#!/bin/bash

# Copyright 2012  Johns Hopkins University (Author: Daniel Povey).  Apache 2.0.
#                 Korbinian Riedhammer

# SGMM training, with speaker vectors.  This script would normally be called on
# top of fMLLR features obtained from a conventional system, but it also works
# on top of any type of speaker-independent features (based on
# deltas+delta-deltas or LDA+MLLT).  For more info on SGMMs, see the paper "The
# subspace Gaussian mixture model--A structured model for speech recognition".
# (Computer Speech and Language, 2011).

# Begin configuration section.
nj=4
cmd=run.pl
stage=-6 # use this to resume partially finished training 
context_opts= # e.g. set it to "--context-width=5 --central-position=2"  for a
# quinphone system.
scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
num_iters=25   # Total number of iterations of training
num_iters_alimdl=3 # Number of iterations for estimating alignment model.
max_iter_inc=15 # Last iter to increase #substates on.
realign_iters="5 10 15"; # Iters to realign on. 
spkvec_iters="5 8 12 17" # Iters to estimate speaker vectors on.
increase_iters="6 10 14"; # Iters on which to increase phn dim and/or spk dim;
    # rarely necessary, and if it is, only the 1st will normally be necessary.
rand_prune=0.1 # Randomized-pruning parameter for posteriors, to speed up training.
               # Bigger -> more pruning; zero = no pruning.
phn_dim=  # You can use this to set the phonetic subspace dim. [default: feat-dim+1]
spk_dim=  # You can use this to set the speaker subspace dim. [default: feat-dim]
power=0.2 # Exponent for number of gaussians according to occurrence counts
beam=8
self_weight=0.9
retry_beam=40
leaves_per_group=5 # Relates to the SCTM (state-clustered tied-mixture) aspect:
                   # average number of pdfs in a "group" of pdfs.
update_m_iter=4
spk_dep_weights=true # [Symmetric SGMM] set this to false if you don't want "u" (i.e. to turn off
                      # symmetric SGMM.
normft2=true
# 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 [ $# != 8 ]; then
  echo "Usage: steps/tandem/train_sgmm2.sh <num-leaves> <num-substates> <data1> <data2> <lang> <ali-dir> <ubm> <exp-dir>"
  echo " e.g.: steps/tandem/train_sgmm2.sh 5000 8000 {mfcc,bottleneck}/data/train_si84 data/lang \\"
  echo "                      exp/tri3b_ali_si84 exp/ubm4a/final.ubm exp/sgmm4a"
  echo "main options (for others, see top of script file)"
  echo "  --config <config-file>                           # config containing options"
  echo "  --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
  echo "  --silence-weight <sil-weight>                    # weight for silence (e.g. 0.5 or 0.0)"
  echo "  --num-iters <#iters>                             # Number of iterations of E-M"
  echo "  --leaves-per-group <#leaves>                     # Average #leaves shared in one group"
  exit 1;
fi

num_pdfs=$1  # final #leaves, at 2nd level of tree.
totsubstates=$2
data1=$3
data2=$4
lang=$5
alidir=$6
ubm=$7
dir=$8

num_groups=$[$num_pdfs/$leaves_per_group]
first_spkvec_iter=`echo $spkvec_iters | awk '{print $1}'` || exit 1;

# Check some files.
for f in $data1/feats.scp $data2/feats.scp $lang/L.fst $alidir/ali.1.gz $alidir/final.mdl $ubm; do
  [ ! -f $f ] && echo "$0: no such file $f" && exit 1;
done


