nnet3-chain-compute-prob.cc
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// nnet3bin/nnet3-chain-compute-prob.cc
// Copyright 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/nnet-chain-diagnostics.h"
#include "nnet3/nnet-utils.h"
int main(int argc, char *argv[]) {
try {
using namespace kaldi;
using namespace kaldi::nnet3;
typedef kaldi::int32 int32;
typedef kaldi::int64 int64;
const char *usage =
"Computes and prints to in logging messages the average log-prob per frame of\n"
"the given data with an nnet3+chain neural net. The input of this is the output of\n"
"e.g. nnet3-chain-get-egs | nnet3-chain-merge-egs.\n"
"\n"
"Usage: nnet3-chain-compute-prob [options] <raw-nnet3-model-in> <denominator-fst> <training-examples-in>\n"
"e.g.: nnet3-chain-compute-prob 0.mdl den.fst ark:valid.egs\n";
bool batchnorm_test_mode = true, dropout_test_mode = true;
// This program doesn't support using a GPU, because these probabilities are
// used for diagnostics, and you can just compute them with a small enough
// amount of data that a CPU can do it within reasonable time.
// It wouldn't be hard to make it support GPU, though.
NnetComputeProbOptions nnet_opts;
chain::ChainTrainingOptions chain_opts;
ParseOptions po(usage);
po.Register("batchnorm-test-mode", &batchnorm_test_mode,
"If true, set test-mode to true on any BatchNormComponents.");
po.Register("dropout-test-mode", &dropout_test_mode,
"If true, set test-mode to true on any DropoutComponents and "
"DropoutMaskComponents.");
nnet_opts.Register(&po);
chain_opts.Register(&po);
po.Read(argc, argv);
if (po.NumArgs() != 3) {
po.PrintUsage();
exit(1);
}
std::string nnet_rxfilename = po.GetArg(1),
den_fst_rxfilename = po.GetArg(2),
examples_rspecifier = po.GetArg(3);
Nnet nnet;
ReadKaldiObject(nnet_rxfilename, &nnet);
if (batchnorm_test_mode)
SetBatchnormTestMode(true, &nnet);
if (dropout_test_mode)
SetDropoutTestMode(true, &nnet);
fst::StdVectorFst den_fst;
ReadFstKaldi(den_fst_rxfilename, &den_fst);
NnetChainComputeProb chain_prob_computer(nnet_opts, chain_opts, den_fst,
nnet);
SequentialNnetChainExampleReader example_reader(examples_rspecifier);
for (; !example_reader.Done(); example_reader.Next())
chain_prob_computer.Compute(example_reader.Value());
bool ok = chain_prob_computer.PrintTotalStats();
return (ok ? 0 : 1);
} catch(const std::exception &e) {
std::cerr << e.what() << '\n';
return -1;
}
}