model-optimizer/extensions/ops/merge_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 import numpy as np
  19
  20 from extensions.ops.merge import Merge
  21 from mo.graph.graph import Node
  22 from mo.utils.unittest.graph import build_graph_with_attrs, compare_graphs
  23
  24
  25 class TestMerge(unittest.TestCase):
  26     nodes = [
  27         ('first', {'value': np.ones((2, 2)), 'kind': 'data', 'executable': True, 'shape': np.array([2, 2]),
  28                    'is_partial_inferred': True}),
  29         ('second', {'value': np.zeros((2, 2)), 'kind': 'data', 'executable': False, 'shape': np.array([2, 2]),
  30                     'is_partial_inferred': True}),
  31         ('merge', {'type': 'Merge', 'kind': 'op', 'op': 'Merge'}),
  32         ('merge_output', {'value': None, 'kind': 'data', 'executable': True, 'shape': None}),
  33     ]
  34     edges = [
  35         ('first', 'merge', {'in': 0}),
  36         ('second', 'merge', {'in': 1}),
  37         ('merge', 'merge_output', {'out': 0}),
  38     ]
  39
  40     def test_merge_infer_simple_case_one_executable(self):
  41         graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges)
  42
  43         # We should propagate value of the first input since only this input is executable
  44         graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes,
  45                                            edges_with_attrs=self.edges,
  46                                            update_nodes_attributes=[('merge_output', {'shape': np.array([2, 2]),
  47                                                                                       'value': np.ones((2,2))}),
  48                                                                     ('merge', {'is_not_fully_inferred': False})])
  49
  50         tested_class = Merge(graph=graph, attrs={})
  51         node = Node(graph, 'merge')
  52         tested_class.merge_infer(node)
  53
  54         (flag, resp) = compare_graphs(graph, graph_ref, 'merge_output', check_op_attrs=True)
  55         self.assertTrue(flag, resp)
  56
  57     def test_merge_infer_complex_case(self):
  58         """
  59         Case as in cycles when in first visit only one input are inferred and in the second -- both.
  60         """
  61         graph = build_graph_with_attrs(nodes_with_attrs=self.nodes, edges_with_attrs=self.edges,
  62                                        update_nodes_attributes=[('first', {'is_partial_inferred': False,
  63                                                                            'value': None}),
  64                                                                 ('second', {'executable': True})])
  65
  66         # In first visit we should propagate only shapes
  67         graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes,
  68                                            edges_with_attrs=self.edges,
  69                                            update_nodes_attributes=[('second', {'executable': True}),
  70                                                                     ('first', {'is_partial_inferred': False,
  71                                                                                 'value': None}),
  72                                                                     ('merge_output', {'shape': np.array([2, 2]),
  73                                                                                       'value': None}),
  74                                                                     ('merge', {'is_not_fully_inferred': True})])
  75         tested_class = Merge(graph=graph, attrs={})
  76         node = Node(graph, 'merge')
  77         tested_class.merge_infer(node)
  78
  79         (flag, resp) = compare_graphs(graph, graph_ref, 'merge_output', check_op_attrs=True)
  80         self.assertTrue(flag, resp)
  81
  82         # Imitate that inputs nodes now is inferred
  83         graph.node['first']['is_partial_inferred'] = True
  84
  85         # Run infer second time
  86         tested_class = Merge(graph=graph, attrs={})
  87         node = Node(graph, 'merge')
  88         tested_class.merge_infer(node)
  89
  90         graph_ref = build_graph_with_attrs(nodes_with_attrs=self.nodes,
  91                                            edges_with_attrs=self.edges,
  92                                            update_nodes_attributes=[('second', {'executable': True}),
  93                                                                     ('first', {'is_partial_inferred': True,
  94                                                                                'value': None}),
  95                                                                     ('merge_output', {'shape': np.array([2, 2]),
  96                                                                                       'value': None}),
  97                                                                     ('merge', {'is_not_fully_inferred': False})])
  98         (flag, resp) = compare_graphs(graph, graph_ref, 'merge_output', check_op_attrs=True)
  99         self.assertTrue(flag, resp)