nnet3-init.cc File Reference

#include "base/kaldi-common.h"
#include "util/common-utils.h"
#include "nnet3/nnet-nnet.h"
#include "hmm/transition-model.h"
#include "tree/context-dep.h"

Include dependency graph for nnet3-init.cc:

Go to the source code of this file.

Functions
int	main (int argc, char *argv[])

Function Documentation

main()

int main	(	int	argc,
		char *	argv[]
	)

Definition at line 26 of file nnet3-init.cc.

References ParseOptions::GetArg(), KALDI_ASSERT, KALDI_LOG, ParseOptions::NumArgs(), ParseOptions::PrintUsage(), ParseOptions::Read(), Nnet::ReadConfig(), kaldi::ReadKaldiObject(), ParseOptions::Register(), Input::Stream(), and kaldi::WriteKaldiObject().

                                 {
  try {
    using namespace kaldi;
    using namespace kaldi::nnet3;
    typedef kaldi::int32 int32;

    const char *usage =
        "Initialize nnet3 neural network from a config file; outputs 'raw' nnet\n"
        "without associated information such as transition model and priors.\n"
        "Search for examples in scripts in /egs/wsj/s5/steps/nnet3/\n"
        "Can also be used to add layers to existing model (provide existing model\n"
        "as 1st arg)\n"
        "\n"
        "Usage:  nnet3-init [options] [<existing-model-in>] <config-in> <raw-nnet-out>\n"
        "e.g.:\n"
        " nnet3-init nnet.config 0.raw\n"
        "or: nnet3-init 1.raw nnet.config 2.raw\n"
        "See also: nnet3-copy, nnet3-info\n";

    bool binary_write = true;
    int32 srand_seed = 0;

    ParseOptions po(usage);
    po.Register("binary", &binary_write, "Write output in binary mode");
    po.Register("srand", &srand_seed, "Seed for random number generator");

    po.Read(argc, argv);
    srand(srand_seed);

    if (po.NumArgs() < 2 || po.NumArgs() > 3) {
      po.PrintUsage();
      exit(1);
    }

    std::string raw_nnet_rxfilename = (po.NumArgs() == 3 ?
                                       po.GetArg(1) : std::string("")),
        config_rxfilename = po.GetArg(po.NumArgs() == 3 ? 2 : 1),
        raw_nnet_wxfilename = po.GetArg(po.NumArgs() == 3 ? 3 : 2);

    Nnet nnet;
    if (po.NumArgs() == 3) {
      ReadKaldiObject(raw_nnet_rxfilename, &nnet);
      KALDI_LOG << "Read raw neural net from "
                << raw_nnet_rxfilename;
    }

    {
      bool binary;
      Input ki(config_rxfilename, &binary);
      KALDI_ASSERT(!binary && "Expect config file to contain text.");
      nnet.ReadConfig(ki.Stream());
    }

    WriteKaldiObject(nnet, raw_nnet_wxfilename, binary_write);
    KALDI_LOG << "Initialized raw neural net and wrote it to "
              << raw_nnet_wxfilename;
    return 0;
  } catch(const std::exception &e) {
    std::cerr << e.what() << '\n';
    return -1;
  }
}