp_shape[i], res_shape[i])