// nnetbin/nnet-info.cc // Copyright 2013 Brno University of Technology (Author: Karel Vesely) // 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 "nnet/nnet-nnet.h" int main(int argc, char *argv[]) { try { using namespace kaldi; using namespace kaldi::nnet1; typedef kaldi::int32 int32; const char *usage = "Print human-readable information about the neural network.\n" "(topology, various weight statistics, etc.) It prints to stdout.\n" "Usage: nnet-info [options] \n" "e.g.:\n" " nnet-info 1.nnet\n"; ParseOptions po(usage); po.Read(argc, argv); if (po.NumArgs() != 1) { po.PrintUsage(); exit(1); } std::string nnet_rxfilename = po.GetArg(1); // load the network Nnet nnet; { bool binary_read; Input ki(nnet_rxfilename, &binary_read); nnet.Read(ki.Stream(), binary_read); } std::cout << nnet.Info(); KALDI_LOG << "Printed info about " << nnet_rxfilename; return 0; } catch(const std::exception &e) { std::cerr << e.what(); return -1; } }