// gmmbin/gmm-latgen-faster.cc
  
  // Copyright 2009-2012  Microsoft Corporation
  //           2013-2014  Johns Hopkins University (author: Daniel Povey)
  //                2014  Guoguo Chen
  
  // See ../../COPYING for clarification regarding multiple authors
  //
  // Licensed under the Apache License, Version 2.0 (the "License");
  // you may not use this file except in compliance with the License.
  // You may obtain a copy of the License at
  //
  //  http://www.apache.org/licenses/LICENSE-2.0
  //
  // THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
  // KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
  // WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
  // MERCHANTABLITY OR NON-INFRINGEMENT.
  // See the Apache 2 License for the specific language governing permissions and
  // limitations under the License.
  
  
  #include "base/kaldi-common.h"
  #include "util/common-utils.h"
  #include "gmm/am-diag-gmm.h"
  #include "tree/context-dep.h"
  #include "hmm/transition-model.h"
  #include "fstext/fstext-lib.h"
  #include "decoder/decoder-wrappers.h"
  #include "gmm/decodable-am-diag-gmm.h"
  #include "base/timer.h"
  #include "feat/feature-functions.h"  // feature reversal
  
  int main(int argc, char *argv[]) {
    try {
      using namespace kaldi;
      typedef kaldi::int32 int32;
      using fst::SymbolTable;
      using fst::Fst;
      using fst::StdArc;
  
      const char *usage =
          "Generate lattices using GMM-based model.
  "
          "Usage: gmm-latgen-faster [options] model-in (fst-in|fsts-rspecifier) features-rspecifier"
          " lattice-wspecifier [ words-wspecifier [alignments-wspecifier] ]
  ";
      ParseOptions po(usage);
      Timer timer;
      bool allow_partial = false;
      BaseFloat acoustic_scale = 0.1;
      LatticeFasterDecoderConfig config;
  
      std::string word_syms_filename;
      config.Register(&po);
      po.Register("acoustic-scale", &acoustic_scale,
                  "Scaling factor for acoustic likelihoods");
      po.Register("word-symbol-table", &word_syms_filename,
                  "Symbol table for words [for debug output]");
      po.Register("allow-partial", &allow_partial,
                  "If true, produce output even if end state was not reached.");
  
      po.Read(argc, argv);
  
      if (po.NumArgs() < 4 || po.NumArgs() > 6) {
        po.PrintUsage();
        exit(1);
      }
  
      std::string model_in_filename = po.GetArg(1),
          fst_in_str = po.GetArg(2),
          feature_rspecifier = po.GetArg(3),
          lattice_wspecifier = po.GetArg(4),
          words_wspecifier = po.GetOptArg(5),
          alignment_wspecifier = po.GetOptArg(6);
  
      TransitionModel trans_model;
      AmDiagGmm am_gmm;
      {
        bool binary;
        Input ki(model_in_filename, &binary);
        trans_model.Read(ki.Stream(), binary);
        am_gmm.Read(ki.Stream(), binary);
      }
  
      bool determinize = config.determinize_lattice;
      CompactLatticeWriter compact_lattice_writer;
      LatticeWriter lattice_writer;
      if (! (determinize ? compact_lattice_writer.Open(lattice_wspecifier)
             : lattice_writer.Open(lattice_wspecifier)))
        KALDI_ERR << "Could not open table for writing lattices: "
                   << lattice_wspecifier;
  
      Int32VectorWriter words_writer(words_wspecifier);
  
      Int32VectorWriter alignment_writer(alignment_wspecifier);
  
      fst::SymbolTable *word_syms = NULL;
      if (word_syms_filename != "")
        if (!(word_syms = fst::SymbolTable::ReadText(word_syms_filename)))
          KALDI_ERR << "Could not read symbol table from file "
                     << word_syms_filename;
  
      double tot_like = 0.0;
      kaldi::int64 frame_count = 0;
      int num_done = 0, num_err = 0;
  
      if (ClassifyRspecifier(fst_in_str, NULL, NULL) == kNoRspecifier) {
        SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
        // Input FST is just one FST, not a table of FSTs.
        Fst<StdArc> *decode_fst = fst::ReadFstKaldiGeneric(fst_in_str);
        timer.Reset();
  
        {
          LatticeFasterDecoder decoder(*decode_fst, config);
  
          for (; !feature_reader.Done(); feature_reader.Next()) {
            std::string utt = feature_reader.Key();
            Matrix<BaseFloat> features (feature_reader.Value());
            feature_reader.FreeCurrent();
            if (features.NumRows() == 0) {
              KALDI_WARN << "Zero-length utterance: " << utt;
              num_err++;
              continue;
            }
  
            DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features,
                                                   acoustic_scale);
  
            double like;
            if (DecodeUtteranceLatticeFaster(
                    decoder, gmm_decodable, trans_model, word_syms, utt,
                    acoustic_scale, determinize, allow_partial, &alignment_writer,
                    &words_writer, &compact_lattice_writer, &lattice_writer,
                    &like)) {
              tot_like += like;
              frame_count += features.NumRows();
              num_done++;
            } else num_err++;
          }
        }
        delete decode_fst; // delete this only after decoder goes out of scope.
      } else { // We have different FSTs for different utterances.
        SequentialTableReader<fst::VectorFstHolder> fst_reader(fst_in_str);
        RandomAccessBaseFloatMatrixReader feature_reader(feature_rspecifier);
        for (; !fst_reader.Done(); fst_reader.Next()) {
          std::string utt = fst_reader.Key();
          if (!feature_reader.HasKey(utt)) {
            KALDI_WARN << "Not decoding utterance " << utt
                       << " because no features available.";
            num_err++;
            continue;
          }
          const Matrix<BaseFloat> &features = feature_reader.Value(utt);
          if (features.NumRows() == 0) {
            KALDI_WARN << "Zero-length utterance: " << utt;
            num_err++;
            continue;
          }
  
          LatticeFasterDecoder decoder(fst_reader.Value(), config);
          DecodableAmDiagGmmScaled gmm_decodable(am_gmm, trans_model, features,
                                                 acoustic_scale);
          double like;
          if (DecodeUtteranceLatticeFaster(
                  decoder, gmm_decodable, trans_model, word_syms, utt,
                  acoustic_scale, determinize, allow_partial, &alignment_writer,
                  &words_writer, &compact_lattice_writer, &lattice_writer,
                  &like)) {
            tot_like += like;
            frame_count += features.NumRows();
            num_done++;
          } else num_err++;
        }
      }
  
      double elapsed = timer.Elapsed();
      KALDI_LOG << "Time taken "<< elapsed
                << "s: real-time factor assuming 100 frames/sec is "
                << (elapsed*100.0/frame_count);
      KALDI_LOG << "Done " << num_done << " utterances, failed for "
                << num_err;
      KALDI_LOG << "Overall log-likelihood per frame is " << (tot_like/frame_count) << " over "
                << frame_count << " frames.";
  
      delete word_syms;
      if (num_done != 0) return 0;
      else return 1;
    } catch(const std::exception &e) {
      std::cerr << e.what();
      return -1;
    }
  }