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#include "translator/scorers.h"
namespace marian {
Ptr<Scorer> scorerByType(std::string fname,
float weight,
std::string model,
Ptr<Config> config) {
Ptr<Options> options = New<Options>();
options->merge(config);
options->set("inference", true);
std::string type = options->get<std::string>("type");
// @TODO: solve this better
if(type == "lm" && config->has("input")) {
size_t index = config->get<std::vector<std::string>>("input").size();
options->set("index", index);
}
auto encdec = models::from_options(options, models::usage::translation);
LOG(info, "Loading scorer of type {} as feature {}", type, fname);
return New<ScorerWrapper>(encdec, fname, weight, model);
}
std::vector<Ptr<Scorer>> createScorers(Ptr<Config> options) {
std::vector<Ptr<Scorer>> scorers;
auto models = options->get<std::vector<std::string>>("models");
int dimVocab = options->get<std::vector<int>>("dim-vocabs").back();
std::vector<float> weights(models.size(), 1.f);
if(options->has("weights"))
weights = options->get<std::vector<float>>("weights");
int i = 0;
for(auto model : models) {
std::string fname = "F" + std::to_string(i);
auto modelOptions = New<Config>(*options);
try {
if(!options->get<bool>("ignore-model-config"))
modelOptions->loadModelParameters(model);
} catch(std::runtime_error& e) {
LOG(warn, "No model settings found in model file");
}
scorers.push_back(scorerByType(fname, weights[i], model, modelOptions));
i++;
}
return scorers;
}
}
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