#!/usr/bin/env bash

# fix segmentation fault reported in https://github.com/k2-fsa/icefall/issues/674
export PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python

set -eou pipefail

nj=60
stage=6
stop_stage=9

# We assume dl_dir (download dir) contains the following
# directories and files. If not, they will be downloaded
# by this script automatically.
#
#  - $dl_dir/hi-en

dl_dir=$PWD/download
espnet_path=/home/wtc7/espnet/egs2/MUCS/asr1/data/hi-en/

. shared/parse_options.sh || exit 1

# vocab size for sentence piece models.
# It will generate data/lang_bpe_xxx,
# data/lang_bpe_yyy
vocab_size=400

# All files generated by this script are saved in "data".
# You can safely remove "data" and rerun this script to regenerate it.
mkdir -p data

log() {
  # This function is from espnet
  local fname=${BASH_SOURCE[1]##*/}
  echo -e "$(date '+%Y-%m-%d %H:%M:%S') (${fname}:${BASH_LINENO[0]}:${FUNCNAME[1]}) $*"
}

log "dl_dir: $dl_dir"

if [ $stage -le -1 ] && [ $stop_stage -ge -1 ]; then
  log "Stage -1: prepare LM files"
  mkdir -p $dl_dir/lm
  if [ ! -e $dl_dir/lm/.done ]; then
    ./local/prepare_lm_files.py --out-dir=$dl_dir/lm --data-path=$espnet_path --mode="train"
    touch $dl_dir/lm/.done
  fi
fi

if [ $stage -le 0 ] && [ $stop_stage -ge 0 ]; then
  log "Stage 0: Download data"
fi

if [ $stage -le 1 ] && [ $stop_stage -ge 1 ]; then
  log "Stage 1: Prepare MUCS manifest"
  # We assume that you have downloaded the MUCS corpus
  # to $dl_dir/
  mkdir -p data/manifests
  if [ ! -e data/manifests/.mucs.done ]; then
    # generate lhotse manifests from kaldi style files
    ./local/prepare_manifest.py "$espnet_path" $nj data/manifests

    touch data/manifests/.mucs.done
  fi
fi

if [ $stage -le 3 ] && [ $stop_stage -ge 3 ]; then
  log "Stage 3: Compute fbank for mucs"
  mkdir -p data/fbank
  if [ ! -e data/fbank/.mucs.done ]; then
    ./local/compute_fbank_mucs.py
    touch data/fbank/.mucs.done
  fi

  # exit

  if [ ! -e data/fbank/.mucs-validated.done ]; then
    log "Validating data/fbank for mucs"
    parts=(
      train
      test
      dev
    )
    for part in ${parts[@]}; do
      python3 ./local/validate_manifest.py \
        data/fbank/mucs_cuts_${part}.jsonl.gz
    done
    touch data/fbank/.mucs-validated.done
  fi
fi



if [ $stage -le 5 ] && [ $stop_stage -ge 5 ]; then
  log "Stage 5: Prepare phone based lang"
  lang_dir=data/lang_phone
  mkdir -p $lang_dir

  (echo '!SIL SIL'; echo '<SPOKEN_NOISE> SPN'; echo '<UNK> SPN'; ) |
    cat - $dl_dir/lm/mucs_lexicon.txt |
    sort | uniq > $lang_dir/lexicon.txt

  if [ ! -f $lang_dir/L_disambig.pt ]; then
    ./local/prepare_lang.py --lang-dir $lang_dir
  fi

  if [ ! -f $lang_dir/L.fst ]; then
    log "Converting L.pt to L.fst"
    ./shared/convert-k2-to-openfst.py \
      --olabels aux_labels \
      $lang_dir/L.pt \
      $lang_dir/L.fst
  fi

  if [ ! -f $lang_dir/L_disambig.fst ]; then
    log "Converting L_disambig.pt to L_disambig.fst"
    ./shared/convert-k2-to-openfst.py \
      --olabels aux_labels \
      $lang_dir/L_disambig.pt \
      $lang_dir/disambig_L.fst
  fi
fi


