#!/bin/bash
  
  # Copyright 2012  Johns Hopkins University (Author: Daniel Povey).
  # Apache 2.0.
  
  # This script does decoding with a neural-net.  If the neural net was built on
  # top of fMLLR transforms from a conventional system, you should provide the
  # --transform-dir option.
  
  # Begin configuration section.
  stage=1
  transform_dir=    # dir to find fMLLR transforms.
  nj=4 # number of decoding jobs.  If --transform-dir set, must match that number!
  acwt=0.1  # Just a default value, used for adaptation and beam-pruning..
  cmd=run.pl
  beam=15.0
  max_active=7000
  
  #WARNING: This option is renamed lat_beam (it was renamed to follow the naming 
  #         in the other scripts
  lattice_beam=8.0 # Beam we use in lattice generation.
  iter=final
  num_threads=1 # if >1, will use gmm-latgen-faster-parallel
  parallel_opts=  # If you supply num-threads, you should supply this too.
  scoring_opts=
  skip_scoring=false
  feat_type=
  # End configuration section.
  
  echo "$0 $@"  # Print the command line for logging
  
  [ -f ./path.sh ] && . ./path.sh; # source the path.
  . parse_options.sh || exit 1;
  
  if [ $# -ne 3 ]; then
    echo "Usage: steps/decode_nnet_cpu.sh [options] <graph-dir> <data-dir> <decode-dir>"
    echo " e.g.: steps/decode_nnet_cpu.sh --transform-dir exp/tri3b/decode_dev93_tgpr \\"
    echo "      exp/tri3b/graph_tgpr data/test_dev93 exp/tri4a_nnet/decode_dev93_tgpr"
    echo "main options (for others, see top of script file)"
    echo "  --transform-dir <decoding-dir>           # directory of previous decoding"
    echo "                                           # where we can find transforms for SAT systems."
    echo "  --config <config-file>                   # config containing options"
    echo "  --nj <nj>                                # number of parallel jobs"
    echo "  --cmd <cmd>                              # Command to run in parallel with"
    echo "  --beam <beam>                            # Decoding beam; default 15.0"
    echo "  --iter <iter>                            # Iteration of model to decode; default is final."
    echo "  --scoring-opts <string>                  # options to local/score.sh"
    echo "  --num-threads <n>                        # number of threads to use, default 1."
    echo "  --parallel-opts <opts>                   # e.g. '-pe smp 4' if you supply --num-threads 4"
    exit 1;
  fi
  
  graphdir=$1
  data=$2
  dir=$3
  srcdir=`dirname $dir`; # Assume model directory one level up from decoding directory.
  model=$srcdir/$iter.mdl
  
  for f in $graphdir/HCLG.fst $data/feats.scp $model; do
    [ ! -f $f ] && echo "$0: no such file $f" && exit 1;
  done
  
  sdata=$data/split$nj;
  splice_opts=`cat $srcdir/splice_opts 2>/dev/null`
  thread_string=
  [ $num_threads -gt 1 ] && thread_string="-parallel --num-threads=$num_threads" 
  
  mkdir -p $dir/log
  [[ -d $sdata && $data/feats.scp -ot $sdata ]] || split_data.sh $data $nj || exit 1;
  echo $nj > $dir/num_jobs
  
  
  ## Set up features.
  if [ -z "$feat_type" ]; then
    if [ -f $srcdir/final.mat ]; then feat_type=lda; else feat_type=delta; fi
    echo "$0: feature type is $feat_type"
  fi
  
  case $feat_type in
    raw) feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- |";;
    delta) feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | add-deltas ark:- ark:- |";;
    lda) feats="ark,s,cs:apply-cmvn --norm-vars=false --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- | splice-feats $splice_opts ark:- ark:- | transform-feats $srcdir/final.mat ark:- ark:- |"
      ;;
    *) echo "$0: invalid feature type $feat_type" && exit 1;
  esac
  if [ ! -z "$transform_dir" ]; then
    echo "$0: using transforms from $transform_dir"
    if [ "$feat_type" == "raw" ]; then
      [ ! -f $transform_dir/raw_trans.1 ] && echo "$0: no such file $transform_dir/raw_trans.1" && exit 1;
      [ "$nj" -ne "`cat $transform_dir/num_jobs`" ] \
        && echo "$0: #jobs mismatch with transform-dir." && exit 1;
      feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$transform_dir/raw_trans.JOB ark:- ark:- |"
    else
      [ ! -f $transform_dir/trans.1 ] && echo "$0: no such file $transform_dir/trans.1" && exit 1;
      [ "$nj" -ne "`cat $transform_dir/num_jobs`" ] \
        && echo "$0: #jobs mismatch with transform-dir." && exit 1;
      feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark,s,cs:$transform_dir/trans.JOB ark:- ark:- |"
    fi
  elif grep 'transform-feats --utt2spk' $srcdir/log/train.1.log >&/dev/null; then
    echo "$0: **WARNING**: you seem to be using a neural net system trained with transforms,"
    echo "  but you are not providing the --transform-dir option in test time."
  fi
  ##
  
  
  if [ $stage -le 1 ]; then
    $cmd $parallel_opts JOB=1:$nj $dir/log/decode.JOB.log \
      nnet-latgen-faster$thread_string --max-active=$max_active --beam=$beam --lattice-beam=$lattice_beam \
      --acoustic-scale=$acwt --allow-partial=true --word-symbol-table=$graphdir/words.txt "$model" \
      $graphdir/HCLG.fst "$feats" "ark:|gzip -c > $dir/lat.JOB.gz" || exit 1;
  fi
  
  # The output of this script is the files "lat.*.gz"-- we'll rescore this at 
  # different acoustic scales to get the final output.
  
  
  if [ $stage -le 2 ]; then
    if ! $skip_scoring ; then
      [ ! -x local/score.sh ] && \
        echo "Not scoring because local/score.sh does not exist or not executable." && exit 1;
      echo "score best paths"
      local/score.sh $scoring_opts --cmd "$cmd" $data $graphdir $dir
      echo "score confidence and timing with sclite"
    fi
  fi
  echo "Decoding done."
  exit 0;