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egs/wsj/s5/steps/nnet2/get_egs_discriminative2.sh
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#!/bin/bash # Copyright 2012 Johns Hopkins University (Author: Daniel Povey). Apache 2.0. # This script dumps examples MPE or MMI or state-level minimum bayes risk (sMBR) # training of neural nets. Note: for "criterion", smbr > mpe > mmi in terms of # compatibility of the dumped egs, meaning you can use the egs dumped with # --criterion smbr for MPE or MMI, and egs dumped with --criterion mpe for MMI # training. The discriminative training program itself doesn't enforce this and # it would let you mix and match them arbitrarily; we area speaking in terms of # the correctness of the algorithm that splits the lattices into pieces. # Begin configuration section. cmd=run.pl criterion=smbr drop_frames=false # option relevant for MMI, affects how we dump examples. samples_per_iter=400000 # measured in frames, not in "examples" max_temp_archives=128 # maximum number of temp archives per input job, only # affects the process of generating archives, not the # final result. stage=0 cleanup=true transform_dir= # If this is a SAT system, directory for transforms online_ivector_dir= num_utts_subset=3000 num_archives_priors=10 # End configuration section. echo "$0 $@" # Print the command line for logging if [ -f path.sh ]; then . ./path.sh; fi . parse_options.sh || exit 1; if [ $# != 6 ]; then echo "Usage: $0 [opts] <data> <lang> <ali-dir> <denlat-dir> <src-model-file> <degs-dir>" echo " e.g.: $0 data/train data/lang exp/tri3_ali exp/tri4_nnet_denlats exp/tri4/final.mdl exp/tri4_mpe/degs" echo "" echo "Main options (for others, see top of script file)" echo " --config <config-file> # config file containing options" echo " --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs (probably would be good to add --max-jobs-run 5 or so if using" echo " # GridEngine (to avoid excessive NFS traffic)." echo " --samples-per-iter <#samples|400000> # Number of samples of data to process per iteration, per" echo " # process." echo " --stage <stage|-8> # Used to run a partially-completed training process from somewhere in" echo " # the middle." echo " --criterion <criterion|smbr> # Training criterion: may be smbr, mmi or mpfe" echo " --online-ivector-dir <dir|""> # Directory for online-estimated iVectors, used in the" echo " # online-neural-net setup. (but you may want to use" echo " # steps/online/nnet2/get_egs_discriminative2.sh instead)" exit 1; fi data=$1 lang=$2 alidir=$3 denlatdir=$4 src_model=$5 dir=$6 extra_files= [ ! -z $online_ivector_dir ] && \ extra_files="$online_ivector_dir/ivector_period $online_ivector_dir/ivector_online.scp" # Check some files. for f in $data/feats.scp $lang/L.fst $alidir/ali.1.gz $alidir/num_jobs $alidir/tree \ $denlatdir/lat.1.gz $denlatdir/num_jobs $src_model $extra_files; do [ ! -f $f ] && echo "$0: no such file $f" && exit 1; done mkdir -p $dir/log $dir/info || exit 1; utils/lang/check_phones_compatible.sh $lang/phones.txt $alidir/phones.txt || exit 1; nj=$(cat $denlatdir/num_jobs) || exit 1; # $nj is the number of # splits of the denlats and alignments. nj_ali=$(cat $alidir/num_jobs) || exit 1; sdata=$data/split$nj utils/split_data.sh $data $nj if [ $nj_ali -eq $nj ]; then ali_rspecifier="ark,s,cs:gunzip -c $alidir/ali.JOB.gz |" alis=$(for n in $(seq $nj); do echo -n "$alidir/ali.