# Set some variables.
oov=`cat $lang/oov.int`
silphonelist=`cat $lang/phones/silence.csl`
if [ "$self_weight" == "1.0" ]; then
  numsubstates=$num_groups # Initial #-substates.
else
  numsubstates=$num_pdfs # Initial #-substates.
fi
incsubstates=$[($totsubstates-$numsubstates)/$max_iter_inc] # per-iter increment for #substates
feat_dim=`gmm-info $alidir/final.mdl 2>/dev/null | awk '/feature dimension/{print $NF}'` || exit 1;
[ $feat_dim -eq $feat_dim ] || exit 1; # make sure it's numeric.
[ -z $phn_dim ] && phn_dim=$[$feat_dim+1]
[ -z $spk_dim ] && spk_dim=$feat_dim
nj=`cat $alidir/num_jobs` || exit 1;

mkdir -p $dir/log
echo $nj > $dir/num_jobs

sdata1=$data1/split$nj;
sdata2=$data2/split$nj;
[[ -d $sdata1 && $data1/feats.scp -ot $sdata1 ]] || split_data.sh $data1 $nj || exit 1;
[[ -d $sdata2 && $data2/feats.scp -ot $sdata2 ]] || split_data.sh $data2 $nj || exit 1;

spkvecs_opt=  # Empty option for now, until we estimate the speaker vectors.
gselect_opt="--gselect=ark,s,cs:gunzip -c $dir/gselect.JOB.gz|"

## Set up features.


# We will use the same settings as with the alidir
splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options.
normft2=`cat $alidir/normft2 2>/dev/null`

if [ -f $alidir/final.mat ]; then feat_type=lda; else feat_type=delta; fi

case $feat_type in
  delta) 
  	echo "$0: feature type is $feat_type"
  	;;
  lda) 
  	echo "$0: feature type is $feat_type"
    cp $alidir/{lda,final}.mat $dir/ || exit 1;
    ;;
  *) echo "$0: invalid feature type $feat_type" && exit 1;
esac

# set up feature stream 1;  this are usually spectral features, so we will add
# deltas or splice them
feats1="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata1/JOB/utt2spk scp:$sdata1/JOB/cmvn.scp scp:$sdata1/JOB/feats.scp ark:- |"

if [ "$feat_type" == "delta" ]; then
  feats1="$feats1 add-deltas ark:- ark:- |"
elif [ "$feat_type" == "lda" ]; then
  feats1="$feats1 splice-feats $splice_opts ark:- ark:- | transform-feats $dir/lda.mat ark:- ark:- |"
fi

# set up feature stream 2;  this are usually bottleneck or posterior features, 
# which may be normalized if desired
feats2="scp:$sdata2/JOB/feats.scp"

if [ "$normft2" == "true" ]; then
  feats2="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata2/JOB/utt2spk scp:$sdata2/JOB/cmvn.scp $feats2 ark:- |"
fi

# assemble tandem features
feats="ark,s,cs:paste-feats '$feats1' '$feats2' ark:- |"

# add transformation, if applicable
if [ "$feat_type" == "lda" ]; then
  feats="$feats transform-feats $dir/final.mat ark:- ark:- |"
fi

# splicing/normalization options
cp $alidir/{splice_opts,tandem,normft2} $dir 2>/dev/null

if [ -f $alidir/trans.1 ]; then
  echo "$0: using transforms from $alidir"
  feats="$feats transform-feats --utt2spk=ark:$sdata1/JOB/utt2spk ark,s,cs:$alidir/trans.JOB ark:- ark:- |"
fi
##


if [ $stage -le -6 ]; then
  echo "$0: accumulating tree stats"
  $cmd JOB=1:$nj $dir/log/acc_tree.JOB.log \
    acc-tree-stats  --ci-phones=$ciphonelist $alidir/final.mdl "$feats" \
    "ark:gunzip -c $alidir/ali.JOB.gz|" $dir/JOB.treeacc || exit 1;
  [ "`ls $dir/*.treeacc | wc -w`" -ne "$nj" ] && echo "$0: Wrong #tree-stats" && exit 1;
  sum-tree-stats $dir/treeacc $dir/*.treeacc 2>$dir/log/sum_tree_acc.log || exit 1;
  rm $dir/*.treeacc
fi

if [ $stage -le -5 ]; then
  echo "$0: Getting questions for tree clustering."
  # preparing questions, roots file...
  cluster-phones $dir/treeacc $lang/phones/sets.int $dir/questions.int 2> $dir/log/questions.log || exit 1;
  cat $lang/phones/extra_questions.int >> $dir/questions.int
  compile-questions $lang/topo $dir/questions.int $dir/questions.qst 2>$dir/log/compile_questions.log || exit 1;