if [ $stage -le 6 ] && [ $stop_stage -ge 6 ]; then
  log "Stage 6: Prepare BPE based lang"

    lang_dir=data/lang_bpe_${vocab_size}
    mkdir -p $lang_dir
    # We reuse words.txt from phone based lexicon
    # so that the two can share G.pt later.
    cp data/lang_phone/words.txt $lang_dir

    if [ ! -f $lang_dir/transcript_words.txt ]; then
      log "Generate data for BPE training"
      cp download/lm/mucs_vocab_text.txt $lang_dir/transcript_words.txt
    fi

    if [ ! -f $lang_dir/bpe.model ]; then
      ./local/train_bpe_model.py \
        --lang-dir $lang_dir \
        --vocab-size $vocab_size \
        --transcript $lang_dir/transcript_words.txt
    fi

    if [ ! -f $lang_dir/L_disambig.pt ]; then
      ./local/prepare_lang_bpe.py --lang-dir $lang_dir

      log "Validating $lang_dir/lexicon.txt"
      ./local/validate_bpe_lexicon.py \
        --lexicon $lang_dir/lexicon.txt \
        --bpe-model $lang_dir/bpe.model
    fi

    if [ ! -f $lang_dir/L.fst ]; then
      log "Converting L.pt to L.fst"
      ./shared/convert-k2-to-openfst.py \
        --olabels aux_labels \
        $lang_dir/L.pt \
        $lang_dir/L.fst
    fi

    if [ ! -f $lang_dir/L_disambig.fst ]; then
      log "Converting L_disambig.pt to L_disambig.fst"
      ./shared/convert-k2-to-openfst.py \
        --olabels aux_labels \
        $lang_dir/L_disambig.pt \
        $lang_dir/L_disambig.fst
    fi
  
fi

if [ $stage -le 7 ] && [ $stop_stage -ge 7 ]; then
  log "Stage 7: Train LM from training data"

    lang_dir=data/lang_bpe_${vocab_size}

    if [ ! -f $lang_dir/lm_3.arpa ]; then
      ./shared/make_kn_lm.py \
        -ngram-order 3 \
        -text $lang_dir/transcript_words.txt \
        -lm $lang_dir/lm_3.arpa
    fi

    if [ ! -f $lang_dir/lm_4.arpa ]; then
      ./shared/make_kn_lm.py \
        -ngram-order 4 \
        -text $lang_dir/transcript_words.txt \
        -lm $lang_dir/lm_4.arpa
    fi

fi

if [ $stage -le 8 ] && [ $stop_stage -ge 8 ]; then
  log "Stage 8: Prepare G"
  # We assume you have install kaldilm, if not, please install
  # it using: pip install kaldilm

  mkdir -p data/lm
  if [ ! -f data/lm/G_3_gram.fst.txt ]; then
    # It is used in building HLG
    python3 -m kaldilm \
      --read-symbol-table="data/lang_phone/words.txt" \
      --disambig-symbol='#0' \
      --max-order=3 \
      data/lang_bpe_${vocab_size}/lm_3.arpa > data/lm/G_3_gram.fst.txt
  fi

  if [ ! -f data/lm/G_4_gram.fst.txt ]; then
    # It is used in building HLG
    python3 -m kaldilm \
      --read-symbol-table="data/lang_phone/words.txt" \
      --disambig-symbol='#0' \
      --max-order=3 \
      data/lang_bpe_${vocab_size}/lm_4.arpa > data/lm/G_4_gram.fst.txt
  fi

fi

if [ $stage -le 9 ] && [ $stop_stage -ge 9 ]; then
  log "Stage 9: Compile HLG"
  # ./local/compile_hlg.py --lang-dir data/lang_phone

  # Note If ./local/compile_hlg.py throws OOM,
  # please switch to the following command
  #
  # ./local/compile_hlg_using_openfst.py --lang-dir data/lang_phone

    lang_dir=data/lang_bpe_${vocab_size}
    ./local/compile_hlg.py --lang-dir $lang_dir

fi