# Copyright 2017 Google Inc.
#
# 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 utility functions."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import numpy as np
import tensorflow as tf

from dnc import util

try:
  xrange
except NameError:
  xrange = range


class BatchInvertPermutation(tf.test.TestCase):

  def test(self):
    # Tests that the _batch_invert_permutation function correctly inverts a
    # batch of permutations.
    batch_size = 5
    length = 7

    permutations = np.empty([batch_size, length], dtype=int)
    for i in xrange(batch_size):
      permutations[i] = np.random.permutation(length)

    inverse = util.batch_invert_permutation(tf.constant(permutations, tf.int32))
    with self.test_session():
      inverse = inverse.eval()

    for i in xrange(batch_size):
      for j in xrange(length):
        self.assertEqual(permutations[i][inverse[i][j]], j)


class BatchGather(tf.test.TestCase):

  def test(self):
    values = np.array([[3, 1, 4, 1], [5, 9, 2, 6], [5, 3, 5, 7]])
    indexs = np.array([[1, 2, 0, 3], [3, 0, 1, 2], [0, 2, 1, 3]])
    target = np.array([[1, 4, 3, 1], [6, 5, 9, 2], [5, 5, 3, 7]])
    result = util.batch_gather(tf.constant(values), tf.constant(indexs))
    with self.test_session():
      result = result.eval()
    self.assertAllEqual(target, result)


if __name__ == '__main__':
  tf.test.main()