  echo "$0: Building the tree"
  $cmd $dir/log/build_tree.log \
    build-tree-two-level --binary=false --verbose=1 --max-leaves-first=$num_groups \
     --max-leaves-second=$num_pdfs $dir/treeacc $lang/phones/roots.int \
     $dir/questions.qst $lang/topo $dir/tree $dir/pdf2group.map || exit 1;
fi

if [ $stage -le -4 ]; then
  echo "$0: Initializing the model"  
  # Note: if phn_dim > feat_dim+1 or spk_dim > feat_dim, these dims
  # will be truncated on initialization.
  $cmd $dir/log/init_sgmm.log \
    sgmm2-init --spk-dep-weights=$spk_dep_weights --self-weight=$self_weight \
       --pdf-map=$dir/pdf2group.map --phn-space-dim=$phn_dim \
       --spk-space-dim=$spk_dim $lang/topo $dir/tree $ubm $dir/0.mdl || exit 1;
fi

if [ $stage -le -3 ]; then
  echo "$0: doing Gaussian selection"
  $cmd JOB=1:$nj $dir/log/gselect.JOB.log \
    sgmm2-gselect $dir/0.mdl "$feats" \
    "ark,t:|gzip -c >$dir/gselect.JOB.gz" || exit 1;
fi

if [ $stage -le -2 ]; then
  echo "$0: compiling training graphs"
  text="ark:sym2int.pl --map-oov $oov -f 2- $lang/words.txt < $sdata1/JOB/text|"
  $cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \
    compile-train-graphs $dir/tree $dir/0.mdl  $lang/L.fst  \
    "$text" "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1;
fi

if [ $stage -le -1 ]; then
  echo "$0: converting alignments" 
  $cmd JOB=1:$nj $dir/log/convert_ali.JOB.log \
    convert-ali $alidir/final.mdl $dir/0.mdl $dir/tree "ark:gunzip -c $alidir/ali.JOB.gz|" \
    "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
fi


x=0
while [ $x -lt $num_iters ]; do
   echo "$0: training pass $x ... "
   if echo $realign_iters | grep -w $x >/dev/null && [ $stage -le $x ]; then
     echo "$0: re-aligning data"
     $cmd JOB=1:$nj $dir/log/align.$x.JOB.log  \
       sgmm2-align-compiled $spkvecs_opt $scale_opts "$gselect_opt" \
       --utt2spk=ark:$sdata1/JOB/utt2spk --beam=$beam --retry-beam=$retry_beam \
       $dir/$x.mdl "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" \
       "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
   fi
   if [ $spk_dim -gt 0 ] && echo $spkvec_iters | grep -w $x >/dev/null; then
     if [ $stage -le $x ]; then
       $cmd JOB=1:$nj $dir/log/spkvecs.$x.JOB.log \
         ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
         weight-silence-post 0.01 $silphonelist $dir/$x.mdl ark:- ark:- \| \
         sgmm2-est-spkvecs --rand-prune=$rand_prune --spk2utt=ark:$sdata1/JOB/spk2utt \
         $spkvecs_opt "$gselect_opt" $dir/$x.mdl "$feats" ark,s,cs:- \
         ark:$dir/tmp_vecs.JOB '&&' mv $dir/tmp_vecs.JOB $dir/vecs.JOB || exit 1;
     fi
     spkvecs_opt="--spk-vecs=ark:$dir/vecs.JOB"
   fi  
   if [ $x -eq 0 ]; then
     flags=vwcSt # on the first iteration, don't update projections M or N
   elif [ $spk_dim -gt 0 -a $[$x%2] -eq 1 -a $x -ge $first_spkvec_iter ]; then 
     # Update N if we have speaker-vector space and x is odd,
     # and we've already updated the speaker vectors...
     flags=vNwSct
   else
     if [ $x -ge $update_m_iter ]; then
       flags=vMwSct # udpate M.
     else
       flags=vwSct # no M on early iters, if --update-m-iter option given.
     fi
   fi
   $spk_dep_weights && [ $x -ge $first_spkvec_iter ] && flags=${flags}u; # update 
   # spk-weight projections "u".
   
