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/*
* 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 "common/feature-extractor.h"
#include "common/feature-types.h"
#include "common/fml-parser.h"
#include "util/base/integral_types.h"
#include "util/base/logging.h"
#include "util/gtl/stl_util.h"
#include "util/strings/numbers.h"
namespace libtextclassifier {
namespace nlp_core {
constexpr FeatureValue GenericFeatureFunction::kNone;
GenericFeatureExtractor::GenericFeatureExtractor() {}
GenericFeatureExtractor::~GenericFeatureExtractor() {}
bool GenericFeatureExtractor::Parse(const std::string &source) {
// Parse feature specification into descriptor.
FMLParser parser;
if (!parser.Parse(source, mutable_descriptor())) return false;
// Initialize feature extractor from descriptor.
if (!InitializeFeatureFunctions()) return false;
return true;
}
bool GenericFeatureExtractor::InitializeFeatureTypes() {
// Register all feature types.
GetFeatureTypes(&feature_types_);
for (size_t i = 0; i < feature_types_.size(); ++i) {
FeatureType *ft = feature_types_[i];
ft->set_base(i);
// Check for feature space overflow.
double domain_size = ft->GetDomainSize();
if (domain_size < 0) {
TC_LOG(ERROR) << "Illegal domain size for feature " << ft->name() << ": "
<< domain_size;
return false;
}
}
return true;
}
FeatureValue GenericFeatureExtractor::GetDomainSize() const {
// Domain size of the set of features is equal to:
// [largest domain size of any feature types] * [number of feature types]
FeatureValue max_feature_type_dsize = 0;
for (size_t i = 0; i < feature_types_.size(); ++i) {
FeatureType *ft = feature_types_[i];
const FeatureValue feature_type_dsize = ft->GetDomainSize();
if (feature_type_dsize > max_feature_type_dsize) {
max_feature_type_dsize = feature_type_dsize;
}
}
return max_feature_type_dsize * feature_types_.size();
}
std::string GenericFeatureFunction::GetParameter(
const std::string &name) const {
// Find named parameter in feature descriptor.
for (int i = 0; i < descriptor_->parameter_size(); ++i) {
if (name == descriptor_->parameter(i).name()) {
return descriptor_->parameter(i).value();
}
}
return "";
}
GenericFeatureFunction::GenericFeatureFunction() {}
GenericFeatureFunction::~GenericFeatureFunction() { delete feature_type_; }
int GenericFeatureFunction::GetIntParameter(const std::string &name,
int default_value) const {
int32 parsed_value = default_value;
std::string value = GetParameter(name);
if (!value.empty()) {
if (!ParseInt32(value.c_str(), &parsed_value)) {
// A parameter value has been specified, but it can't be parsed as an int.
// We don't crash: instead, we long an error and return the default value.
TC_LOG(ERROR) << "Value of param " << name << " is not an int: " << value;
}
}
return parsed_value;
}
bool GenericFeatureFunction::GetBoolParameter(const std::string &name,
bool default_value) const {
std::string value = GetParameter(name);
if (value.empty()) return default_value;
if (value == "true") return true;
if (value == "false") return false;
TC_LOG(ERROR) << "Illegal value '" << value << "' for bool parameter '"
<< name << "'"
<< " will assume default " << default_value;
return default_value;
}
void GenericFeatureFunction::GetFeatureTypes(
std::vector<FeatureType *> *types) const {
if (feature_type_ != nullptr) types->push_back(feature_type_);
}
FeatureType *GenericFeatureFunction::GetFeatureType() const {
// If a single feature type has been registered return it.
if (feature_type_ != nullptr) return feature_type_;
// Get feature types for function.
std::vector<FeatureType *> types;
GetFeatureTypes(&types);
// If there is exactly one feature type return this, else return null.
if (types.size() == 1) return types[0];
return nullptr;
}
std::string GenericFeatureFunction::name() const {
std::string output;
if (descriptor_->name().empty()) {
if (!prefix_.empty()) {
output.append(prefix_);
output.append(".");
}
ToFML(*descriptor_, &output);
} else {
output = descriptor_->name();
}
return output;
}
} // namespace nlp_core
} // namespace libtextclassifier