#!/bin/bash
  # Copyright 2012  Johns Hopkins University (Author: Daniel Povey).  Apache 2.0.
  
  
  # This does Speaker Adapted Training (SAT).  We train on fMLLR-adapted features,
  # but in this "raw" script, these transforms are at the level of the raw
  # cepstra.  The model must be built on top of LDA+MLLT features, and the
  # transforms are estimated using the model, in a rather clever way.  If there
  # are no raw transforms supplied in the alignment directory, it will estimate
  # transforms itself before building the tree (and in any case, it estimates
  # transforms a number of times during training).
  # You need to decode the models it builds with decode_raw_fmllr.sh
  
  # Begin configuration section.
  stage=-6
  cmd=run.pl
  scale_opts="--transition-scale=1.0 --acoustic-scale=0.1 --self-loop-scale=0.1"
  beam=10
  retry_beam=40
  boost_silence=1.0 # Factor by which to boost silence likelihoods in alignment
  context_opts=  # e.g. set this to "--context-width 5 --central-position 2" for quinphone.
  realign_iters="10 20 30";
  fmllr_iters="2 4 6 12";
  mllt_iters="3 5 7 10"
  dim=40
  randprune=4.0 # This is approximately the ratio by which we will speed up the
                # LDA and MLLT calculations via randomized pruning.
  silence_weight=0.0 # Weight on silence in fMLLR estimation.
  num_iters=35   # Number of iterations of training
  max_iter_inc=25 # Last iter to increase #Gauss on.
  power=0.2 # Exponent for number of gaussians according to occurrence counts
  cluster_thresh=-1  # for build-tree control final bottom-up clustering of leaves
  phone_map=
  train_tree=true
  # End configuration section.
  
  echo "$0 $@"  # Print the command line for logging
  
  [ -f path.sh ] && . ./path.sh
  . parse_options.sh || exit 1;
  
  if [ $# != 6 ]; then
    echo "Usage: steps/train_sat.sh <#leaves> <#gauss> <data> <lang> <ali-dir> <exp-dir>"
    echo " e.g.: steps/train_sat.sh 2500 15000 data/train_si84 data/lang exp/tri2b_ali_si84 exp/tri3b"
    echo "Main options (for others, see top of script file)"
    echo "  --cmd (utils/run.pl|utils/queue.pl <queue opts>) # how to run jobs."
    echo "  --config <config-file>                           # config containing options"
    echo "  --stage <stage>                                  # stage to do partial re-run from."
    exit 1;
  fi
  
  numleaves=$1
  totgauss=$2
  data=$3
  lang=$4
  alidir=$5
  dir=$6
  
  for f in $data/feats.scp $lang/phones.txt $alidir/final.mdl $alidir/ali.1.gz; do
    [ ! -f $f ] && echo "train_sat.sh: no such file $f" && exit 1;
  done
  
  numgauss=$numleaves
  incgauss=$[($totgauss-$numgauss)/$max_iter_inc]  # per-iter #gauss increment
  oov=`cat $lang/oov.int`
  nj=`cat $alidir/num_jobs` || exit 1;
  silphonelist=`cat $lang/phones/silence.csl`
  ciphonelist=`cat $lang/phones/context_indep.csl` || exit 1;
  sdata=$data/split$nj;
  splice_opts=`cat $alidir/splice_opts 2>/dev/null` # frame-splicing options.
  phone_map_opt=
  [ ! -z "$phone_map" ] && phone_map_opt="--phone-map='$phone_map'"
  
  mkdir -p $dir/log
  cp $alidir/splice_opts $dir 2>/dev/null # frame-splicing options.
  
  echo $nj >$dir/num_jobs
  [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
  
  # Set up features.
  
  if [[ ! -f $alidir/final.mat || ! -f $alidir/full.mat ]]; then
    echo "$0: expected to find  $alidir/final.mat and $alidir/full.mat"
    exit 1
  fi
  
  sisplicedfeats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | splice-feats $splice_opts ark:- ark:- |"
  sifeats="$sisplicedfeats transform-feats $alidir/final.mat ark:- ark:- |"
  