$n.gz "; done) prior_ali_rspecifier="ark,s,cs:gunzip -c $alis | copy-int-vector ark:- ark,t:- | utils/filter_scp.pl $dir/priors_uttlist | ali-to-pdf $alidir/final.mdl ark,t:- ark:- |" else ali_rspecifier="scp:$dir/ali.scp" prior_ali_rspecifier="ark,s,cs:utils/filter_scp.pl $dir/priors_uttlist $dir/ali.scp | ali-to-pdf $alidir/final.mdl scp:- ark:- |" if [ $stage -le 1 ]; then echo "$0: number of jobs in den-lats versus alignments differ: dumping them as single archive and index." alis=$(for n in $(seq $nj_ali); do echo -n "$alidir/ali.$n.gz "; done) $cmd $dir/log/copy_alignments.log \ copy-int-vector "ark:gunzip -c $alis|" \ ark,scp:$dir/ali.ark,$dir/ali.scp || exit 1; fi fi splice_opts=`cat $alidir/splice_opts 2>/dev/null` silphonelist=`cat $lang/phones/silence.csl` || exit 1; cmvn_opts=`cat $alidir/cmvn_opts 2>/dev/null` cp $alidir/splice_opts $dir 2>/dev/null cp $alidir/cmvn_opts $dir 2>/dev/null cp $alidir/tree $dir cp $lang/phones/silence.csl $dir/info/ cp $src_model $dir/final.mdl || exit 1 if [ ! -z "$online_ivector_dir" ]; then ivector_period=$(cat $online_ivector_dir/ivector_period) ivector_dim=$(feat-to-dim scp:$online_ivector_dir/ivector_online.scp -) || exit 1; echo $ivector_dim >$dir/info/ivector_dim # the 'const_dim_opt' allows it to write only one iVector per example, # rather than one per time-index... it has to average over const_dim_opt="--const-feat-dim=$ivector_dim" else echo 0 > $dir/info/ivector_dim fi # Get list of validation utterances. awk '{print $1}' $data/utt2spk | utils/shuffle_list.pl | head -$num_utts_subset \ > $dir/priors_uttlist || exit 1; ## We don't support deltas here, only LDA or raw (mainly because deltas are less ## frequently used). if [ -z $feat_type ]; then if [ -f $alidir/final.mat ] && [ ! -f $transform_dir/raw_trans.1 ]; then feat_type=lda; else feat_type=raw; fi fi echo "$0: feature type is $feat_type" case $feat_type in 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:- |" priors_feats="ark,s,cs:utils/filter_scp.pl $dir/priors_uttlist $data/feats.scp | apply-cmvn $cmvn_opts --utt2spk=ark:$data/utt2spk scp:$data/cmvn.scp scp:- ark:- |" ;; lda) splice_opts=`cat $alidir/splice_opts 2>/dev/null` cp $alidir/final.mat $dir feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $dir/final.mat ark:- ark:- |" priors_feats="ark,s,cs:utils/filter_scp.pl $dir/priors_uttlist $data/feats.scp | apply-cmvn $cmvn_opts --utt2spk=ark:$data/utt2spk scp:$data/cmvn.scp scp:- ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $dir/final.mat ark:- ark:- |" ;; *) echo "$0: invalid feature type $feat_type" && exit 1; esac if [ -z "$transform_dir" ]; then if [ -f $transform_dir/trans.1 ] || [ -f $transform_dir/raw_trans.1 ]; then transform_dir=$alidir fi fi if [ ! -z "$transform_dir" ]; then echo "$0: using transforms from $transform_dir" [ ! -s $transform_dir/num_jobs ] && \ echo "$0: expected $transform_dir/num_jobs to contain the number of jobs." && exit 1; nj_orig=$(cat $transform_dir/num_jobs) if [ $feat_type == "raw" ]; then trans=raw_trans; else trans=trans; fi if [ $feat_type == "lda" ] && ! cmp $transform_dir/final.mat $alidir/final.mat; then echo "$0: LDA transforms differ between $alidir and $transform_dir" exit 1; fi if [ ! -f $transform_dir/$trans.1 ]; then echo "$0: expected $transform_dir/$trans.1 to exist (--transform-dir option)" exit 1; fi if [ $nj -ne $nj_orig ]; then # Copy the transforms into an archive with an index. for n in $(seq $nj_orig); do cat $transform_dir/$trans.