#!/bin/bash
# Copyright 2012-2013 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=
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="-pe smp 2"

echo "$0 $@"  # Print the command line for logging

[ -f ./path.sh ] && . ./path.sh; # source the path.
. parse_options.sh || exit 1;

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

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("\n"); }' | \
  utils/make_unigram_grammar.pl | fstcompile > $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
# 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=$delta_order ark:- ark:- |"
fi
# Finally add feature_transform and the MLP
feats="$feats nnet-forward --feature-transform=$feature_transform --no-softmax=true --class-frame-counts=$class_frame_counts --use-gpu=$use_gpu $nnet ark:- ark:- |"


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 '{ print $1" | gzip -c >'$dir'/lat'$n'/"$1".gz"; }' 
  done >$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
  for n in `seq $nj`; do
    if [ -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)";
    else
      sdata2=$data/split$nj/$n/split$sub_split;
      if [ ! -d $sdata2 ] || [ $sdata2 -ot $sdata/$n/feats.scp ]; then
        split_data.sh --per-utt $sdata/$n $sub_split || exit 1;
      fi
      mkdir -p $dir/log/$n
      feats_subset=$(echo $feats | sed s:JOB/:$n/split$sub_split/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 '{ print $1" | gzip -c >'$dir'/lat'$n'/'$k'/"$1".gz"; }' 
      done >$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 || exit 1;
      touch $dir/.done.$n
    fi
  done
fi

#2) Generate 'scp' for reading the lattices
for n in `seq $nj`; do
  find $dir/lat${n} -name "*.gz" | awk -v FS="/" '{ print gensub(".gz","","",$NF)" gunzip -c "$0" |"; }' 
done >$dir/lat.scp

echo "$0: done generating denominator lattices."