#!/bin/bash
  
  # Copyright 2012-2015 Brno University of Technology (author: Karel Vesely), Daniel Povey
  # Apache 2.0
  
  # Begin configuration section.
  nnet=               # non-default location of DNN (optional)
  feature_transform=  # non-default location of feature_transform (optional)
  model=              # non-default location of transition model (optional)
  class_frame_counts= # non-default location of PDF counts (optional)
  srcdir=             # non-default location of DNN-dir (decouples model dir from decode dir)
  ivector=            # rx-specifier with i-vectors (ark-with-vectors),
  
  blocksoftmax_dims=   # 'csl' with block-softmax dimensions: dim1,dim2,dim3,...
  blocksoftmax_active= # '1' for the 1st block,
  
  stage=0 # stage=1 skips lattice generation
  nj=4
  cmd=run.pl
  
  acwt=0.10 # note: only really affects pruning (scoring is on lattices).
  beam=13.0
  lattice_beam=8.0
  min_active=200
  max_active=7000 # limit of active tokens
  max_mem=50000000 # approx. limit to memory consumption during minimization in bytes
  nnet_forward_opts="--no-softmax=true --prior-scale=1.0"
  
  skip_scoring=false
  scoring_opts="--min-lmwt 4 --max-lmwt 15"
  
  num_threads=1 # if >1, will use latgen-faster-parallel
  parallel_opts=   # Ignored now.
  use_gpu="no" # yes|no|optionaly
  # End configuration section.
  
  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 [ $# != 3 ]; then
     echo "Usage: $0 [options] <graph-dir> <data-dir> <decode-dir>"
     echo "... where <decode-dir> is assumed to be a sub-directory of the directory"
     echo " where the DNN and transition model is."
     echo "e.g.: $0 exp/dnn1/graph_tgpr data/test exp/dnn1/decode_tgpr"
     echo ""
     echo "This script works on plain or modified features (CMN,delta+delta-delta),"
     echo "which are then sent through feature-transform. It works out what type"
     echo "of features you used from content of srcdir."
     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 ""
     echo "  --nnet <nnet>                                    # non-default location of DNN (opt.)"
     echo "  --srcdir <dir>                                   # non-default dir with DNN/models, can be different"
     echo "                                                   # from parent dir of <decode-dir>' (opt.)"
     echo ""
     echo "  --acwt <float>                                   # select acoustic scale for decoding"
     echo "  --scoring-opts <opts>                            # options forwarded to local/score.sh"
     echo "  --num-threads <N>                                # N>1: run multi-threaded decoder"
     exit 1;
  fi
  
  
  graphdir=$1
  data=$2
  dir=$3
  [ -z $srcdir ] && srcdir=`dirname $dir`; # Default model directory one level up from decoding directory.
  sdata=$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
  
  # Select default locations to model files (if not already set externally)
  [ -z "$nnet" ] && nnet=$srcdir/final.nnet
  [ -z "$model" ] && model=$srcdir/final.mdl
  [ -z "$feature_transform" -a -e $srcdir/final.feature_transform ] && feature_transform=$srcdir/final.feature_transform
  #
  [ -z "$class_frame_counts" -a -f $srcdir/prior_counts ] && class_frame_counts=$srcdir/prior_counts # priority,
  [ -z "$class_frame_counts" ] && class_frame_counts=$srcdir/ali_train_pdf.counts
  
  # Check that files exist,
  for f in $sdata/1/feats.scp $nnet $model $feature_transform $class_frame_counts $graphdir/HCLG.fst; do
    [ ! -f $f ] && echo "$0: missing file $f" && exit 1;
  done
  
  # Possibly use multi-threaded decoder
  thread_string=
  [ $num_threads -gt 1 ] && thread_string="-parallel --num-threads=$num_threads"
  
  
  # PREPARE FEATURE EXTRACTION PIPELINE
  # import config,
  online_cmvn_opts=
  cmvn_opts=
  delta_opts=
  D=$srcdir
  [ -e $D/online_cmvn_opts ] && online_cmvn_opts=$(cat $D/online_cmvn_opts)
  [ -e $D/cmvn_opts ] && cmvn_opts=$(cat $D/cmvn_opts)
  [ -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-online (optional),
  [ -n "$online_cmvn_opts" -a ! -f $nndir/global_cmvn_stats.mat ] && echo "$0: Missing $nndir/global_cmvn_stats.mat" && exit 1
  [ -n "$online_cmvn_opts" ] && feats="$feats apply-cmvn-online $online_cmvn_opts --spk2utt=ark:$srcdata/spk2utt $nndir/global_cmvn_stats.mat ark:- ark:- |"
  # apply-cmvn (optional),
  [ -n "$cmvn_opts" -a ! -f $sdata/1/cmvn.scp ] && echo "$0: Missing $sdata/1/cmvn.scp" && exit 1
  [ -n "$cmvn_opts" ] && feats="$feats apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp ark:- ark:- |"
  # add-deltas (optional),
  [ -n "$delta_opts" ] && feats="$feats add-deltas $delta_opts ark:- ark:- |"
  
  # 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
  
  # select a block from blocksoftmax,
  if [ ! -z "$blocksoftmax_dims" ]; then
    # blocksoftmax_active is a csl! dim1,dim2,dim3,...
    [ -z "$blocksoftmax_active" ] && echo "$0 Missing option --blocksoftmax-active N" && exit 1
    # getting dims,
    dim_total=$(awk -F'[:,]' '{ for(i=1;i<=NF;i++) { sum += $i }; print sum; }' <(echo $blocksoftmax_dims))
    dim_block=$(awk -F'[:,]' -v active=$blocksoftmax_active '{ print $active; }' <(echo $blocksoftmax_dims))
    offset=$(awk -F'[:,]' -v active=$blocksoftmax_active '{ sum=0; for(i=1;i<active;i++) { sum += $i }; print sum; }' <(echo $blocksoftmax_dims))
    # create components which select a block,
    nnet-initialize <(echo "<Copy> <InputDim> $dim_total <OutputDim> $dim_block <BuildVector> $((1+offset)):$((offset+dim_block)) </BuildVector>";
                      echo "<Softmax> <InputDim> $dim_block <OutputDim> $dim_block") $dir/copy_and_softmax.nnet
    # nnet is assembled on-the fly, <BlockSoftmax> is removed, while <Copy> + <Softmax> is added,
    nnet="nnet-concat 'nnet-copy --remove-last-components=1 $nnet - |' $dir/copy_and_softmax.nnet - |"
  fi
  
  # Run the decoding in the queue,
  if [ $stage -le 0 ]; then
    $cmd --num-threads $((num_threads+1)) JOB=1:$nj $dir/log/decode.JOB.log \
      nnet-forward $nnet_forward_opts --feature-transform=$feature_transform --class-frame-counts=$class_frame_counts --use-gpu=$use_gpu "$nnet" "$feats" ark:- \| \
      latgen-faster-mapped$thread_string --min-active=$min_active --max-active=$max_active --max-mem=$max_mem --beam=$beam \
      --lattice-beam=$lattice_beam --acoustic-scale=$acwt --allow-partial=true --word-symbol-table=$graphdir/words.txt \
      $model $graphdir/HCLG.fst ark:- "ark:|gzip -c > $dir/lat.JOB.gz" || exit 1;
  fi
  
  # Run the scoring
  if ! $skip_scoring ; then
    [ ! -x local/score.sh ] && \
      echo "Not scoring because local/score.sh does not exist or not executable." && exit 1;
    local/score.sh $scoring_opts --cmd "$cmd" $data $graphdir $dir || exit 1;
  fi
  
  exit 0;