google-research

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# coding=utf-8
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# Copyright 2024 The Google Research Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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#     http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Tests for negative_cache.util."""
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import tensorflow.compat.v2 as tf
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from negative_cache import util
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class LossesTest(tf.test.TestCase):
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  def test_approximate_top_k_with_indices(self):
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    negative_scores = tf.convert_to_tensor([[1.0, 2.0, 3.0, 4.0],
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                                            [2.0, 1.0, 3.0, 4.0],
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                                            [4.0, 1.0, 3.0, 2.0]])
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    top_k_scores, top_k_indices = util.approximate_top_k_with_indices(
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        negative_scores, k=2)
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    top_k_scores_expected = tf.convert_to_tensor([[2.0, 4.0], [2.0, 4.0],
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                                                  [4.0, 3.0]])
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    top_k_indices_expected = tf.convert_to_tensor([[1, 3], [0, 3], [0, 2]])
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    self.assertAllClose(top_k_scores_expected, top_k_scores)
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    self.assertAllEqual(top_k_indices_expected, top_k_indices)
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if __name__ == '__main__':
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  tf.enable_v2_behavior()
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  tf.test.main()
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