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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 #include "util/base/logging.h"
19 
20 namespace libtextclassifier {
21 
Extract(const std::vector<std::vector<int>> & sparse_features,const std::vector<std::vector<float>> & dense_features,const std::function<bool (const std::vector<int> &,const std::vector<float> &,float *)> & feature_vector_fn)22 void CachedFeatures::Extract(
23     const std::vector<std::vector<int>>& sparse_features,
24     const std::vector<std::vector<float>>& dense_features,
25     const std::function<bool(const std::vector<int>&, const std::vector<float>&,
26                              float*)>& feature_vector_fn) {
27   features_.resize(feature_vector_size_ * tokens_.size());
28   for (int i = 0; i < tokens_.size(); ++i) {
29     feature_vector_fn(sparse_features[i], dense_features[i],
30                       features_.data() + i * feature_vector_size_);
31   }
32 }
33 
Get(int click_pos,VectorSpan<float> * features,VectorSpan<Token> * output_tokens)34 bool CachedFeatures::Get(int click_pos, VectorSpan<float>* features,
35                          VectorSpan<Token>* output_tokens) {
36   const int token_start = click_pos - context_size_;
37   const int token_end = click_pos + context_size_ + 1;
38   if (token_start < 0 || token_end > tokens_.size()) {
39     TC_LOG(ERROR) << "Tokens out of range: " << token_start << " " << token_end;
40     return false;
41   }
42 
43   *features =
44       VectorSpan<float>(features_.begin() + token_start * feature_vector_size_,
45                         features_.begin() + token_end * feature_vector_size_);
46   *output_tokens = VectorSpan<Token>(tokens_.begin() + token_start,
47                                      tokens_.begin() + token_end);
48   if (remap_v0_feature_vector_) {
49     RemapV0FeatureVector(features);
50   }
51 
52   return true;
53 }
54 
RemapV0FeatureVector(VectorSpan<float> * features)55 void CachedFeatures::RemapV0FeatureVector(VectorSpan<float>* features) {
56   if (!remap_v0_feature_vector_) {
57     return;
58   }
59 
60   auto it = features->begin();
61   int num_suffix_features =
62       feature_vector_size_ - remap_v0_chargram_embedding_size_;
63   int num_tokens = context_size_ * 2 + 1;
64   for (int t = 0; t < num_tokens; ++t) {
65     for (int i = 0; i < remap_v0_chargram_embedding_size_; ++i) {
66       v0_feature_storage_[t * remap_v0_chargram_embedding_size_ + i] = *it;
67       ++it;
68     }
69     // Rest of the features are the dense features that come to the end.
70     for (int i = 0; i < num_suffix_features; ++i) {
71       // clang-format off
72       v0_feature_storage_[num_tokens * remap_v0_chargram_embedding_size_
73                       + t * num_suffix_features
74                       + i] = *it;
75       // clang-format on
76       ++it;
77     }
78   }
79   *features = VectorSpan<float>(v0_feature_storage_);
80 }
81 
82 }  // namespace libtextclassifier
83