#!/bin/bash
  # Copyright 2012-2013 Brno University of Technology (author: Karel Vesely), Daniel Povey
  # Apache 2.0.
  
  # Create denominator lattices for MMI/MPE/sMBR training.
  # Creates its output in $dir/lat.*.ark,$dir/lat.scp
  # The lattices are uncompressed, we need random access for DNN training.
  
  # Begin configuration section.
  nj=4
  cmd=run.pl
  sub_split=1
  beam=13.0
  lattice_beam=7.0
  acwt=0.1
  max_active=5000
  nnet=
  nnet_forward_opts="--no-softmax=true --prior-scale=1.0"
  max_mem=20000000 # This will stop the processes getting too large.
  # This is in bytes, but not "real" bytes-- you have to multiply
  # by something like 5 or 10 to get real bytes (not sure why so large)
  # End configuration section.
  use_gpu=no # yes|no|optional
  parallel_opts="--num-threads 2"
  ivector=         # rx-specifier with i-vectors (ark-with-vectors),
  
  echo "$0 $@"  # Print the command line for logging
  
  [ -f ./path.sh ] && . ./path.sh; # source the path.
  . parse_options.sh || exit 1;
  
  set -euo pipefail
  
  if [ $# != 4 ]; then
     echo "Usage: steps/$0 [options] <data-dir> <lang-dir> <src-dir> <exp-dir>"
     echo "  e.g.: steps/$0 data/train data/lang exp/tri1 exp/tri1_denlats"
     echo "Works for plain features (or CMN, delta), forwarded through feature-transform."
     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 "  --sub-split <n-split>                            # e.g. 40; use this for "
     echo "                           # large databases so your jobs will be smaller and"
     echo "                           # will (individually) finish reasonably soon."
     exit 1;
  fi
  
  data=$1
  lang=$2
  srcdir=$3
  dir=$4
  
  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
  
  oov=`cat $lang/oov.int` || exit 1;
  
  mkdir -p $dir
  
  utils/lang/check_phones_compatible.sh $lang/phones.txt $srcdir/phones.txt
  
  cp -r $lang $dir/
  
  # Compute grammar FST which corresponds to unigram decoding graph.
  new_lang="$dir/"$(basename "$lang")
  echo "Making unigram grammar FST in $new_lang"
  cat $data/text | utils/sym2int.pl --map-oov $oov -f 2- $lang/words.txt | \
    awk '{for(n=2;n<=NF;n++){ printf("%s ", $n); } printf("
  "); }' | \
    utils/make_unigram_grammar.pl | fstcompile | fstarcsort --sort_type=ilabel > $new_lang/G.fst \
     || exit 1;
  
  # mkgraph.sh expects a whole directory "lang", so put everything in one directory...
  # it gets L_disambig.fst and G.fst (among other things) from $dir/lang, and
  # final.mdl from $srcdir; the output HCLG.fst goes in $dir/graph.
  
  echo "Compiling decoding graph in $dir/dengraph"
  if [ -s $dir/dengraph/HCLG.fst ] && [ $dir/dengraph/HCLG.fst -nt $srcdir/final.mdl ]; then
     echo "Graph $dir/dengraph/HCLG.fst already exists: skipping graph creation."
  else
    utils/mkgraph.sh $new_lang $srcdir $dir/dengraph || exit 1;
  fi
  
  
  cp $srcdir/{tree,final.mdl} $dir
  
  # Select default locations to model files
  [ -z "$nnet" ] && nnet=$srcdir/final.nnet;
  class_frame_counts=$srcdir/ali_train_pdf.counts
  feature_transform=$srcdir/final.feature_transform
  model=$dir/final.mdl
  
  # Check that files exist
  for f in $sdata/1/feats.scp $nnet $model $feature_transform $class_frame_counts; do
    [ ! -f $f ] && echo "$0: missing file $f" && exit 1;
  done
  
  
  # PREPARE FEATURE EXTRACTION PIPELINE
  # import config,
  cmvn_opts=
  delta_opts=
  D=$srcdir
  [ -e $D/norm_vars ] && cmvn_opts="--norm-means=true --norm-vars=$(cat $D/norm_vars)" # Bwd-compatibility,
  [ -e $D/cmvn_opts ] && cmvn_opts=$(cat $D/cmvn_opts)
  [ -e $D/delta_order ] && delta_opts="--delta-order=$(cat $D/delta_order)" # Bwd-compatibility,
  [ -e $D/delta_opts ] && delta_opts=$(cat $D/delta_opts)
  #
  # Create the feature stream,
  feats="ark,s,cs:copy-feats scp:$sdata/JOB/feats.scp ark:- |"
  # apply-cmvn (optional),
  [ ! -z "$cmvn_opts" -a ! -f $sdata/1/cmvn.scp ] && echo "$0: Missing $sdata/1/cmvn.scp" && exit 1
  [ ! -z "$cmvn_opts" ] && feats="$feats apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp ark:- ark:- |"
  # add-deltas (optional),
  [ ! -z "$delta_opts" ] && feats="$feats add-deltas $delta_opts ark:- ark:- |"
  # add-pytel transform (optional),
  [ -e $D/pytel_transform.py ] && feats="$feats /bin/env python $D/pytel_transform.py |"
  
