1 /*
2 * Copyright (C) 2017 The Android Open Source Project
3 *
4 * Licensed under the Apache License, Version 2.0 (the "License");
5 * you may not use this file except in compliance with the License.
6 * You may obtain a copy of the License at
7 *
8 * http://www.apache.org/licenses/LICENSE-2.0
9 *
10 * Unless required by applicable law or agreed to in writing, software
11 * distributed under the License is distributed on an "AS IS" BASIS,
12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13 * See the License for the specific language governing permissions and
14 * limitations under the License.
15 */
16
17 #include "smartselect/cached-features.h"
18
19 #include "gmock/gmock.h"
20 #include "gtest/gtest.h"
21
22 namespace libtextclassifier {
23 namespace {
24
25 class TestingCachedFeatures : public CachedFeatures {
26 public:
27 using CachedFeatures::CachedFeatures;
28 using CachedFeatures::RemapV0FeatureVector;
29 };
30
TEST(CachedFeaturesTest,Simple)31 TEST(CachedFeaturesTest, Simple) {
32 std::vector<Token> tokens;
33 tokens.push_back(Token());
34 tokens.push_back(Token());
35 tokens.push_back(Token("Hello", 0, 1));
36 tokens.push_back(Token("World", 1, 2));
37 tokens.push_back(Token("today!", 2, 3));
38 tokens.push_back(Token());
39 tokens.push_back(Token());
40
41 std::vector<std::vector<int>> sparse_features(tokens.size());
42 for (int i = 0; i < sparse_features.size(); ++i) {
43 sparse_features[i].push_back(i);
44 }
45 std::vector<std::vector<float>> dense_features(tokens.size());
46 for (int i = 0; i < dense_features.size(); ++i) {
47 dense_features[i].push_back(-i);
48 }
49
50 TestingCachedFeatures feature_extractor(
51 tokens, /*context_size=*/2, sparse_features, dense_features,
52 [](const std::vector<int>& sparse_features,
53 const std::vector<float>& dense_features, float* features) {
54 features[0] = sparse_features[0];
55 features[1] = sparse_features[0];
56 features[2] = dense_features[0];
57 features[3] = dense_features[0];
58 features[4] = 123;
59 return true;
60 },
61 5);
62
63 VectorSpan<float> features;
64 VectorSpan<Token> output_tokens;
65 EXPECT_TRUE(feature_extractor.Get(2, &features, &output_tokens));
66 for (int i = 0; i < 5; i++) {
67 EXPECT_EQ(features[i * 5 + 0], i) << "Feature " << i;
68 EXPECT_EQ(features[i * 5 + 1], i) << "Feature " << i;
69 EXPECT_EQ(features[i * 5 + 2], -i) << "Feature " << i;
70 EXPECT_EQ(features[i * 5 + 3], -i) << "Feature " << i;
71 EXPECT_EQ(features[i * 5 + 4], 123) << "Feature " << i;
72 }
73 }
74
TEST(CachedFeaturesTest,InvalidInput)75 TEST(CachedFeaturesTest, InvalidInput) {
76 std::vector<Token> tokens;
77 tokens.push_back(Token());
78 tokens.push_back(Token());
79 tokens.push_back(Token("Hello", 0, 1));
80 tokens.push_back(Token("World", 1, 2));
81 tokens.push_back(Token("today!", 2, 3));
82 tokens.push_back(Token());
83 tokens.push_back(Token());
84
85 std::vector<std::vector<int>> sparse_features(tokens.size());
86 std::vector<std::vector<float>> dense_features(tokens.size());
87
88 TestingCachedFeatures feature_extractor(
89 tokens, /*context_size=*/2, sparse_features, dense_features,
90 [](const std::vector<int>& sparse_features,
91 const std::vector<float>& dense_features,
92 float* features) { return true; },
93 /*feature_vector_size=*/5);
94
95 VectorSpan<float> features;
96 VectorSpan<Token> output_tokens;
97 EXPECT_FALSE(feature_extractor.Get(-1000, &features, &output_tokens));
98 EXPECT_FALSE(feature_extractor.Get(-1, &features, &output_tokens));
99 EXPECT_FALSE(feature_extractor.Get(0, &features, &output_tokens));
100 EXPECT_TRUE(feature_extractor.Get(2, &features, &output_tokens));
101 EXPECT_TRUE(feature_extractor.Get(4, &features, &output_tokens));
102 EXPECT_FALSE(feature_extractor.Get(5, &features, &output_tokens));
103 EXPECT_FALSE(feature_extractor.Get(500, &features, &output_tokens));
104 }
105
TEST(CachedFeaturesTest,RemapV0FeatureVector)106 TEST(CachedFeaturesTest, RemapV0FeatureVector) {
107 std::vector<Token> tokens;
108 tokens.push_back(Token());
109 tokens.push_back(Token());
110 tokens.push_back(Token("Hello", 0, 1));
111 tokens.push_back(Token("World", 1, 2));
112 tokens.push_back(Token("today!", 2, 3));
113 tokens.push_back(Token());
114 tokens.push_back(Token());
115
116 std::vector<std::vector<int>> sparse_features(tokens.size());
117 std::vector<std::vector<float>> dense_features(tokens.size());
118
119 TestingCachedFeatures feature_extractor(
120 tokens, /*context_size=*/2, sparse_features, dense_features,
121 [](const std::vector<int>& sparse_features,
122 const std::vector<float>& dense_features,
123 float* features) { return true; },
124 /*feature_vector_size=*/5);
125
126 std::vector<float> features_orig(5 * 5);
127 for (int i = 0; i < features_orig.size(); i++) {
128 features_orig[i] = i;
129 }
130 VectorSpan<float> features;
131
132 feature_extractor.SetV0FeatureMode(0);
133 features = VectorSpan<float>(features_orig);
134 feature_extractor.RemapV0FeatureVector(&features);
135 EXPECT_EQ(
136 std::vector<float>({0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
137 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24}),
138 std::vector<float>(features.begin(), features.end()));
139
140 feature_extractor.SetV0FeatureMode(2);
141 features = VectorSpan<float>(features_orig);
142 feature_extractor.RemapV0FeatureVector(&features);
143 EXPECT_EQ(std::vector<float>({0, 1, 5, 6, 10, 11, 15, 16, 20, 21, 2, 3, 4,
144 7, 8, 9, 12, 13, 14, 17, 18, 19, 22, 23, 24}),
145 std::vector<float>(features.begin(), features.end()));
146 }
147
148 } // namespace
149 } // namespace libtextclassifier
150