#!/bin/bash
  # Copyright 2017    Hossein Hadian
  
  set -e
  stage=0
  nj=20
  username=
  password=
  process_aachen_split=false
  overwrite=false
  # iam_database points to the database path on the JHU grid. If you have not
  # already downloaded the database you can set it to a local directory
  # like "data/download" and follow the instructions
  # in "local/prepare_data.sh" to download the database:
  iam_database=/export/corpora5/handwriting_ocr/IAM
  # wellington_database points to the database path on the JHU grid. The Wellington
  # corpus contains two directories WWC and WSC (Wellington Written and Spoken Corpus).
  # This corpus is of written NZ English that can be purchased here:
  # "https://www.victoria.ac.nz/lals/resources/corpora-default"
  wellington_database=/export/corpora5/Wellington/WWC/
  train_set=train_aug
  . ./cmd.sh ## You'll want to change cmd.sh to something that will work on your system.
             ## This relates to the queue.
  . ./path.sh
  . ./utils/parse_options.sh  # e.g. this parses the above options
                              # if supplied.
  ./local/check_tools.sh
  if [ $stage -le 0 ]; then
  
   if [ -f data/train/text ] && ! $overwrite; then
      echo "$0: Not processing, probably script have run from wrong stage"
      echo "Exiting with status 1 to avoid data corruption"
      exit 1;
    fi
  
    echo "$0: Preparing data..."
    local/prepare_data.sh --download-dir "$iam_database" \
      --wellington-dir "$wellington_database" \
      --username "$username" --password "$password" \
      --process_aachen_split $process_aachen_split
  fi
  mkdir -p data/{train,test,val}/data
  
  if [ $stage -le 1 ]; then
    echo "$0: $(date) stage 1: getting allowed image widths for e2e training..."
    image/get_image2num_frames.py --feat-dim 40 data/train # This will be needed for the next command
    # The next command creates a "allowed_lengths.txt" file in data/train
    # which will be used by local/make_features.py to enforce the images to
    # have allowed lengths. The allowed lengths will be spaced by 10% difference in length.
    image/get_allowed_lengths.py --frame-subsampling-factor 4 10 data/train
    echo "$0: $(date) Extracting features, creating feats.scp file"
    local/extract_features.sh --nj $nj --cmd "$cmd" --feat-dim 40 data/train
    steps/compute_cmvn_stats.sh data/train || exit 1;
    for set in val test; do
      local/extract_features.sh --nj $nj --cmd "$cmd" --augment true \
      --feat-dim 40 data/${set}
      steps/compute_cmvn_stats.sh data/${set} || exit 1;
    done
    utils/fix_data_dir.sh data/train
  fi
  
  if [ $stage -le 2 ]; then
    for set in train; do
      echo "$0: $(date) stage 2: Performing augmentation, it will double training data"
      local/augment_data.sh --nj $nj --cmd "$cmd" --feat-dim 40 data/${set} data/${set}_aug data
      steps/compute_cmvn_stats.sh data/${set}_aug || exit 1;
    done
  fi
  
  if [ $stage -le 3 ]; then
    echo "$0: Estimating a language model for decoding..."
    # We do this stage before dict preparation because prepare_dict.sh
    # generates the lexicon from pocolm's wordlist
    local/train_lm.sh --vocab-size 50k
  fi
  
  if [ $stage -le 4 ]; then
    echo "$0: Preparing dictionary and lang..."
    # This is for training. Use a large vocab size, e.g. 500k to include all the
    # training words:
    local/prepare_dict.sh --vocab-size 500k --dir data/local/dict
    utils/prepare_lang.sh --num-sil-states 4 --num-nonsil-states 8 --sil-prob 0.95 \
                          data/local/dict "<unk>" data/lang/temp data/lang
    silphonelist=`cat data/lang/phones/silence.csl`
    nonsilphonelist=`cat data/lang/phones/nonsilence.csl`
    local/gen_topo.py 8 4 4 $nonsilphonelist $silphonelist data/lang/phones.txt >data/lang/topo
  
    # This is for decoding. We use a 50k lexicon to be consistent with the papers
    # reporting WERs on IAM.
    local/prepare_dict.sh --vocab-size 50k --dir data/local/dict_50k
    utils/prepare_lang.sh --num-sil-states 4 --num-nonsil-states 8 --sil-prob 0.95 \
                          data/local/dict_50k "<unk>" data/lang_test/temp data/lang_test
    utils/format_lm.sh data/lang_test data/local/local_lm/data/arpa/3gram_big.arpa.gz \
                       data/local/dict_50k/lexicon.txt data/lang_test
  
    echo "$0: Preparing the unk model for open-vocab decoding..."
    utils/lang/make_unk_lm.sh --ngram-order 4 --num-extra-ngrams 7500 \
                              data/local/dict_50k exp/unk_lang_model
    utils/prepare_lang.sh --unk-fst exp/unk_lang_model/unk_fst.txt \
                          data/local/dict_50k "<unk>" data/lang_unk/temp data/lang_unk
  
    silphonelist=`cat data/lang/phones/silence.csl`
    nonsilphonelist=`cat data/lang/phones/nonsilence.csl`
    local/gen_topo.py 8 4 4 $nonsilphonelist $silphonelist data/lang_unk/phones.txt >data/lang_unk/topo
    cp data/lang_test/G.fst data/lang_unk/G.fst
  fi
  
  if [ $stage -le 5 ]; then
    echo "$0: Calling the flat-start chain recipe..."
    local/chain/run_e2e_cnn.sh --train_set $train_set
  fi
  
  if [ $stage -le 6 ]; then
    echo "$0: Aligning the training data using the e2e chain model..."
    steps/nnet3/align.sh --nj 50 --cmd "$cmd" \
                         --use-gpu false \
                         --scale-opts '--transition-scale=1.0 --self-loop-scale=1.0 --acoustic-scale=1.0' \
                         data/$train_set data/lang exp/chain/e2e_cnn_1a exp/chain/e2e_ali_train
  fi
  
  if [ $stage -le 7 ]; then
    echo "$0: Building a tree and training a regular chain model using the e2e alignments..."
    local/chain/run_cnn_e2eali.sh --train_set $train_set
  fi