fgmm-global-merge.cc
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// fgmmbin/fgmm-global-merge.cc
// Copyright 2009-2011 Microsoft Corporation
// 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 "util/common-utils.h"
#include "gmm/full-gmm.h"
#include "gmm/mle-full-gmm.h"
namespace kaldi {
/// merges GMMs by appending Gaussians in "src" to "dst".
/// Renormalizes weights by allocating weight proportional to #Gauss.
void MergeFullGmm(const FullGmm &src, FullGmm *dst) {
FullGmm dst_copy;
dst_copy.CopyFromFullGmm(*dst);
KALDI_ASSERT(src.NumGauss() != 0 && dst_copy.NumGauss() != 0
&& src.Dim() == dst_copy.Dim());
int32 src_num_mix = src.NumGauss(), dst_num_mix = dst_copy.NumGauss(),
num_mix = src_num_mix + dst_num_mix, dim = src.Dim();
dst->Resize(num_mix, dim);
std::vector<SpMatrix<BaseFloat> > invcovars(num_mix);
for(int32 i = 0; i < dst_num_mix; i++) {
invcovars[i].Resize(dim);
invcovars[i].CopyFromSp(dst_copy.inv_covars()[i]);
}
for(int32 i = 0; i < src_num_mix; i++) {
invcovars[i+dst_num_mix].Resize(dim);
invcovars[i+dst_num_mix].CopyFromSp(src.inv_covars()[i]);
}
Matrix<BaseFloat> means_invcovars(num_mix, dim);
means_invcovars.Range(0, dst_num_mix, 0, dim).CopyFromMat(dst_copy.means_invcovars());
means_invcovars.Range(dst_num_mix, src_num_mix, 0, dim).CopyFromMat(src.means_invcovars());
dst->SetInvCovarsAndMeansInvCovars(invcovars, means_invcovars);
Vector<BaseFloat> weights(num_mix); // initialized to zero.
// weight proportional to #Gaussians, so that if we combine a number of
// models with same #Gaussians, they all get the same weight.
BaseFloat src_weight = src_num_mix / static_cast<BaseFloat>(num_mix),
dst_weight = dst_num_mix / static_cast<BaseFloat>(num_mix);
weights.Range(0, dst_num_mix).AddVec(dst_weight, dst_copy.weights());
weights.Range(dst_num_mix, src_num_mix).AddVec(src_weight, src.weights());
dst->SetWeights(weights);
dst->ComputeGconsts();
}
}
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
typedef kaldi::int32 int32;
const char *usage =
"Combine a number of GMMs into a larger GMM, with #Gauss = \n"
" sum(individual #Gauss)). Output full GMM, and a text file with\n"
" sizes of each individual GMM.\n"
"Usage: fgmm-global-merge [options] fgmm-out sizes-file-out fgmm-in1 fgmm-in2 ...\n";
bool binary = true;
ParseOptions po(usage);
po.Register("binary", &binary, "Write output in binary mode");
po.Read(argc, argv);
if (po.NumArgs() < 4) {
po.PrintUsage();
exit(1);
}
std::string fgmm_out_filename = po.GetArg(1),
sizes_out_filename = po.GetArg(2);
FullGmm fgmm;
Output sizes_ko(sizes_out_filename, false); // false == not binary.
for (int i = 3, max = po.NumArgs(); i <= max; i++) {
std::string stats_in_filename = po.GetArg(i);
bool binary_read;
Input ki(stats_in_filename, &binary_read);
if (i==3) {
fgmm.Read(ki.Stream(), binary_read);
sizes_ko.Stream() << fgmm.NumGauss() << ' ';
} else {
FullGmm fgmm2;
fgmm2.Read(ki.Stream(), binary_read);
sizes_ko.Stream() << fgmm2.NumGauss() << ' ';
MergeFullGmm(fgmm2, &fgmm);
}
}
sizes_ko.Stream() << "\n";
// Write out the model
WriteKaldiObject(fgmm, fgmm_out_filename, binary);
KALDI_LOG << "Written merged GMM to " << fgmm_out_filename;
} catch(const std::exception &e) {
std::cerr << e.what() << '\n';
return -1;
}
}