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// nnet3bin/nnet3-am-info.cc
// Copyright 2012-2015 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 "nnet3/am-nnet-simple.h"
#include "hmm/transition-model.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using namespace kaldi::nnet3;
typedef kaldi::int32 int32;
const char *usage =
"Print some text information about an nnet3 neural network, to
"
"standard output
"
"
"
"Usage: nnet3-am-info [options] <nnet>
"
"e.g.:
"
" nnet3-am-info 0.mdl
"
"See also: nnet3-am-info
";
ParseOptions po(usage);
po.Read(argc, argv);
if (po.NumArgs() != 1) {
po.PrintUsage();
exit(1);
}
std::string nnet_rxfilename = po.GetArg(1);
TransitionModel trans_model;
AmNnetSimple am_nnet;
{
bool binary;
Input ki(nnet_rxfilename, &binary);
trans_model.Read(ki.Stream(), binary);
am_nnet.Read(ki.Stream(), binary);
}
std::cout << am_nnet.Info();
return 0;
} catch(const std::exception &e) {
std::cerr << e.what() << '
';
return -1;
}
}
/*
Test script:
cat <<EOF | nnet3-init --binary=false - - | nnet3-info -
component name=affine1 type=NaturalGradientAffineComponent input-dim=72 output-dim=59
component name=relu1 type=RectifiedLinearComponent dim=59
component name=final_affine type=NaturalGradientAffineComponent input-dim=59 output-dim=298
component name=logsoftmax type=SoftmaxComponent dim=298
input-node name=input dim=18
component-node name=affine1_node component=affine1 input=Append(Offset(input, -4), Offset(input, -3), Offset(input, -2), Offset(input, 0))
component-node name=nonlin1 component=relu1 input=affine1_node
component-node name=final_affine component=final_affine input=nonlin1
component-node name=output_nonlin component=logsoftmax input=final_affine
output-node name=output input=output_nonlin
EOF
*/
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