91 lines
3 KiB
C++
91 lines
3 KiB
C++
/*
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* Copyright (C) 2017 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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#include "lang_id/relevant-script-feature.h"
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#include <string>
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#include "common/feature-extractor.h"
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#include "common/feature-types.h"
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#include "common/task-context.h"
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#include "common/workspace.h"
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#include "lang_id/script-detector.h"
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#include "util/base/logging.h"
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#include "util/strings/utf8.h"
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namespace libtextclassifier {
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namespace nlp_core {
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namespace lang_id {
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bool RelevantScriptFeature::Setup(TaskContext *context) { return true; }
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bool RelevantScriptFeature::Init(TaskContext *context) {
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set_feature_type(new NumericFeatureType(name(), kNumRelevantScripts));
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return true;
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}
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void RelevantScriptFeature::Evaluate(const WorkspaceSet &workspaces,
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const LightSentence &sentence,
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FeatureVector *result) const {
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// We expect kNumRelevantScripts to be small, so we stack-allocate the array
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// of counts. Still, if that changes, we want to find out.
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static_assert(
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kNumRelevantScripts < 25,
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"switch counts to vector<int>: too big for stack-allocated int[]");
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// counts[s] is the number of characters with script s.
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// Note: {} "value-initializes" the array to zero.
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int counts[kNumRelevantScripts]{};
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int total_count = 0;
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for (int i = 0; i < sentence.num_words(); ++i) {
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const std::string &word = sentence.word(i);
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const char *const word_end = word.data() + word.size();
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const char *curr = word.data();
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// Skip over token start '^'.
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TC_DCHECK_EQ(*curr, '^');
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curr += GetNumBytesForNonZeroUTF8Char(curr);
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while (true) {
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const int num_bytes = GetNumBytesForNonZeroUTF8Char(curr);
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Script script = GetScript(curr, num_bytes);
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// We do this update and the if (...) break below *before* incrementing
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// counts[script] in order to skip the token end '$'.
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curr += num_bytes;
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if (curr >= word_end) {
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TC_DCHECK_EQ(*(curr - num_bytes), '$');
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break;
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}
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TC_DCHECK_GE(script, 0);
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TC_DCHECK_LT(script, kNumRelevantScripts);
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counts[script]++;
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total_count++;
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}
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}
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for (int script_id = 0; script_id < kNumRelevantScripts; ++script_id) {
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int count = counts[script_id];
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if (count > 0) {
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const float weight = static_cast<float>(count) / total_count;
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FloatFeatureValue value(script_id, weight);
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result->add(feature_type(), value.discrete_value);
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}
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}
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}
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} // namespace lang_id
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} // namespace nlp_core
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} // namespace libtextclassifier
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