model-optimizer/mo/ops/power_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 mo.graph.graph import Node
  22 from mo.ops.power import Power
  23 from mo.utils.unittest.graph import build_graph
  24
  25
  26 class TestPowerOp(unittest.TestCase):
  27     @staticmethod
  28     def create_graph(single_input=True):
  29         nodes_attributes = {
  30             'input1': {
  31                 'kind': 'data',
  32                 'shape': np.array([1, 3, 224, 224]),
  33                 'value': None,
  34             },
  35             'input2': {
  36                 'kind': 'data',
  37                 'shape': np.array([]),
  38                 'value': np.array(1.0),
  39             },
  40             'power': {
  41                 'kind': 'op',
  42                 'shape': np.array([1, 3, 224, 224]),
  43             },
  44             'power_data': {
  45                 'kind': 'data',
  46                 'shape': None,
  47             },
  48         }
  49         if single_input:
  50             return build_graph(nodes_attributes,
  51                                [
  52                                    ('input1', 'power'),
  53                                    ('power', 'power_data')
  54                                ])
  55         else:
  56             return build_graph(nodes_attributes,
  57                                [
  58                                    ('input1', 'power'),
  59                                    ('input2', 'power'),
  60                                    ('power', 'power_data')
  61                                ])
  62
  63     def test_power_single_input_infer1(self):
  64         graph = self.create_graph(single_input=True)
  65         graph.graph['layout'] = 'NCHW'
  66         power_node = Node(graph, 'power')
  67         power_node['power'] = 1.0
  68
  69         Power.infer(power_node)
  70
  71         self.assertTrue(np.array_equal(power_node.out_node().shape, power_node.in_node(0).shape))
  72
  73     def test_power_two_input_infer1(self):
  74         graph = self.create_graph(single_input=False)
  75         graph.graph['layout'] = 'NCHW'
  76         power_node = Node(graph, 'power')
  77
  78         Power.infer(power_node)
  79
  80         self.assertTrue(np.array_equal(power_node.out_node().shape, power_node.in_node(0).shape))
  81
  82     def test_power_two_input_infer2(self):
  83         graph = self.create_graph(single_input=False)
  84         power_node = Node(graph, 'power')
  85         input2 = Node(graph, 'input2')
  86         input2.value = np.ones((1, 2, 3))
  87
  88         Power.infer(power_node)
  89
  90         self.assertIsNone(power_node.out_node().shape)
  91
  92     def test_power_two_input_infer3(self):
  93         graph = self.create_graph(single_input=False)
  94         power_node = Node(graph, 'power')
  95         input2 = Node(graph, 'input2')
  96         input2.value = None
  97
  98         Power.infer(power_node)
  99
 100         self.assertIsNone(power_node.out_node().shape)