text: """
   Copyright (C) 2018-2021 Intel Corporation
  
   Licensed under the Apache License, Version 2.0 (the "License");
   you may not use this file except in compliance with the License.
   You may obtain a copy of the License at
  
        http://www.apache.org/licenses/LICENSE-2.0
  
   Unless required by applicable law or agreed to in writing, software
   distributed under the License is distributed on an "AS IS" BASIS,
   WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
   See the License for the specific language governing permissions and
   limitations under the License.
  """
  
  import unittest
  from unittest.mock import MagicMock
  
  import numpy as np
  
  from mo.front.common.partial_infer.caffe_fallback import build_net
  from mo.utils.unittest.extractors import FakeMultiParam, FakeValue
  from mo.utils.unittest.graph import build_graph
  
  
  class Net:
      def __init__(self, blobs):
          self.blobs = blobs
          self.reshape_blob = MagicMock(return_value=np.array([1, 1, 1, 1]))
          self.reshape = MagicMock(return_value=np.array([1, 1, 1, 1]))
          self.forward = MagicMock(return_value={'top_node': FakeValue(np.array([1, 3, 112, 112]))})
  
  
  my_mock_net = None
  
  
  class Caffe:
      def __init__(self):
          self.TEST = 'TEST'
  
      def Net(self, *args):
          return my_mock_net
  
  
  class TestCaffeNativePartialInfer(unittest.TestCase):
      @classmethod
      def setUpClass(cls):
          import sys
          sys.modules['caffe'] = Caffe()
          cls.nodes_attributes = {
              'node_1': {'type': 'Parameter', 'kind': 'op'},
              'node_2': {'type': 'Parameter', 'kind': 'op'},
              'node_3': {'type': 'Identity', 'kind': 'op'},
              'node_4': {'type': 'Identity', 'kind': 'op'},
              'op_output': { 'kind': 'op', 'op': 'Result'}
          }
  
      def test_build_net_equal_inputs(self):
          global my_mock_net
          my_blobs = {
              'node_1': FakeValue(np.array([1, 3, 227, 227])),
              'node_2': FakeValue(np.array([1, 3, 224, 224]))
          }
          my_mock_net = Net(my_blobs)
          graph = build_graph(self.nodes_attributes,
                              [
                                  ('node_1', 'node_3'),
                                  ('node_2', 'node_3'),
                                  ('node_3', 'node_4'),
                                  ('node_4', 'op_output')
                              ],
                              {
                                  'node_4': {'shape': None},
                                  'node_1': {'shape': np.array([1, 3, 227, 227])},
                                  'node_2': {'shape': np.array([1, 3, 224, 224])},
                                  'node_3': {'top': 'top_node'}
                              })
          graph.proto_path = 'path_to_proto'
          graph.caffemodel_path = 'path_to_proto'
          build_net(graph)
          my_mock_net.reshape.assert_not_called()
          my_mock_net.forward.assert_called_once_with()
          self.assertIsNotNone(graph.caffe_net)
  
      def test_build_net_not_equal_inputs(self):
          global my_mock_net
          input_node_param = {
              'shape': np.array([1, 3, 112, 112]),
              'reshape': MagicMock(return_value=134)
          }
          my_blobs = {
              'node_1': FakeMultiParam(input_node_param),
          }
          my_mock_net = Net(my_blobs)
          graph = build_graph(self.nodes_attributes,
                              [
                                  ('node_1', 'node_3'),
                                  ('node_3', 'node_4'),
                                  ('node_4', 'op_output')
                              ],
                              {'node_4': {'shape': None},
                               'node_1': {'shape': np.array([1, 3, 227, 227])},
                               'node_3': {'top': 'top_node'}
                               },
                              nodes_with_edges_only=True)
          graph.proto_path = 'path_to_proto'
          graph.caffemodel_path = 'path_to_proto'
          build_net(graph)
          my_mock_net.reshape.assert_called_once_with()
          my_mock_net.forward.assert_called_once_with()
          self.assertIsNotNone(graph.caffe_net)
  