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1# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
2#
3# Licensed under the Apache License, Version 2.0 (the "License");
4# you may not use this file except in compliance with the License.
5# You may obtain a copy of the License at
6#
7#     http://www.apache.org/licenses/LICENSE-2.0
8#
9# Unless required by applicable law or agreed to in writing, software
10# distributed under the License is distributed on an "AS IS" BASIS,
11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12# See the License for the specific language governing permissions and
13# limitations under the License.
14# ==============================================================================
15"""Tests for DecodeLibsvm op."""
16
17from __future__ import absolute_import
18from __future__ import division
19from __future__ import print_function
20
21import numpy as np
22
23from tensorflow.contrib.libsvm.python.ops import libsvm_ops
24from tensorflow.python.framework import dtypes
25from tensorflow.python.ops import sparse_ops
26from tensorflow.python.platform import test
27
28
29class DecodeLibsvmOpTest(test.TestCase):
30
31  def testBasic(self):
32    with self.cached_session() as sess:
33      content = [
34          "1 1:3.4 2:0.5 4:0.231", "1 2:2.5 3:inf 5:0.503",
35          "2 3:2.5 2:nan 1:0.105"
36      ]
37      sparse_features, labels = libsvm_ops.decode_libsvm(
38          content, num_features=6)
39      features = sparse_ops.sparse_tensor_to_dense(
40          sparse_features, validate_indices=False)
41
42      self.assertAllEqual(labels.get_shape().as_list(), [3])
43
44      features, labels = sess.run([features, labels])
45      self.assertAllEqual(labels, [1, 1, 2])
46      self.assertAllClose(
47          features, [[0, 3.4, 0.5, 0, 0.231, 0], [0, 0, 2.5, np.inf, 0, 0.503],
48                     [0, 0.105, np.nan, 2.5, 0, 0]])
49
50  def testNDimension(self):
51    with self.cached_session() as sess:
52      content = [["1 1:3.4 2:0.5 4:0.231", "1 1:3.4 2:0.5 4:0.231"],
53                 ["1 2:2.5 3:inf 5:0.503", "1 2:2.5 3:inf 5:0.503"],
54                 ["2 3:2.5 2:nan 1:0.105", "2 3:2.5 2:nan 1:0.105"]]
55      sparse_features, labels = libsvm_ops.decode_libsvm(
56          content, num_features=6, label_dtype=dtypes.float64)
57      features = sparse_ops.sparse_tensor_to_dense(
58          sparse_features, validate_indices=False)
59
60      self.assertAllEqual(labels.get_shape().as_list(), [3, 2])
61
62      features, labels = sess.run([features, labels])
63      self.assertAllEqual(labels, [[1, 1], [1, 1], [2, 2]])
64      self.assertAllClose(
65          features, [[[0, 3.4, 0.5, 0, 0.231, 0], [0, 3.4, 0.5, 0, 0.231, 0]], [
66              [0, 0, 2.5, np.inf, 0, 0.503], [0, 0, 2.5, np.inf, 0, 0.503]
67          ], [[0, 0.105, np.nan, 2.5, 0, 0], [0, 0.105, np.nan, 2.5, 0, 0]]])
68
69
70if __name__ == "__main__":
71  test.main()
72