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  # Copyright 2015 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 PrecisionOp."""
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import numpy as np
  
  from tensorflow.python.framework import constant_op
  from tensorflow.python.ops import nn_ops
  from tensorflow.python.platform import test
  
  
  class InTopKTest(test.TestCase):
  
    def _validateInTopK(self, predictions, target, k, expected):
      np_ans = np.array(expected)
      with self.cached_session(use_gpu=True):
        precision = nn_ops.in_top_k(predictions, target, k)
        out = self.evaluate(precision)
  =======
  """Tests for PrecisionOp."""
  import tensorflow.python.platform
  
  import numpy as np
  import tensorflow as tf
  
  
  class InTopKTest(tf.test.TestCase):
  
    def _validateInTopK(self, predictions, target, k, expected):
      np_ans = np.array(expected)
      with self.test_session():
        precision = tf.nn.in_top_k(predictions, target, k)
        out = precision.eval()
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        self.assertAllClose(np_ans, out)
        self.assertShapeEqual(np_ans, precision)
  
    def testInTop1(self):
      predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
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      target = [3, 2]
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      target = [3, 1]
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      self._validateInTopK(predictions, target, 1, [True, False])
  
    def testInTop2(self):
      predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
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      target = [2, 2]
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      target = [0, 2]
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      self._validateInTopK(predictions, target, 2, [False, True])
  
    def testInTop2Tie(self):
      # Class 2 and 3 tie for 2nd, so both are considered in top 2.
      predictions = [[0.1, 0.3, 0.2, 0.2], [0.1, 0.3, 0.2, 0.2]]
      target = [2, 3]
      self._validateInTopK(predictions, target, 2, [True, True])
  
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    def testInTop2_int64Target(self):
      predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
      target = np.asarray([0, 2]).astype(np.int64)
      self._validateInTopK(predictions, target, 2, [False, True])
  
    def testInTopNan(self):
      predictions = [[0.1, float("nan"), 0.2, 0.4], [0.1, 0.2, 0.3, float("inf")]]
      target = [1, 3]
      self._validateInTopK(predictions, target, 2, [False, False])
  
    def testBadTarget(self):
      predictions = [[0.1, 0.3, 0.2, 0.2], [0.1, 0.3, 0.2, 0.2]]
      target = [2, 4]  # must return False for invalid target
      self._validateInTopK(predictions, target, 2, [True, False])
  
    def testTensorK(self):
      predictions = [[0.1, 0.3, 0.2, 0.4], [0.1, 0.2, 0.3, 0.4]]
      target = [0, 2]
      k = constant_op.constant(3)
      np_ans = np.array([False, True])
      with self.cached_session():
        precision = nn_ops.in_top_k(predictions, target, k)
        out = self.evaluate(precision)
        self.assertAllClose(np_ans, out)
        self.assertShapeEqual(np_ans, precision)
  
  
  if __name__ == "__main__":
    test.main()
  =======
  
  if __name__ == "__main__":
    tf.test.main()
  >>>>>>> f41959ccb2... TensorFlow: Initial commit of TensorFlow library.
  