blob: c249db966317278d98f12ff098ebcdf7ad36ef49 [file] [log] [blame]
/*
* Copyright (C) 2017 The Android Open Source Project
*
* 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.
*/
#include "smartselect/cached-features.h"
#include "util/base/logging.h"
namespace libtextclassifier {
void CachedFeatures::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) {
features_.resize(feature_vector_size_ * tokens_.size());
for (int i = 0; i < tokens_.size(); ++i) {
feature_vector_fn(sparse_features[i], dense_features[i],
features_.data() + i * feature_vector_size_);
}
}
bool CachedFeatures::Get(int click_pos, VectorSpan<float>* features,
VectorSpan<Token>* output_tokens) {
const int token_start = click_pos - context_size_;
const int token_end = click_pos + context_size_ + 1;
if (token_start < 0 || token_end > tokens_.size()) {
TC_LOG(ERROR) << "Tokens out of range: " << token_start << " " << token_end;
return false;
}
*features =
VectorSpan<float>(features_.begin() + token_start * feature_vector_size_,
features_.begin() + token_end * feature_vector_size_);
*output_tokens = VectorSpan<Token>(tokens_.begin() + token_start,
tokens_.begin() + token_end);
if (remap_v0_feature_vector_) {
RemapV0FeatureVector(features);
}
return true;
}
void CachedFeatures::RemapV0FeatureVector(VectorSpan<float>* features) {
if (!remap_v0_feature_vector_) {
return;
}
auto it = features->begin();
int num_suffix_features =
feature_vector_size_ - remap_v0_chargram_embedding_size_;
int num_tokens = context_size_ * 2 + 1;
for (int t = 0; t < num_tokens; ++t) {
for (int i = 0; i < remap_v0_chargram_embedding_size_; ++i) {
v0_feature_storage_[t * remap_v0_chargram_embedding_size_ + i] = *it;
++it;
}
// Rest of the features are the dense features that come to the end.
for (int i = 0; i < num_suffix_features; ++i) {
// clang-format off
v0_feature_storage_[num_tokens * remap_v0_chargram_embedding_size_
+ t * num_suffix_features
+ i] = *it;
// clang-format on
++it;
}
}
*features = VectorSpan<float>(v0_feature_storage_);
}
} // namespace libtextclassifier