nnet-to-raw-nnet.cc
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// nnet2bin/nnet-to-raw-nnet.cc
// Copyright 2013 Johns Hopkins University (author: 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 "nnet2/am-nnet.h"
#include "hmm/transition-model.h"
#include "tree/context-dep.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using namespace kaldi::nnet2;
typedef kaldi::int32 int32;
const char *usage =
"Copy a (cpu-based) neural net: reads the AmNnet with its transition model, but\n"
"writes just the Nnet with no transition model (i.e. the raw neural net.)\n"
"\n"
"Usage: nnet-to-raw-nnet [options] <nnet-in> <raw-nnet-out>\n"
"e.g.:\n"
" nnet-to-raw-nnet --binary=false 1.mdl 1.raw\n";
int32 truncate = -1;
bool binary_write = true;
ParseOptions po(usage);
po.Register("binary", &binary_write, "Write output in binary mode");
po.Register("truncate", &truncate, "If set, will truncate the neural net "
"to this many components by removing the last components.");
po.Read(argc, argv);
if (po.NumArgs() != 2) {
po.PrintUsage();
exit(1);
}
std::string nnet_rxfilename = po.GetArg(1),
raw_nnet_wxfilename = po.GetArg(2);
TransitionModel trans_model;
AmNnet am_nnet;
{
bool binary;
Input ki(nnet_rxfilename, &binary);
trans_model.Read(ki.Stream(), binary);
am_nnet.Read(ki.Stream(), binary);
}
if (truncate >= 0) {
KALDI_LOG << "Truncating neural net to " << truncate << " layers.";
am_nnet.GetNnet().Resize(truncate);
}
const Nnet &nnet = am_nnet.GetNnet();
WriteKaldiObject(nnet, raw_nnet_wxfilename, binary_write);
KALDI_LOG << "Read neural net from " << nnet_rxfilename
<< " and wrote raw neural net to " << raw_nnet_wxfilename;
return 0;
} catch(const std::exception &e) {
std::cerr << e.what() << '\n';
return -1;
}
}