$n; done | \ copy-feats ark:- ark,scp:$dir/$trans.ark,$dir/$trans.scp || exit 1; feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk scp:$dir/$trans.scp ark:- ark:- |" priors_feats="$priors_feats transform-feats --utt2spk=ark:$data/utt2spk scp:$dir/$trans.scp ark:- ark:- |" else # number of jobs matches with alignment dir. feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$transform_dir/$trans.JOB ark:- ark:- |" tras=$(for n in $(seq $nj); do echo -n "$transform_dir/$trans.$n "; done) priors_feats="$priors_feats transform-feats --utt2spk=ark:$data/utt2spk 'ark:cat $tras |' ark:- ark:- |" fi fi if [ ! -z $online_ivector_dir ]; then # add iVectors to the features. feats="$feats paste-feats --length-tolerance=$ivector_period ark:- 'ark,s,cs:utils/filter_scp.pl $sdata/JOB/utt2spk $online_ivector_dir/ivector_online.scp | subsample-feats --n=-$ivector_period scp:- ark:- |' ark:- |" priors_feats="$priors_feats paste-feats --length-tolerance=$ivector_period ark:- 'ark,s,cs:utils/filter_scp.pl $dir/priors_uttlist $online_ivector_dir/ivector_online.scp | subsample-feats --n=-$ivector_period scp:- ark:- |' ark:- |" fi if [ $stage -le 2 ]; then echo "$0: working out number of frames of training data" num_frames=$(steps/nnet2/get_num_frames.sh $data) echo $num_frames > $dir/info/num_frames # Working out total number of archives. Add one on the assumption the # num-frames won't divide exactly, and we want to round up. num_archives=$[$num_frames/$samples_per_iter + 1] # the next few lines relate to how we may temporarily split each input job # into fewer than $num_archives pieces, to avoid using an excessive # number of filehandles. archive_ratio=$[$num_archives/$max_temp_archives+1] num_archives_temp=$[$num_archives/$archive_ratio] # change $num_archives slightly to make it an exact multiple # of $archive_ratio. num_archives=$[$num_archives_temp*$archive_ratio] echo $num_archives >$dir/info/num_archives || exit 1 echo $num_archives_temp >$dir/info/num_archives_temp || exit 1 frames_per_archive=$[$num_frames/$num_archives] # note, this is the number of frames per archive prior to discarding frames. echo $frames_per_archive > $dir/info/frames_per_archive else num_archives=$(cat $dir/info/num_archives) || exit 1; num_archives_temp=$(cat $dir/info/num_archives_temp) || exit 1; frames_per_archive=$(cat $dir/info/frames_per_archive) || exit 1; fi echo "$0: Splitting the data up into $num_archives archives (using $num_archives_temp temporary pieces per input job)" echo "$0: giving samples-per-iteration of $frames_per_archive (you requested $samples_per_iter)." # we create these data links regardless of the stage, as there are situations # where we would want to recreate a data link that had previously been deleted. if [ -d $dir/storage ]; then echo "$0: creating data links for distributed storage of degs" # See utils/create_split_dir.pl for how this 'storage' directory is created. for x in $(seq $nj); do for y in $(seq $num_archives_temp); do utils/create_data_link.pl $dir/degs_orig.$x.$y.ark done done for z in $(seq $num_archives); do utils/create_data_link.pl $dir/degs.$z.ark done if [ $num_archives_temp -ne $num_archives ]; then for z in $(seq $num_archives); do utils/create_data_link.pl $dir/degs_temp.