  
  ## Get initial fMLLR transforms (possibly from alignment dir)
  if [ -f $alidir/raw_trans.1 ]; then
    echo "$0: Using transforms from $alidir"
    cur_trans_dir=$alidir
  else 
    if [ $stage -le -6 ]; then
      echo "$0: obtaining initial fMLLR transforms since not present in $alidir"
      # The next line is necessary because of $silphonelist otherwise being incorrect; would require
      # old $lang dir which would require another option.  Not needed anyway.
      [ ! -z "$phone_map" ] && \
         echo "$0: error: you must provide transforms if you use the --phone-map option." && exit 1;
      full_lda_mat="get-full-lda-mat --print-args=false $alidir/final.mat $alidir/full.mat -|"
      $cmd JOB=1:$nj $dir/log/fmllr.0.JOB.log \
        ali-to-post "ark:gunzip -c $alidir/ali.JOB.gz|" ark:- \| \
        weight-silence-post $silence_weight $silphonelist $alidir/final.mdl ark:- ark:- \| \
        gmm-est-fmllr-raw --spk2utt=ark:$sdata/JOB/spk2utt $alidir/final.mdl \
          "$full_lda_mat" "$sisplicedfeats" ark:- ark:$dir/raw_trans.JOB || exit 1;
    fi
    cur_trans_dir=$dir
  fi
  
  splicedfeats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$cur_trans_dir/raw_trans.JOB ark:- ark:- | splice-feats $splice_opts ark:- ark:- |"
  
  
  if [ $stage -le -5 ]; then
    echo "Accumulating LDA statistics."
    $cmd JOB=1:$nj $dir/log/lda_acc.JOB.log \
      ali-to-post "ark:gunzip -c $alidir/ali.JOB.gz|" ark:- \| \
        weight-silence-post 0.0 $silphonelist $alidir/final.mdl ark:- ark:- \| \
        acc-lda --rand-prune=$randprune $alidir/final.mdl "$splicedfeats" ark,s,cs:- \
         $dir/lda.JOB.acc || exit 1;
    est-lda --write-full-matrix=$dir/full.mat --dim=$dim $dir/0.mat $dir/lda.*.acc \
        2>$dir/log/lda_est.log || exit 1;  
    rm $dir/lda.*.acc
  fi
  
  cur_lda_iter=0
  feats="$splicedfeats transform-feats $dir/$cur_lda_iter.mat ark:- ark:- |"
  
  # To build the tree, we use the previous directory's LDA transform, which
  # is better as it has MLLT also.  It leads to higher auxiliary function
  # improvements in tree building, which is generally a good thing.
  tree_feats="$splicedfeats transform-feats $alidir/final.mat ark:- ark:- |"
  
  
  if [ $stage -le -4 ] && $train_tree; then
    # Get tree stats.
    echo "$0: Accumulating tree stats"
    $cmd JOB=1:$nj $dir/log/acc_tree.JOB.log \
      acc-tree-stats $context_opts --ci-phones=$ciphonelist $alidir/final.mdl "$tree_feats" \
      "ark:gunzip -c $alidir/ali.JOB.gz|" $dir/JOB.treeacc || exit 1;
    [ "`ls $dir/*.treeacc | wc -w`" -ne "$nj" ] && echo "$0: Wrong #tree-accs" && exit 1;
    $cmd $dir/log/sum_tree_acc.log \
      sum-tree-stats $dir/treeacc $dir/*.treeacc || exit 1;
    rm $dir/*.treeacc
  fi
  
  if [ $stage -le -3 ] && $train_tree; then
    echo "$0: Getting questions for tree clustering."
    # preparing questions, roots file...
    cluster-phones $context_opts $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 $context_opts $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 $context_opts --verbose=1 --max-leaves=$numleaves \
      --cluster-thresh=$cluster_thresh $dir/treeacc $lang/phones/roots.int \
      $dir/questions.qst $lang/topo $dir/tree || exit 1;
  fi
  