  # add-ivector (optional),
  if [ -e $D/ivector_dim ]; then
    [ -z $ivector ] && echo "Missing --ivector, they were used in training!" && exit 1
    # Get the tool,
    ivector_append_tool=append-vector-to-feats # default,
    [ -e $D/ivector_append_tool ] && ivector_append_tool=$(cat $D/ivector_append_tool)
    # Check dims,
    feats_job_1=$(sed 's:JOB:1:g' <(echo $feats))
    dim_raw=$(feat-to-dim "$feats_job_1" -)
    dim_raw_and_ivec=$(feat-to-dim "$feats_job_1 $ivector_append_tool ark:- '$ivector' ark:- |" -)
    dim_ivec=$((dim_raw_and_ivec - dim_raw))
    [ $dim_ivec != "$(cat $D/ivector_dim)" ] && \
      echo "Error, i-vector dim. mismatch (expected $(cat $D/ivector_dim), got $dim_ivec in '$ivector')" && \
      exit 1
    # Append to feats,
    feats="$feats $ivector_append_tool ark:- '$ivector' ark:- |"
  fi
  
  # nnet-forward,
  feats="$feats nnet-forward $nnet_forward_opts --feature-transform=$feature_transform --class-frame-counts=$class_frame_counts --use-gpu=$use_gpu $nnet ark:- ark:- |"
  
  # if this job is interrupted by the user, we want any background jobs to be
  # killed too.
  cleanup() {
    local pids=$(jobs -pr)
    [ -n "$pids" ] && kill $pids || true
  }
  trap "cleanup" INT QUIT TERM EXIT
  
  
  echo "$0: generating denlats from data '$data', putting lattices in '$dir'"
  #1) Generate the denominator lattices
  if [ $sub_split -eq 1 ]; then
    # Prepare 'scp' for storing lattices separately and gzipped
    for n in `seq $nj`; do
      [ ! -d $dir/lat$n ] && mkdir $dir/lat$n;
      cat $sdata/$n/feats.scp | \
      awk -v dir=$dir -v n=$n '{ utt=$1; utt_noslash=utt; gsub("/","_",utt_noslash);
                                 printf("%s | gzip -c >%s/lat%d/%s.gz
  ", utt, dir, n, utt_noslash); }'
    done >$dir/lat.store_separately_as_gz.scp
    # Generate the lattices
    $cmd $parallel_opts JOB=1:$nj $dir/log/decode_den.JOB.log \
      latgen-faster-mapped --beam=$beam --lattice-beam=$lattice_beam --acoustic-scale=$acwt \
        --max-mem=$max_mem --max-active=$max_active --word-symbol-table=$lang/words.txt $srcdir/final.mdl  \
        $dir/dengraph/HCLG.fst "$feats" "scp:$dir/lat.store_separately_as_gz.scp" || exit 1;
  else
    # each job from 1 to $nj is split into multiple pieces (sub-split), and we aim
    # to have at most two jobs running at each time.  The idea is that if we have stragglers
    # from one job, we can be processing another one at the same time.
    rm -f $dir/.error
  
    prev_pid=
    for n in `seq $[nj+1]`; do
      if [ $n -gt $nj ]; then
        this_pid=
      elif [ -f $dir/.done.$n ] && [ $dir/.done.$n -nt $srcdir/final.mdl ]; then
        echo "Not processing subset $n as already done (delete $dir/.done.$n if not)";
        this_pid=
      else
        sdata2=$data/split$nj/$n/split${sub_split}utt;
        split_data.sh --per-utt $sdata/$n $sub_split || exit 1;
        mkdir -p $dir/log/$n
        mkdir -p $dir/part
        feats_subset=$(echo $feats | sed s:JOB/:$n/split${sub_split}utt/JOB/:g)
        # Prepare 'scp' for storing lattices separately and gzipped
        for k in `seq $sub_split`; do
          [ ! -d $dir/lat$n/$k ] && mkdir -p $dir/lat$n/$k;
          cat $sdata2/$k/feats.scp | \
          awk -v dir=$dir -v n=$n -v k=$k '{ utt=$1; utt_noslash=utt; gsub("/","_",utt_noslash);
                                             printf("%s | gzip -c >%s/lat%d/%d/%s.gz
  ", utt, dir, n, k, utt_noslash); }'
        done >$dir/lat.${n}.store_separately_as_gz.scp
        # Generate lattices
        $cmd $parallel_opts JOB=1:$sub_split $dir/log/$n/decode_den.JOB.log \
          latgen-faster-mapped --beam=$beam --lattice-beam=$lattice_beam --acoustic-scale=$acwt \
            --max-mem=$max_mem --max-active=$max_active --word-symbol-table=$lang/words.txt $srcdir/final.mdl  \
            $dir/dengraph/HCLG.fst "$feats_subset" scp:$dir/lat.$n.store_separately_as_gz.scp || touch .error &
        this_pid=$!
      fi
      if [ ! -z "$prev_pid" ]; then  # Wait for the previous job; merge the previous set of lattices.
        wait $prev_pid
        [ -f $dir/.error ] && echo "$0: error generating denominator lattices" && exit 1;
        touch $dir/.done.$prev_n
      fi
      prev_n=$n
      prev_pid=$this_pid
    done
  fi
  
  #2) Generate 'scp' for reading the lattices
  # make $dir an absolute pathname.
  [ '/' != ${dir:0:1} ] && dir=$PWD/$dir
  for n in `seq $nj`; do
    find $dir/lat${n} -name "*.gz" | perl -ape 's:.*/([^/]+)\.gz$:$1 gunzip -c $& |:; '
  done | sort >$dir/lat.scp
  [ -s $dir/lat.scp ] || exit 1
  
  echo "$0: done generating denominator lattices."