Blame view

src/nnet2bin/nnet-am-mixup.cc 2.4 KB
8dcb6dfcb   Yannick Estève   first commit
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
  // nnet2bin/nnet-am-mixup.cc
  
  // Copyright 2012  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 "nnet2/mixup-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 =
          "Add mixture-components to a neural net (comparable to mixtures in a Gaussian
  "
          "mixture model).  Number of mixture components must be greater than the number
  "
          "of pdfs
  "
          "
  "
          "Usage:  nnet-am-mixup [options] <nnet-in> <nnet-out>
  "
          "e.g.:
  "
          " nnet-am-mixup --power=0.3 --num-mixtures=5000 1.mdl 2.mdl
  ";
  
      NnetMixupConfig config;
      bool binary_write = true;
      
      ParseOptions po(usage);
      config.Register(&po);
  
      po.Read(argc, argv);
      
      if (po.NumArgs() != 2) {
        po.PrintUsage();
        exit(1);
      }
  
      std::string nnet_rxfilename = po.GetArg(1),
          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);
      }
  
      MixupNnet(config, &(am_nnet.GetNnet()));
  
      {
        Output ko(nnet_wxfilename, binary_write);
        trans_model.Write(ko.Stream(), binary_write);
        am_nnet.Write(ko.Stream(), binary_write);
      }
      KALDI_LOG << "Mixed up neural net from " << nnet_rxfilename
                << " and wrote it to " << nnet_wxfilename;
      return 0;
    } catch(const std::exception &e) {
      std::cerr << e.what() << '
  ';
      return -1;
    }
  }