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egs/wsj/s5/steps/nnet3/decode.sh
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#!/bin/bash # Copyright 2012-2015 Johns Hopkins University (Author: Daniel Povey). # Apache 2.0. # This script does decoding with a neural-net. # Begin configuration section. stage=1 nj=4 # number of decoding jobs. acwt=0.1 # Just a default value, used for adaptation and beam-pruning.. post_decode_acwt=1.0 # can be used in 'chain' systems to scale acoustics by 10 so the # regular scoring script works. cmd=run.pl beam=15.0 frames_per_chunk=50 max_active=7000 min_active=200 ivector_scale=1.0 lattice_beam=8.0 # Beam we use in lattice generation. iter=final num_threads=1 # if >1, will use gmm-latgen-faster-parallel use_gpu=false # If true, will use a GPU, with nnet3-latgen-faster-batch. # In that case it is recommended to set num-threads to a large # number, e.g. 20 if you have that many free CPU slots on a GPU # node, and to use a small number of jobs. scoring_opts= skip_diagnostics=false skip_scoring=false extra_left_context=0 extra_right_context=0 extra_left_context_initial=-1 extra_right_context_final=-1 online_ivector_dir= minimize=false # End configuration section. echo "$0 $@" # Print the command line for logging [ -f ./path.sh ] && . ./path.sh; # source the path. . utils/parse_options.sh || exit 1; if [ $# -ne 3 ]; then echo "Usage: $0 [options] <graph-dir> <data-dir> <decode-dir>" echo "e.g.: steps/nnet3/decode.sh --nj 8 \\" echo "--online-ivector-dir exp/nnet2_online/ivectors_test_eval92 \\" echo " exp/tri4b/graph_bg data/test_eval92_hires $dir/decode_bg_eval92" echo "main options (for others, see top of script file)" echo " --config <config-file> # config containing options" echo " --nj <nj> # number of parallel jobs" echo " --cmd <cmd> # Command to run in parallel with" echo " --beam <beam> # Decoding beam; default 15.0" echo " --iter <iter> # Iteration of model to decode; default is final." echo " --scoring-opts <string> # options to local/score.sh" echo " --num-threads <n> # number of threads to use, default 1." echo " --use-gpu <true|false> # default: false. If true, we recommend" echo " # to use large --num-threads as the graph" echo " # search becomes the limiting factor." exit 1; fi graphdir=$1 data=$2 dir=$3 srcdir=`dirname $dir`; # Assume model directory one level up from decoding directory. model=$srcdir/$iter.mdl extra_files= if [ ! -z "$online_ivector_dir" ]; then steps/nnet2/check_ivectors_compatible.sh $srcdir $online_ivector_dir || exit 1 extra_files="$online_ivector_dir/ivector_online.scp $online_ivector_dir/ivector_period" fi utils/lang/check_phones_compatible.sh {$srcdir,$graphdir}/phones.txt || exit 1 for f in $graphdir/HCLG.fst $data/feats.scp $model $extra_files; do [ ! -f $f ] && echo "$0: no such file $f" && exit 1; done sdata=$data/split$nj; cmvn_opts=`cat $srcdir/cmvn_opts` || exit 1; thread_string= if $use_gpu; then if [ $num_threads -eq 1 ]; then echo "$0: **Warning: we recommend to use --num-threads > 1 for GPU-based decoding." fi thread_string="-batch --num-threads=$num_threads" queue_opt="--num-threads $num_threads --gpu 1" elif [ $num_threads -gt 1 ]; then thread_string="-parallel --num-threads=$num_threads" queue_opt="--num-threads $num_threads" fi mkdir -p $dir/log [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1; echo $nj > $dir/num_jobs ## Set up features. echo "$0: feature type is raw" feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- |" if [ ! -z "$online_ivector_dir" ]; then ivector_period=$(cat $online_ivector_dir/ivector_period) || exit 1; ivector_opts="--online-ivectors=scp:$online_ivector_dir/ivector_online.scp --online-ivector-period=$ivector_period" fi if [ "$post_decode_acwt" == 1.0 ]; then lat_wspecifier="ark:|gzip -c >$dir/lat.JOB.gz" else lat_wspecifier="ark:|lattice-scale --acoustic-scale=$post_decode_acwt ark:- ark:- | gzip -c >$dir/lat.JOB.gz" fi frame_subsampling_opt= if [ -f $srcdir/frame_subsampling_factor ]; then # e.g. for 'chain' systems frame_subsampling_opt="--frame-subsampling-factor=$(cat $srcdir/frame_subsampling_factor)" fi if [ $stage -le 1 ]; then $cmd $queue_opt JOB=1:$nj $dir/log/decode.JOB.log \ nnet3-latgen-faster$thread_string $ivector_opts $frame_subsampling_opt \ --frames-per-chunk=$frames_per_chunk \ --extra-left-context=$extra_left_context \ --extra-right-context=$extra_right_context \ --extra-left-context-initial=$extra_left_context_initial \ --extra-right-context-final=$extra_right_context_final \ --minimize=$minimize --max-active=$max_active --min-active=$min_active --beam=$beam \ --lattice-beam=$lattice_beam --acoustic-scale=$acwt --allow-partial=true \ --word-symbol-table=$graphdir/words.txt "$model" \ $graphdir/HCLG.fst "$feats" "$lat_wspecifier" || exit 1; fi if [ $stage -le 2 ]; then if ! $skip_diagnostics ; then [ ! -z $iter ] && iter_opt="--iter $iter" steps/diagnostic/analyze_lats.sh --cmd "$cmd" $iter_opt $graphdir $dir fi fi # The output of this script is the files "lat.*.gz"-- we'll rescore this at # different acoustic scales to get the final output. if [ $stage -le 3 ]; then if ! $skip_scoring ; then [ ! -x local/score.sh ] && \ echo "Not scoring because local/score.sh does not exist or not executable." && exit 1; echo "score best paths" [ "$iter" != "final" ] && iter_opt="--iter $iter" local/score.sh $scoring_opts --cmd "$cmd" $data $graphdir $dir echo "score confidence and timing with sclite" fi fi echo "Decoding done." exit 0; |