Removed lstm/decode from all the run_lstm scripts in egs and the lstm/decode script itself.

egs/ami/s5/local/nnet3/run_lstm.sh

@@ -178,7 +178,7 @@ if [ $stage -le 11 ]; then
       else
         ivector_opts=
       fi
-      steps/nnet3/lstm/decode.sh --nj 250 --cmd "$decode_cmd" \
+      steps/nnet3/decode.sh --nj 250 --cmd "$decode_cmd" \
           $ivector_opts $model_opts \
           --extra-left-context $extra_left_context  \
 	        --extra-right-context $extra_right_context  \

egs/fisher_swbd/s5/local/nnet3/run_lstm.sh

@@ -142,7 +142,7 @@ if [ $stage -le 11 ]; then
   for decode_set in eval2000 rt03; do
       (
       num_jobs=`cat data/${decode_set}_hires/utt2spk|cut -d' ' -f2|sort -u|wc -l`
-      steps/nnet3/lstm/decode.sh --nj $num_jobs --cmd "$decode_cmd" \
+      steps/nnet3/decode.sh --nj $num_jobs --cmd "$decode_cmd" \
           --extra-left-context $extra_left_context  \
           --extra-right-context $extra_right_context  \
           --frames-per-chunk "$frames_per_chunk" \

egs/hkust/s5/local/nnet3/run_lstm.sh

@@ -155,7 +155,7 @@ if [ $stage -le 9 ]; then
         ivector_opts=
       fi
 
-      steps/nnet3/lstm/decode.sh --nj $num_jobs --cmd "$decode_cmd" $ivector_opts \
+      steps/nnet3/decode.sh --nj $num_jobs --cmd "$decode_cmd" $ivector_opts \
         --extra-left-context $extra_left_context \
         --frames-per-chunk "$frames_per_chunk" \
         $graph_dir data/${decode_set}_hires $decode_dir || exit 1;

egs/swbd/s5c/local/chain/run_lstm_d.sh

@@ -197,7 +197,7 @@ if [ $stage -le 15 ]; then
   fi
   for decode_set in train_dev eval2000; do
       (
-      steps/nnet3/lstm/decode.sh --acwt 1.0 --post-decode-acwt 10.0 \
+      steps/nnet3/decode.sh --acwt 1.0 --post-decode-acwt 10.0 \
           --nj 250 --cmd "$decode_cmd" $iter_opts \
           --extra-left-context $extra_left_context  \
           --extra-right-context $extra_right_context  \

egs/swbd/s5c/local/nnet3/run_blstm_discriminative.sh

@@ -177,7 +177,7 @@ if [ $stage -le 5 ]; then
       num_jobs=`cat data/${decode_set}_hires/utt2spk|cut -d' ' -f2|sort -u|wc -l`
       iter=epoch$x.adj
       
-      steps/nnet3/lstm/decode.sh --nj $num_jobs --cmd "$decode_cmd" --iter $iter \
+      steps/nnet3/decode.sh --nj $num_jobs --cmd "$decode_cmd" --iter $iter \
         --online-ivector-dir exp/nnet3/ivectors_${decode_set} $context_opts \
         $graph_dir data/${decode_set}_hires $dir/decode_${decode_set}_sw1_tg_$iter ;
       if $has_fisher; then

egs/swbd/s5c/local/nnet3/run_lstm.sh

@@ -153,7 +153,7 @@ if [ $stage -le 11 ]; then
   for decode_set in train_dev eval2000; do
       (
       num_jobs=`cat data/${decode_set}_hires/utt2spk|cut -d' ' -f2|sort -u|wc -l`
-      steps/nnet3/lstm/decode.sh --nj 250 --cmd "$decode_cmd" \
+      steps/nnet3/decode.sh --nj 250 --cmd "$decode_cmd" \
           --extra-left-context $extra_left_context  \
           --extra-right-context $extra_right_context  \
           --frames-per-chunk "$frames_per_chunk" \