   if [ $stage -le $x ]; then
     $cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \
       sgmm2-acc-stats $spkvecs_opt --utt2spk=ark:$sdata1/JOB/utt2spk \
       --update-flags=$flags "$gselect_opt" --rand-prune=$rand_prune \
       $dir/$x.mdl "$feats" "ark,s,cs:gunzip -c $dir/ali.JOB.gz | ali-to-post ark:- ark:-|" \
       $dir/$x.JOB.acc || exit 1;
   fi

   # The next option is needed if the user specifies a phone or speaker sub-space
   # dimension that's higher than the "normal" one.
   increase_dim_opts=
   if echo $increase_dim_iters | grep -w $x >/dev/null; then
     increase_dim_opts="--increase-phn-dim=$phn_dim --increase-spk-dim=$spk_dim"
     # Note: the command below might have a null effect on some iterations.
     if [ $spk_dim -gt $feat_dim ]; then 
       cmd JOB=1:$nj $dir/log/copy_vecs.$x.JOB.log \
         copy-vector --print-args=false --change-dim=$spk_dim \
         ark:$dir/vecs.JOB ark:$dir/vecs_tmp.$JOB '&&' \
         mv $dir/vecs_tmp.JOB $dir/vecs.JOB || exit 1;
     fi
   fi

   if [ $stage -le $x ]; then
     $cmd $dir/log/update.$x.log \
       sgmm2-est --update-flags=$flags --split-substates=$numsubstates \
       $increase_dim_opts --power=$power --write-occs=$dir/$[$x+1].occs \
       $dir/$x.mdl "sgmm2-sum-accs - $dir/$x.*.acc|" $dir/$[$x+1].mdl || exit 1;
     rm $dir/$x.mdl $dir/$x.*.acc $dir/$x.occs 2>/dev/null
   fi
   if [ $x -lt $max_iter_inc ]; then
     numsubstates=$[$numsubstates+$incsubstates]
   fi
   x=$[$x+1];
done

rm $dir/final.mdl $dir/final.occs 2>/dev/null
ln -s $x.mdl $dir/final.mdl
ln -s $x.occs $dir/final.occs

if [ $spk_dim -gt 0 ]; then
  # We need to create an "alignment model" that's been trained
  # without the speaker vectors, to do the first-pass decoding with.
  # in test time.

  # We do this for a few iters, in this recipe.
  final_mdl=$dir/$x.mdl
  cur_alimdl=$dir/$x.mdl
  while [ $x -lt $[$num_iters+$num_iters_alimdl] ]; do
    echo "$0: building alignment model (pass $x)"
    if [ $x -eq $num_iters ]; then # 1st pass of building alimdl.
      flags=MwcS # don't update v the first time.  Note-- we never update transitions.
      # they wouldn't change anyway as we use the same alignment as previously.
    else
      flags=vMwcS
    fi
    if [ $stage -le $x ]; then
      $cmd JOB=1:$nj $dir/log/acc_ali.$x.JOB.log \
        ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
        sgmm2-post-to-gpost $spkvecs_opt "$gselect_opt" \
         --utt2spk=ark:$sdata1/JOB/utt2spk $final_mdl "$feats" ark,s,cs:- ark:- \| \
        sgmm2-acc-stats-gpost --rand-prune=$rand_prune --update-flags=$flags \
          $cur_alimdl "$feats" ark,s,cs:- $dir/$x.JOB.aliacc || exit 1;
      $cmd $dir/log/update_ali.$x.log \
        sgmm2-est --update-flags=$flags --remove-speaker-space=true --power=$power \
        $cur_alimdl "sgmm2-sum-accs - $dir/$x.*.aliacc|" $dir/$[$x+1].alimdl || exit 1;
      rm $dir/$x.*.aliacc || exit 1;
      [ $x -gt $num_iters ]  && rm $dir/$x.alimdl
    fi
    cur_alimdl=$dir/$[$x+1].alimdl
    x=$[$x+1]
  done
  rm $dir/final.alimdl 2>/dev/null 
  ln -s $x.alimdl $dir/final.alimdl
fi

utils/summarize_warnings.pl $dir/log

echo Done