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Scripts/steps/.svn/text-base/decode_nnet.sh.svn-base
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#!/bin/bash # Copyright 2012-2013 Karel Vesely, Daniel Povey # Apache 2.0 # Begin configuration section. nnet= # Optionally pre-select network to use for getting state-likelihoods feature_transform= # Optionally pre-select feature transform (in front of nnet) model= # Optionally pre-select transition model class_frame_counts= # Optionally pre-select class-counts used to compute PDF priors stage=0 # stage=1 skips lattice generation nj=4 cmd=run.pl max_active=7000 # maximum of active tokens max_mem=50000000 # limit the fst-size to 50MB (larger fsts are minimized) beam=13.0 # GMM:13.0 latbeam=8.0 # GMM:6.0 acwt=0.10 # GMM:0.0833, note: only really affects pruning (scoring is on lattices). scoring_opts="--min-lmwt 4 --max-lmwt 15" skip_scoring=false use_gpu_id=-1 # disable gpu parallel_opts="-pe smp 2" # use 2 CPUs (1 DNN-forward, 1 decoder) # End configuration section. echo "$0 $@" # Print the command line for logging [ -f ./path.sh ] && . ./path.sh; # source the path. . parse_options.sh || exit 1; if [ $# != 3 ]; then echo "Usage: $0 [options] <graph-dir> <data-dir> <decode-dir>" echo "... where <decode-dir> is assumed to be a sub-directory of the directory" echo " where the DNN + transition model is." echo "e.g.: $0 exp/dnn1/graph_tgpr data/test exp/dnn1/decode_tgpr" echo "" echo "This script works on plain or modified features (CMN,delta+delta-delta)," echo "which are then sent through feature-transform. It works out what type" echo "of features you used from content of srcdir." echo "" 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 (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs." echo "" echo " --nnet <nnet> # which nnet to use (opt.)" echo " --feature-transform <nnet> # select transform in front of nnet (opt.)" echo " --class-frame-counts <file> # file with frame counts (used to compute priors) (opt.)" echo " --model <model> # which transition model to use (opt.)" echo "" echo " --acwt <float> # select acoustic scale for decoding" echo " --scoring-opts <opts> # options forwarded to local/score.sh" exit 1; fi graphdir=$1 data=$2 dir=$3 srcdir=`dirname $dir`; # The model directory is one level up from decoding directory. sdata=$data/split$nj; mkdir -p $dir/log [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1; echo $nj > $dir/num_jobs if [ -z "$nnet" ]; then # if --nnet <nnet> was not specified on the command line... nnet=$srcdir/final.nnet; fi [ -z "$nnet" ] && echo "Error nnet '$nnet' does not exist!" && exit 1; if [ -z "$model" ]; then # if --model <mdl> was not specified on the command line... model=$srcdir/final.mdl; fi # find the feature_transform to use if [ -z "$feature_transform" ]; then feature_transform=$srcdir/final.feature_transform fi if [ ! -f $feature_transform ]; then echo "Missing feature_transform '$feature_transform'" exit 1 fi # check that files exist for f in $sdata/1/feats.scp $nnet_i $nnet $model $graphdir/HCLG.fst; do [ ! -f $f ] && echo "$0: no such file $f" && exit 1; done # PREPARE THE LOG-POSTERIOR COMPUTATION PIPELINE if [ -z "$class_frame_counts" ]; then class_frame_counts=$srcdir/ali_train_pdf.counts else echo "Overriding class_frame_counts by $class_frame_counts" fi # Create the feature stream: feats="ark,s,cs:copy-feats scp:$sdata/JOB/feats.scp ark:- |" # Optionally add cmvn if [ -f $srcdir/norm_vars ]; then norm_vars=$(cat $srcdir/norm_vars 2>/dev/null) [ ! -f $sdata/1/cmvn.scp ] && echo "$0: cannot find cmvn stats $sdata/1/cmvn.scp" && exit 1 feats="$feats apply-cmvn --norm-vars=$norm_vars --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp ark:- ark:- |" fi # Optionally add deltas if [ -f $srcdir/delta_order ]; then delta_order=$(cat $srcdir/delta_order) feats="$feats add-deltas --delta-order=$delta_order ark:- ark:- |" fi # Run the decoding in the queue if [ $stage -le 0 ]; then $cmd $parallel_opts JOB=1:$nj $dir/log/decode.JOB.log \ nnet-forward --feature-transform=$feature_transform --no-softmax=true --class-frame-counts=$class_frame_counts --use-gpu-id=$use_gpu_id $nnet "$feats" ark:- \| \ latgen-faster-mapped --max-active=$max_active --max-mem=$max_mem --beam=$beam --lattice-beam=$latbeam \ --acoustic-scale=$acwt --allow-partial=true --word-symbol-table=$graphdir/words.txt \ $model $graphdir/HCLG.fst ark:- "ark:|gzip -c > $dir/lat.JOB.gz" || exit 1; fi # Run the scoring if ! $skip_scoring ; then [ ! -x local/score.sh ] && \ echo "Not scoring because local/score.sh does not exist or not executable." && exit 1; local/score.sh $scoring_opts --cmd "$cmd" $data $graphdir $dir || exit 1; fi exit 0; |