  if [ $stage -le -2 ]; then
    echo "$0: Initializing the model"
    # Since we trained the tree on different feats, we don't use gmm-init-model, which
    # would initialize the tree with invalid features.  This doesn't really matter anyway,
    # the first iteration of training will set suitable initial parameters.
    cp $alidir/tree $dir/ || exit 1;
    $cmd JOB=1 $dir/log/init_model.log \
      gmm-init-model-flat $dir/tree $lang/topo $dir/1.mdl \
      "$tree_feats subset-feats ark:- ark:-|" || exit 1;
  fi
  
  if [ $stage -le -1 ]; then
    # Convert the alignments.
    echo "$0: Converting alignments from $alidir to use current tree"
    $cmd JOB=1:$nj $dir/log/convert.JOB.log \
      convert-ali $phone_map_opt $alidir/final.mdl $dir/1.mdl $dir/tree \
       "ark:gunzip -c $alidir/ali.JOB.gz|" "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
  fi
  
  if [ $stage -le 0 ] && [ "$realign_iters" != "" ]; then
    echo "$0: Compiling graphs of transcripts"
    $cmd JOB=1:$nj $dir/log/compile_graphs.JOB.log \
      compile-train-graphs $dir/tree $dir/1.mdl  $lang/L.fst  \
       "ark:utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt < $sdata/JOB/text |" \
        "ark:|gzip -c >$dir/fsts.JOB.gz" || exit 1;
  fi
  
  x=1
  while [ $x -lt $num_iters ]; do
     echo Pass $x
    if echo $realign_iters | grep -w $x >/dev/null && [ $stage -le $x ]; then
      echo Aligning data
      mdl="gmm-boost-silence --boost=$boost_silence `cat $lang/phones/optional_silence.csl` $dir/$x.mdl - |"
      $cmd JOB=1:$nj $dir/log/align.$x.JOB.log \
        gmm-align-compiled $scale_opts --beam=$beam --retry-beam=$retry_beam "$mdl" \
        "ark:gunzip -c $dir/fsts.JOB.gz|" "$feats" \
        "ark:|gzip -c >$dir/ali.JOB.gz" || exit 1;
    fi
  
    if echo $fmllr_iters | grep -w $x >/dev/null; then
      if [ $stage -le $x ]; then
        echo Estimating fMLLR transforms
        # We estimate a transform that's additional to the previous transform;
        # we'll compose them.
  
        full_lda_mat="get-full-lda-mat --print-args=false $dir/$cur_lda_iter.mat $dir/full.mat - |"
        $cmd JOB=1:$nj $dir/log/fmllr.$x.JOB.log \
          ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:-  \| \
          weight-silence-post $silence_weight $silphonelist $dir/$x.mdl ark:- ark:- \| \
          gmm-est-fmllr-raw --spk2utt=ark:$sdata/JOB/spk2utt $dir/$x.mdl "$full_lda_mat" \
            "$splicedfeats" ark:- ark:$dir/tmp_trans.JOB || exit 1;
        for n in `seq $nj`; do
          ! ( compose-transforms --b-is-affine=true \
            ark:$dir/tmp_trans.$n ark:$cur_trans_dir/raw_trans.$n ark:$dir/composed_trans.$n \
            && mv $dir/composed_trans.$n $dir/raw_trans.$n && \
            rm $dir/tmp_trans.$n ) 2>$dir/log/compose_transforms.$x.log \
            && echo "$0: Error composing transforms" && exit 1;
        done
      fi
      cur_trans_dir=$dir
      splicedfeats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$cur_trans_dir/raw_trans.JOB ark:- ark:- | splice-feats $splice_opts ark:- ark:- |"
      feats="$splicedfeats transform-feats $dir/$cur_lda_iter.mat ark:- ark:- |"
    fi
  
