// bin/decode-faster-mapped.cc

// Copyright 2009-2011  Microsoft Corporation
//                2013  Johns Hopkins University (author: Daniel Povey)

// 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 "tree/context-dep.h"
#include "hmm/transition-model.h"
#include "fstext/fstext-lib.h"
#include "decoder/faster-decoder.h"
#include "decoder/decodable-matrix.h"
#include "base/timer.h"
#include "lat/kaldi-lattice.h" // for {Compact}LatticeArc

int main(int argc, char *argv[]) {
  try {
    using namespace kaldi;
    typedef kaldi::int32 int32;
    using fst::SymbolTable;
    using fst::VectorFst;
    using fst::StdArc;

    const char *usage =
        "Decode, reading log-likelihoods as matrices\n"
        " (model is needed only for the integer mappings in its transition-model)\n"
        "Usage:   decode-faster-mapped [options] <model-in> <fst-in> "
        "<loglikes-rspecifier> <words-wspecifier> [<alignments-wspecifier>]\n";
    ParseOptions po(usage);
    bool binary = true;
    BaseFloat acoustic_scale = 0.1;
    bool allow_partial = true;
    std::string word_syms_filename;
    FasterDecoderOptions decoder_opts;
    decoder_opts.Register(&po, true);  // true == include obscure settings.
    po.Register("binary", &binary, "Write output in binary mode");
    po.Register("acoustic-scale", &acoustic_scale, "Scaling factor for acoustic likelihoods");
    po.Register("allow-partial", &allow_partial, "Produce output even when final state was not reached");
    po.Register("word-symbol-table", &word_syms_filename, "Symbol table for words [for debug output]");

    po.Read(argc, argv);

    if (po.NumArgs() < 4 || po.NumArgs() > 5) {
      po.PrintUsage();
      exit(1);
    }

    std::string model_in_filename = po.GetArg(1),
        fst_in_filename = po.GetArg(2),
        loglikes_rspecifier = po.GetArg(3),
        words_wspecifier = po.GetArg(4),
        alignment_wspecifier = po.GetOptArg(5);

    TransitionModel trans_model;
    ReadKaldiObject(model_in_filename, &trans_model);

    Int32VectorWriter words_writer(words_wspecifier);

    Int32VectorWriter alignment_writer(alignment_wspecifier);

    fst::SymbolTable *word_syms = NULL;
    if (word_syms_filename != "") {
      word_syms = fst::SymbolTable::ReadText(word_syms_filename);
      if (!word_syms)
        KALDI_ERR << "Could not read symbol table from file "<<word_syms_filename;
    }

    SequentialBaseFloatMatrixReader loglikes_reader(loglikes_rspecifier);

    // It's important that we initialize decode_fst after loglikes_reader, as it
    // can prevent crashes on systems installed without enough virtual memory.
    // It has to do with what happens on UNIX systems if you call fork() on a
    // large process: the page-table entries are duplicated, which requires a
    // lot of virtual memory.
    VectorFst<StdArc> *decode_fst = fst::ReadFstKaldi(fst_in_filename);

    BaseFloat tot_like = 0.0;
    kaldi::int64 frame_count = 0;
    int num_success = 0, num_fail = 0;
    FasterDecoder decoder(*decode_fst, decoder_opts);

    Timer timer;

    for (; !loglikes_reader.Done(); loglikes_reader.Next()) {
      std::string key = loglikes_reader.Key();
      const Matrix<BaseFloat> &loglikes (loglikes_reader.Value());

      if (loglikes.NumRows() == 0) {
        KALDI_WARN << "Zero-length utterance: " << key;
        num_fail++;
        continue;
      }

      DecodableMatrixScaledMapped decodable(trans_model, loglikes, acoustic_scale);
      decoder.Decode(&decodable);

      VectorFst<LatticeArc> decoded;  // linear FST.

      if ( (allow_partial || decoder.ReachedFinal())
           && decoder.GetBestPath(&decoded) ) {
        num_success++;
        if (!decoder.ReachedFinal())
          KALDI_WARN << "Decoder did not reach end-state, outputting partial traceback.";

        std::vector<int32> alignment;
        std::vector<int32> words;
        LatticeWeight weight;
        frame_count += loglikes.NumRows();

        GetLinearSymbolSequence(decoded, &alignment, &words, &weight);

        words_writer.Write(key, words);
        if (alignment_writer.IsOpen())
          alignment_writer.Write(key, alignment);
        if (word_syms != NULL) {
          std::cerr << key << ' ';
          for (size_t i = 0; i < words.size(); i++) {
            std::string s = word_syms->Find(words[i]);
            if (s == "")
              KALDI_ERR << "Word-id " << words[i] <<" not in symbol table.";
            std::cerr << s << ' ';
          }
          std::cerr << '\n';
        }
        BaseFloat like = -weight.Value1() -weight.Value2();
        tot_like += like;
        KALDI_LOG << "Log-like per frame for utterance " << key << " is "
                  << (like / loglikes.NumRows()) << " over "
                  << loglikes.NumRows() << " frames.";

      } else {
        num_fail++;
        KALDI_WARN << "Did not successfully decode utterance " << key
                   << ", len = " << loglikes.NumRows();
      }
    }

    double elapsed = timer.Elapsed();
    KALDI_LOG << "Time taken [excluding initialization] "<< elapsed
              << "s: real-time factor assuming 100 frames/sec is "
              << (elapsed*100.0/frame_count);
    KALDI_LOG << "Done " << num_success << " utterances, failed for "
              << num_fail;
    KALDI_LOG << "Overall log-likelihood per frame is " << (tot_like/frame_count)
              << " over " << frame_count << " frames.";

    delete word_syms;
    delete decode_fst;
    if (num_success != 0) return 0;
    else return 1;
  } catch(const std::exception &e) {
    std::cerr << e.what();
    return -1;
  }
}