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/*
* Copyright (C) 2018 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 "lang_id/features/relevant-script-feature.h"
#include <string>
#include <vector>
#include "lang_id/common/fel/feature-types.h"
#include "lang_id/common/fel/task-context.h"
#include "lang_id/common/fel/workspace.h"
#include "lang_id/common/lite_base/logging.h"
#include "lang_id/common/utf8.h"
#include "lang_id/script/script-detector.h"
namespace libtextclassifier3 {
namespace mobile {
namespace lang_id {
bool RelevantScriptFeature::Setup(TaskContext *context) {
std::string script_detector_name = GetParameter(
"script_detector_name", /* default_value = */ "tiny-script-detector");
// We don't use absl::WrapUnique, nor the rest of absl, see http://b/71873194
script_detector_.reset(ScriptDetector::Create(script_detector_name));
if (script_detector_ == nullptr) {
// This means ScriptDetector::Create() could not find the requested
// script_detector_name. In that case, Create() already logged an error
// message.
return false;
}
// We use default value 172 because this is the number of scripts supported by
// the first model we trained with this feature. See http://b/70617713.
// Newer models may support more scripts.
num_supported_scripts_ = GetIntParameter("num_supported_scripts", 172);
return true;
}
bool RelevantScriptFeature::Init(TaskContext *context) {
set_feature_type(new NumericFeatureType(name(), num_supported_scripts_));
return true;
}
void RelevantScriptFeature::Evaluate(
const WorkspaceSet &workspaces, const LightSentence &sentence,
FeatureVector *result) const {
// counts[s] is the number of characters with script s.
std::vector<int> counts(num_supported_scripts_);
int total_count = 0;
for (const std::string &word : sentence) {
const char *const word_end = word.data() + word.size();
const char *curr = word.data();
// Skip over token start '^'.
SAFTM_DCHECK_EQ(*curr, '^');
curr += utils::OneCharLen(curr);
while (true) {
const int num_bytes = utils::OneCharLen(curr);
int script = script_detector_->GetScript(curr, num_bytes);
// We do this update and the if (...) break below *before* incrementing
// counts[script] in order to skip the token end '$'.
curr += num_bytes;
if (curr >= word_end) {
SAFTM_DCHECK_EQ(*(curr - num_bytes), '$');
break;
}
SAFTM_DCHECK_GE(script, 0);
if (script < num_supported_scripts_) {
counts[script]++;
total_count++;
} else {
// Unsupported script: this usually indicates a script that is
// recognized by newer versions of the code, after the model was
// trained. E.g., new code running with old model.
}
}
}
for (int script_id = 0; script_id < num_supported_scripts_; ++script_id) {
int count = counts[script_id];
if (count > 0) {
const float weight = static_cast<float>(count) / total_count;
FloatFeatureValue value(script_id, weight);
result->add(feature_type(), value.discrete_value);
}
}
}
SAFTM_STATIC_REGISTRATION(RelevantScriptFeature);
} // namespace lang_id
} // namespace mobile
} // namespace nlp_saft
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