$z.ark done fi fi rm $dir/.error 2>/dev/null left_context=$(nnet-am-info $dir/final.mdl | grep '^left-context' | awk '{print $2}') || exit 1 right_context=$(nnet-am-info $dir/final.mdl | grep '^right-context' | awk '{print $2}') || exit 1 ( if [ $stage -le 10 ]; then priors_egs_list= for y in `seq $num_archives_priors`; do utils/create_data_link.pl $dir/priors_egs.$y.ark priors_egs_list="$priors_egs_list ark:$dir/priors_egs.$y.ark" done nnet_context_opts="--left-context=$left_context --right-context=$right_context" echo "$0: dumping egs for prior adjustment in the background." $cmd $dir/log/create_priors_subset.log \ nnet-get-egs $ivectors_opt $nnet_context_opts "$priors_feats" \ "$prior_ali_rspecifier ali-to-post ark:- ark:- |" \ ark:- \| nnet-copy-egs ark:- $priors_egs_list || \ { touch $dir/.error; echo "Error in creating priors subset. See $dir/log/create_priors_subset.log"; exit 1; } sleep 3; echo $num_archives_priors >$dir/info/num_archives_priors fi ) & if [ $stage -le 3 ]; then echo "$0: getting initial training examples by splitting lattices" degs_list=$(for n in $(seq $num_archives_temp); do echo -n "ark:$dir/degs_orig.JOB.$n.ark "; done) $cmd JOB=1:$nj $dir/log/get_egs.JOB.log \ nnet-get-egs-discriminative --criterion=$criterion --drop-frames=$drop_frames \ "$src_model" "$feats" "$ali_rspecifier" "ark,s,cs:gunzip -c $denlatdir/lat.JOB.gz|" ark:- \| \ nnet-copy-egs-discriminative $const_dim_opt ark:- $degs_list || exit 1; sleep 5; # wait a bit so NFS has time to write files. fi if [ $stage -le 4 ]; then degs_list=$(for n in $(seq $nj); do echo -n "$dir/degs_orig.$n.JOB.ark "; done) if [ $num_archives -eq $num_archives_temp ]; then echo "$0: combining data into final archives and shuffling it" $cmd JOB=1:$num_archives $dir/log/shuffle.JOB.log \ cat $degs_list \| nnet-shuffle-egs-discriminative --srand=JOB ark:- \ ark:$dir/degs.JOB.ark || exit 1; else echo "$0: combining and re-splitting data into un-shuffled versions of final archives." archive_ratio=$[$num_archives/$num_archives_temp] ! [ $archive_ratio -gt 1 ] && echo "$0: Bad archive_ratio $archive_ratio" && exit 1; # note: the \$[ .. ] won't be evaluated until the job gets executed. The # aim is to write to the archives with the final numbering, 1 # ... num_archives, which is more than num_archives_temp. The list with # \$[... ] expressions in it computes the set of final indexes for each # temporary index. degs_list_out=$(for n in $(seq $archive_ratio); do echo -n "ark:$dir/degs_temp.\$[((JOB-1)*$archive_ratio)+$n].ark "; done) # e.g. if dir=foo and archive_ratio=2, we'd have # degs_list_out='foo/degs_temp.$[((JOB-1)*2)+1].ark foo/degs_temp.$[((JOB-1)*2)+2].ark' $cmd JOB=1:$num_archives_temp $dir/log/resplit.JOB.log \ cat $degs_list \| nnet-copy-egs-discriminative --srand=JOB ark:- \ $degs_list_out || exit 1; fi fi if [ $stage -le 5 ] && [ $num_archives -ne $num_archives_temp ]; then echo "$0: shuffling final archives." $cmd JOB=1:$num_archives $dir/log/shuffle.JOB.log \ nnet-shuffle-egs-discriminative --srand=JOB ark:$dir/degs_temp.JOB.ark \ ark:$dir/degs.JOB.ark || exit 1 fi wait; [ -f $dir/.error ] && echo "Error detected while creating priors adjustment egs" && exit 1 if $cleanup; then echo "$0: removing temporary archives." for x in $(seq $nj); do for y in $(seq $num_archives_temp); do file=$dir/degs_orig.$x.$y.ark [ -L $file ] && rm $(utils/make_absolute.sh $file); rm $file done done if [ $num_archives_temp -ne $num_archives ]; then for z in $(seq $num_archives); do file=$dir/degs_temp.$z.ark [ -L $file ] && rm $(utils/make_absolute.sh $file); rm $file done fi fi echo "$0: Done." |