fmpe-acc-stats.cc
3.79 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
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
// featbin/fmpe-acc-stats.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 "transform/fmpe.h"
int main(int argc, char *argv[]) {
using namespace kaldi;
using kaldi::int32;
try {
const char *usage =
"Compute statistics for fMPE training\n"
"Usage: fmpe-acc-stats [options...] <fmpe-object> "
"<feat-rspecifier> <feat-diff-rspecifier> <gselect-rspecifier> <stats-out>\n"
"Note: gmm-fmpe-acc-stats avoids computing the features an extra time\n";
ParseOptions po(usage);
bool binary = true;
po.Register("binary", &binary, "If true, output stats in binary mode.");
po.Read(argc, argv);
if (po.NumArgs() != 5) {
po.PrintUsage();
exit(1);
}
std::string fmpe_rxfilename = po.GetArg(1),
feat_rspecifier = po.GetArg(2),
feat_diff_rspecifier = po.GetArg(3),
gselect_rspecifier = po.GetArg(4),
stats_wxfilename = po.GetArg(5);
Fmpe fmpe;
ReadKaldiObject(fmpe_rxfilename, &fmpe);
SequentialBaseFloatMatrixReader feat_reader(feat_rspecifier);
RandomAccessBaseFloatMatrixReader diff_reader(feat_diff_rspecifier);
RandomAccessInt32VectorVectorReader gselect_reader(gselect_rspecifier);
// fmpe stats...
FmpeStats fmpe_stats(fmpe);
int32 num_done = 0, num_err = 0;
for (; !feat_reader.Done(); feat_reader.Next()) {
std::string key = feat_reader.Key();
const Matrix<BaseFloat> feat_in(feat_reader.Value());
if (!gselect_reader.HasKey(key)) {
KALDI_WARN << "No gselect information for key " << key;
num_err++;
continue;
}
const std::vector<std::vector<int32> > &gselect =
gselect_reader.Value(key);
if (static_cast<int32>(gselect.size()) != feat_in.NumRows()) {
KALDI_WARN << "gselect information has wrong size";
num_err++;
continue;
}
if (!diff_reader.HasKey(key)) {
KALDI_WARN << "No gradient information for key " << key;
num_err++;
continue;
}
const Matrix<BaseFloat> &feat_deriv = diff_reader.Value(key);
if (feat_deriv.NumCols() == feat_in.NumCols()) { // Only direct derivative.
fmpe.AccStats(feat_in, gselect, feat_deriv, NULL, &fmpe_stats);
} else if (feat_deriv.NumCols() == feat_in.NumCols() * 2) { // +indirect.
SubMatrix<BaseFloat> direct_deriv(feat_deriv, 0, feat_deriv.NumRows(),
0, feat_in.NumCols()),
indirect_deriv(feat_deriv, 0, feat_deriv.NumRows(),
feat_in.NumCols(), feat_in.NumCols());
fmpe.AccStats(feat_in, gselect, direct_deriv, &indirect_deriv, &fmpe_stats);
} else {
KALDI_ERR << "Mismatch in dimension of feature derivative.";
}
num_done++;
}
KALDI_LOG << " Done " << num_done << " utterances, " << num_err
<< " had errors.";
WriteKaldiObject(fmpe_stats, stats_wxfilename, binary);
return (num_done != 0 ? 0 : 1);
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}