nnet-init.cc
2.43 KB
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
// nnet2bin/nnet-init.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 "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 =
"Initialize the nnet2 neural network from a config file with a line for each\n"
"component. Note, this only outputs the neural net itself, not the associated\n"
"information such as the transition-model; you'll probably want to pipe\n"
"the output into something like nnet-am-init.\n"
"\n"
"Usage: nnet-init [options] <config-in> <raw-nnet-out>\n"
"e.g.:\n"
" nnet-init nnet.config 1.raw\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.PrintUsage();
exit(1);
}
std::string config_rxfilename = po.GetArg(1),
raw_nnet_wxfilename = po.GetArg(2);
Nnet nnet;
{
bool binary;
Input ki(config_rxfilename, &binary);
KALDI_ASSERT(!binary && "Expect config file to contain text.");
nnet.Init(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;
}
}