    if echo $mllt_iters | grep -w $x >/dev/null; then
      if [ $stage -le $x ]; then
        echo "Estimating MLLT"
        $cmd JOB=1:$nj $dir/log/macc.$x.JOB.log \
          ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:- \| \
          weight-silence-post 0.0 $silphonelist $dir/$x.mdl ark:- ark:- \| \
          gmm-acc-mllt --rand-prune=$randprune  $dir/$x.mdl "$feats" ark:- $dir/$x.JOB.macc \
          || exit 1;
        est-mllt $dir/$x.mat.new $dir/$x.*.macc 2> $dir/log/mupdate.$x.log || exit 1;
        gmm-transform-means  $dir/$x.mat.new $dir/$x.mdl $dir/$x.mdl \
          2> $dir/log/transform_means.$x.log || exit 1;
        compose-transforms --print-args=false $dir/$x.mat.new $dir/$cur_lda_iter.mat $dir/$x.mat || exit 1;
        rm $dir/$x.*.macc
      fi
      cur_lda_iter=$x
      feats="$splicedfeats transform-feats $dir/$cur_lda_iter.mat ark:- ark:- |"
    fi
    
    if [ $stage -le $x ]; then
      $cmd JOB=1:$nj $dir/log/acc.$x.JOB.log \
        gmm-acc-stats-ali $dir/$x.mdl "$feats" \
        "ark,s,cs:gunzip -c $dir/ali.JOB.gz|" $dir/$x.JOB.acc || exit 1;
      [ `ls $dir/$x.*.acc | wc -w` -ne "$nj" ] && echo "$0: Wrong #accs" && exit 1;
      $cmd $dir/log/update.$x.log \
        gmm-est --power=$power --write-occs=$dir/$[$x+1].occs --mix-up=$numgauss $dir/$x.mdl \
        "gmm-sum-accs - $dir/$x.*.acc |" $dir/$[$x+1].mdl || exit 1;
      rm $dir/$x.mdl $dir/$x.*.acc
      rm $dir/$x.occs 2>/dev/null
    fi
    [ $x -le $max_iter_inc ] && numgauss=$[$numgauss+$incgauss];
    x=$[$x+1];
  done
  
  
  if [ $stage -le $x ]; then
    # Accumulate stats for "alignment model"-- this model is
    # computed with the speaker-independent features, but matches Gaussian-for-Gaussian
    # with the final speaker-adapted model.
    sifeats="$sisplicedfeats transform-feats $dir/$cur_lda_iter.mat ark:- ark:- |"
    $cmd JOB=1:$nj $dir/log/acc_alimdl.JOB.log \
      ali-to-post "ark:gunzip -c $dir/ali.JOB.gz|" ark:-  \| \
      gmm-acc-stats-twofeats $dir/$x.mdl "$feats" "$sifeats" \
      ark,s,cs:- $dir/$x.JOB.acc || exit 1;
    [ `ls $dir/$x.*.acc | wc -w` -ne "$nj" ] && echo "$0: Wrong #accs" && exit 1;
    # Update model.
    $cmd $dir/log/est_alimdl.log \
      gmm-est --power=$power --remove-low-count-gaussians=false $dir/$x.mdl \
      "gmm-sum-accs - $dir/$x.*.acc|" $dir/$x.alimdl  || exit 1;
    rm $dir/$x.*.acc
  fi
  
  rm $dir/final.{mdl,alimdl,mat,occs} 2>/dev/null
  ln -s $x.mdl $dir/final.mdl
  ln -s $x.occs $dir/final.occs
  ln -s $x.alimdl $dir/final.alimdl
  ln -s $cur_lda_iter.mat $dir/final.mat
  
  
  utils/summarize_warnings.pl $dir/log
  (
    echo "$0: Likelihood evolution (not sure if this is totally correct):"
    for x in `seq $[$num_iters-1]`; do
      tail -n 30 $dir/log/acc.$x.*.log | awk '/Overall avg like/{l += $(NF-3)*$(NF-1); t += $(NF-1); }
          /Overall average logdet/{d += $(NF-3)*$(NF-1); t2 += $(NF-1);} 
          END{ d /= t2; l /= t; printf("%s ", d+l); } '
    done
    echo
  ) | tee $dir/log/summary.log
  
  echo Done