egs/wsj/s5/steps/nnet3/lstm/decode.sh

-#!/bin/bash
-
-# Copyright 2012-2015  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
-min_active=200
-ivector_scale=1.0
-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=  # ignored now.
-scoring_opts=
-skip_scoring=false
-feat_type=
-online_ivector_dir=
-minimize=false
-
-frames_per_chunk=10000
-extra_left_context=20   # it is recommended to use the same value as the chunk_left_context
-                        # used during training
-extra_right_context=0   # it is recommended to use the same value as the chunk_right_context
-                        # used during training (usually used in bi-directional LSTM case)
-# 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: $0 [options] <graph-dir> <data-dir> <decode-dir>"
-  echo "e.g.:   steps/nnet3/decode.sh --nj 8 \\"
-  echo "--online-ivector-dir exp/nnet2_online/ivectors_test_eval92 \\"
-  echo "    exp/tri4b/graph_bg data/test_eval92_hires $dir/decode_bg_eval92"
-  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. '--num-threads 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/$iter.mdl
-
-
-[ ! -z "$online_ivector_dir" ] && \
-  extra_files="$online_ivector_dir/ivector_online.scp $online_ivector_dir/ivector_period"
-
-for f in $graphdir/HCLG.fst $data/feats.scp $model $extra_files; do
-  [ ! -f $f ] && echo "$0: no such file $f" && exit 1;
-done
-
-sdata=$data/split${nj}utt;
-cmvn_opts=`cat $srcdir/cmvn_opts` || exit 1;
-thread_string=
-[ $num_threads -gt 1 ] && thread_string="-parallel --num-threads=$num_threads"
-
-mkdir -p $dir/log
-split_data.sh --per-utt $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=raw; fi
-  echo "$0: feature type is $feat_type"
-fi
-
-splice_opts=`cat $srcdir/splice_opts 2>/dev/null`
-
-case $feat_type in
-  raw) feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$sdata/JOB/utt2spk scp:$sdata/JOB/cmvn.scp scp:$sdata/JOB/feats.scp ark:- |";;
-  lda) feats="ark,s,cs:apply-cmvn $cmvn_opts --utt2spk=ark:$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"
-  [ ! -s $transform_dir/num_jobs ] && \
-    echo "$0: expected $transform_dir/num_jobs to contain the number of jobs." && exit 1;
-  nj_orig=$(cat $transform_dir/num_jobs)
-
-  if [ $feat_type == "raw" ]; then trans=raw_trans;
-  else trans=trans; fi
-  if [ $feat_type == "lda" ] && \
-    ! cmp $transform_dir/../final.mat $srcdir/final.mat && \
-    ! cmp $transform_dir/final.mat $srcdir/final.mat; then
-    echo "$0: LDA transforms differ between $srcdir and $transform_dir"
-    exit 1;
-  fi
-  if [ ! -f $transform_dir/$trans.1 ]; then
-    echo "$0: expected $transform_dir/$trans.1 to exist (--transform-dir option)"
-    exit 1;
-  fi
-  if [ $nj -ne $nj_orig ]; then
-    # Copy the transforms into an archive with an index.
-    for n in $(seq $nj_orig); do cat $transform_dir/$trans.$n; done | \
-       copy-feats ark:- ark,scp:$dir/$trans.ark,$dir/$trans.scp || exit 1;
-    feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk scp:$dir/$trans.scp ark:- ark:- |"
-  else
-    # number of jobs matches with alignment dir.
-    feats="$feats transform-feats --utt2spk=ark:$sdata/JOB/utt2spk ark:$transform_dir/$trans.JOB ark:- ark:- |"
-  fi
-elif grep 'transform-feats --utt2spk' $srcdir/log/train.1.log >&/dev/null; then
-  echo "$0: **WARNING**: you seem to be using a neural net system trained with transforms,"
-  echo "  but you are not providing the --transform-dir option in test time."
-fi
-##
-
-if [ ! -z "$online_ivector_dir" ]; then
-  ivector_period=$(cat $online_ivector_dir/ivector_period) || exit 1;
-  ivector_opts="--online-ivectors=scp:$online_ivector_dir/ivector_online.scp --online-ivector_period=$ivector_period"
-fi
-
-if [ $stage -le 1 ]; then
-  $cmd --num-threads $num_threads JOB=1:$nj $dir/log/decode.JOB.log \
-    nnet3-latgen-faster$thread_string $ivector_opts \
-     --frames-per-chunk=$frames_per_chunk \
-     --minimize=$minimize --max-active=$max_active --min-active=$min_active --beam=$beam \
-     --lattice-beam=$lattice_beam --acoustic-scale=$acwt --allow-partial=true \
-     --extra-left-context=$extra_left_context \
-     --extra-right-context=$extra_right_context \
-     --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;