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src/ivectorbin/logistic-regression-copy.cc
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// ivectorbin/logistic-regression-copy.cc
// Copyright 2014 Daniel Povey
// See ../../COPYING for clarification regarding multiple authors
//
// 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
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "ivector/logistic-regression.h"
int main(int argc, char *argv[]) {
using namespace kaldi;
typedef kaldi::int32 int32;
try {
const char *usage =
"Copy a logistic-regression model, possibly changing the binary mode;
"
"also supports the --scale-priors option which can scale the prior probabilities
"
"the model assigns to different classes (e.g., you can remove the effect of
"
"unbalanced training data by scaling by the inverse of the class priors in the
"
"training data)
"
"Usage: logistic-regression-copy [options] <model-in> <model-out>
"
"e.g.: echo '[ 2.6 1.7 3.9 1.24 7.5 ]' | logistic-regression-copy --scale-priors=- \\
"
" 1.model scaled_priors.mdl
";
ParseOptions po(usage);
bool binary = true;
std::string scale_priors_rxfilename;
po.Register("binary", &binary, "Write output in binary mode");
po.Register("scale-priors", &scale_priors_rxfilename, "(extended) filename for file "
"containing a vector of prior-scales (e.g. inverses of training priors)");
po.Read(argc, argv);
if (po.NumArgs() != 2) {
po.PrintUsage();
exit(1);
}
std::string model_rxfilename = po.GetArg(1),
model_wxfilename = po.GetArg(2);
LogisticRegression model;
ReadKaldiObject(model_rxfilename, &model);
if (scale_priors_rxfilename != "") {
Vector<BaseFloat> prior_scales;
ReadKaldiObject(scale_priors_rxfilename, &prior_scales);
model.ScalePriors(prior_scales);
}
WriteKaldiObject(model, model_wxfilename, binary);
KALDI_LOG << "Wrote model to " << PrintableWxfilename(model_wxfilename);
return 0;
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}
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