text: # Copyright 2017 The TensorFlow Authors. All Rights Reserved.
  #
  # 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.
  # ==============================================================================
  
  """Tests for object_detection.core.bipartite_matcher."""
  
  import tensorflow as tf
  
  from object_detection.matchers import bipartite_matcher
  
  
  class GreedyBipartiteMatcherTest(tf.test.TestCase):
  
    def test_get_expected_matches_when_all_rows_are_valid(self):
      similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
      num_valid_rows = 2
      expected_match_results = [-1, 1, 0]
  
      matcher = bipartite_matcher.GreedyBipartiteMatcher()
      match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
      with self.test_session() as sess:
        match_results_out = sess.run(match._match_results)
        self.assertAllEqual(match_results_out, expected_match_results)
  
    def test_get_expected_matches_with_valid_rows_set_to_minus_one(self):
      similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
      num_valid_rows = -1
      expected_match_results = [-1, 1, 0]
  
      matcher = bipartite_matcher.GreedyBipartiteMatcher()
      match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
      with self.test_session() as sess:
        match_results_out = sess.run(match._match_results)
        self.assertAllEqual(match_results_out, expected_match_results)
  
    def test_get_no_matches_with_zero_valid_rows(self):
      similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
      num_valid_rows = 0
      expected_match_results = [-1, -1, -1]
  
      matcher = bipartite_matcher.GreedyBipartiteMatcher()
      match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
      with self.test_session() as sess:
        match_results_out = sess.run(match._match_results)
        self.assertAllEqual(match_results_out, expected_match_results)
  
    def test_get_expected_matches_with_only_one_valid_row(self):
      similarity_matrix = tf.constant([[0.50, 0.1, 0.8], [0.15, 0.2, 0.3]])
      num_valid_rows = 1
      expected_match_results = [-1, -1, 0]
  
      matcher = bipartite_matcher.GreedyBipartiteMatcher()
      match = matcher.match(similarity_matrix, num_valid_rows=num_valid_rows)
      with self.test_session() as sess:
        match_results_out = sess.run(match._match_results)
        self.assertAllEqual(match_results_out, expected_match_results)
  
  
  if __name__ == '__main__':
    tf.test.main()
  