Blame view
src/nnet2bin/nnet-get-feature-transform.cc
3.07 KB
8dcb6dfcb
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 90 |
// nnet2bin/nnet-get-feature-transform.cc
// Copyright 2013 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/get-feature-transform.h"
int main(int argc, char *argv[]) {
using namespace kaldi;
typedef kaldi::int32 int32;
try {
const char *usage =
"Get feature-projection transform using stats obtained with acc-lda.
"
"See comments in the code of nnet2/get-feature-transform.h for more
"
"information.
"
"
"
"Usage: nnet-get-feature-transform [options] <matrix-out> <lda-acc-1> <lda-acc-2> ...
";
bool binary = true;
FeatureTransformEstimateOptions opts;
std::string write_cholesky;
std::string write_within_covar;
ParseOptions po(usage);
po.Register("binary", &binary, "Write outputs in binary mode.");
po.Register("write-cholesky", &write_cholesky, "If supplied, write to this "
"wxfilename the Cholesky factor of the within-class covariance. "
"Can be used for perturbing features. E.g. "
"--write-cholesky=exp/nnet5/cholesky.tpmat");
po.Register("write-within-covar", &write_within_covar, "If supplied, write "
"to this wxfilename the within-class covariance (as a symmetric "
"matrix). E.g. --write-within-covar=exp/nnet5/within_covar.mat");
opts.Register(&po);
po.Read(argc, argv);
if (po.NumArgs() < 2) {
po.PrintUsage();
exit(1);
}
FeatureTransformEstimate fte;
std::string projection_wxfilename = po.GetArg(1);
for (int32 i = 2; i <= po.NumArgs(); i++) {
bool binary_in, add = true;
Input ki(po.GetArg(i), &binary_in);
fte.Read(ki.Stream(), binary_in, add);
}
Matrix<BaseFloat> mat;
TpMatrix<BaseFloat> cholesky;
fte.Estimate(opts, &mat,
(write_cholesky != "" || write_within_covar != "" ?
&cholesky : NULL));
WriteKaldiObject(mat, projection_wxfilename, binary);
if (write_cholesky != "") {
WriteKaldiObject(cholesky, write_cholesky, binary);
}
if (write_within_covar != "") {
SpMatrix<BaseFloat> within_var(cholesky.NumRows());
within_var.AddTp2(1.0, cholesky, kNoTrans, 0.0);
WriteKaldiObject(within_var, write_within_covar, binary);
}
return 0;
} catch(const std::exception &e) {
std::cerr << e.what();
return -1;
}
}
|