nnet-initialize.cc
2.09 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
// nnetbin/nnet-initialize.cc
// Copyright 2014 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 =
"Initialize Neural Network parameters according to a prototype (nnet1).\n"
"Usage: nnet-initialize [options] <nnet-prototype-in> <nnet-out>\n"
"e.g.: nnet-initialize --binary=false nnet.proto nnet.init\n";
SetVerboseLevel(1); // be verbose by default,
ParseOptions po(usage);
bool binary_write = true;
po.Register("binary", &binary_write, "Write output in binary mode");
int32 seed = 777;
po.Register("seed", &seed, "Seed for random number generator");
po.Read(argc, argv);
if (po.NumArgs() != 2) {
po.PrintUsage();
exit(1);
}
std::string nnet_config_in_filename = po.GetArg(1),
nnet_out_filename = po.GetArg(2);
std::srand(seed);
// initialize the network
Nnet nnet;
nnet.Init(nnet_config_in_filename);
// store the network
Output ko(nnet_out_filename, binary_write);
nnet.Write(ko.Stream(), binary_write);
KALDI_LOG << "Written initialized model to " << nnet_out_filename;
return 0;
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}