// sgmm2bin/sgmm2-acc-stats-gpost.cc
  
  // Copyright 2009-2012   Saarland University  Microsoft Corporation
  //                       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 "sgmm2/am-sgmm2.h"
  #include "hmm/transition-model.h"
  #include "sgmm2/estimate-am-sgmm2.h"
  
  
  int main(int argc, char *argv[]) {
    using namespace kaldi;
    try {
      const char *usage =
          "Accumulate stats for SGMM training, given Gaussian-level posteriors
  "
          "Usage: sgmm2-acc-stats-gpost [options] <model-in> <feature-rspecifier> "
          "<gpost-rspecifier> <stats-out>
  "
          "e.g.: sgmm2-acc-stats-gpost 1.mdl 1.ali scp:train.scp ark, s, cs:- 1.acc
  ";
  
      ParseOptions po(usage);
      bool binary = true;
      std::string spkvecs_rspecifier, utt2spk_rspecifier;
      std::string update_flags_str = "vMNwcSt";
      BaseFloat rand_prune = 1.0e-05;
  
      po.Register("binary", &binary, "Write output in binary mode");
      po.Register("spk-vecs", &spkvecs_rspecifier, "Speaker vectors (rspecifier)");
      po.Register("utt2spk", &utt2spk_rspecifier,
                  "rspecifier for utterance to speaker map");
      po.Register("rand-prune", &rand_prune, "Pruning threshold for posteriors");
      po.Register("update-flags", &update_flags_str, "Which SGMM parameters to update: subset of vMNwcS.");
      po.Read(argc, argv);
  
      kaldi::SgmmUpdateFlagsType acc_flags = StringToSgmmUpdateFlags(update_flags_str);
  
      if (po.NumArgs() != 4) {
        po.PrintUsage();
        exit(1);
      }
  
      std::string model_filename = po.GetArg(1),
          feature_rspecifier = po.GetArg(2),
          gpost_rspecifier = po.GetArg(3),
          accs_wxfilename = po.GetArg(4);
  
      using namespace kaldi;
      typedef kaldi::int32 int32;
  
      // Initialize the readers before the model, as this can avoid
      // crashes on systems with low virtual memory.
      SequentialBaseFloatMatrixReader feature_reader(feature_rspecifier);
      RandomAccessSgmm2GauPostReader gpost_reader(gpost_rspecifier);
      RandomAccessBaseFloatVectorReaderMapped spkvecs_reader(spkvecs_rspecifier,
                                                             utt2spk_rspecifier);
      RandomAccessTokenReader utt2spk_map(utt2spk_rspecifier);
      
      AmSgmm2 am_sgmm;
      TransitionModel trans_model;
      {
        bool binary;
        Input ki(model_filename, &binary);
        trans_model.Read(ki.Stream(), binary);
        am_sgmm.Read(ki.Stream(), binary);
      }
  
      Vector<double> transition_accs;
      trans_model.InitStats(&transition_accs);
      MleAmSgmm2Accs sgmm_accs(rand_prune);
      sgmm_accs.ResizeAccumulators(am_sgmm, acc_flags, (spkvecs_rspecifier != ""));
  
      double tot_t = 0.0;
      kaldi::Sgmm2PerFrameDerivedVars per_frame_vars;
      
      int32 num_done = 0, num_err = 0;
      std::string cur_spk;
      Sgmm2PerSpkDerivedVars spk_vars;
      
      for (; !feature_reader.Done(); feature_reader.Next()) {
        std::string utt = feature_reader.Key();
        std::string spk = utt;
  
        if (!utt2spk_rspecifier.empty()) {
          if (!utt2spk_map.HasKey(utt)) {
            KALDI_WARN << "utt2spk map does not have value for " << utt
                       << ", ignoring this utterance.";
            continue;
          } else { spk = utt2spk_map.Value(utt); }
        }
  
        if (spk != cur_spk && cur_spk != "")
          sgmm_accs.CommitStatsForSpk(am_sgmm, spk_vars);
        
        if (spk != cur_spk || spk_vars.Empty()) {
          spk_vars.Clear();
          if (spkvecs_reader.IsOpen()) {
            if (spkvecs_reader.HasKey(utt)) {
              spk_vars.SetSpeakerVector(spkvecs_reader.Value(utt));
              am_sgmm.ComputePerSpkDerivedVars(&spk_vars);
            } else {
              KALDI_WARN << "Cannot find speaker vector for " << utt;
              num_err++;
              continue;
            }
          } // else spk_vars is "empty"
        }
  
        cur_spk = spk;      
        
        const Matrix<BaseFloat> &mat = feature_reader.Value();
        if (!gpost_reader.HasKey(utt) ||
            gpost_reader.Value(utt).size() != mat.NumRows()) {
          KALDI_WARN << "No Gaussian-posterior information for utterance "
                     << utt << " (or wrong size).";
          num_err++;
          continue;
        }
        const Sgmm2GauPost &gpost = gpost_reader.Value(utt);
        
        num_done++;
        BaseFloat tot_weight = 0.0;
  
        for (size_t i = 0; i < gpost.size(); i++) {
          const std::vector<int32> &gselect = gpost[i].gselect;
          am_sgmm.ComputePerFrameVars(mat.Row(i), gselect, spk_vars,
                                      &per_frame_vars);
  
          for (size_t j = 0; j < gpost[i].tids.size(); j++) {
            int32 tid = gpost[i].tids[j],  // transition identifier.
                pdf_id = trans_model.TransitionIdToPdf(tid);
            
            BaseFloat weight = gpost[i].posteriors[j].Sum();
            trans_model.Accumulate(weight, tid, &transition_accs);
            sgmm_accs.AccumulateFromPosteriors(am_sgmm, per_frame_vars,
                                               gpost[i].posteriors[j],
                                               pdf_id, &spk_vars);
            tot_weight += weight;
          }
        }
  
        tot_t += tot_weight;
        if (num_done % 50 == 0)
          KALDI_LOG << "Processed " << num_done << " utterances";      
      }
      sgmm_accs.CommitStatsForSpk(am_sgmm, spk_vars); // for last speaker
      
      KALDI_LOG << "Overall number of frames is " << tot_t;
      KALDI_LOG << "Done " << num_done << " files, "
                << num_err << " with errors.";
  
      {
        Output ko(accs_wxfilename, binary);
        transition_accs.Write(ko.Stream(), binary);
        sgmm_accs.Write(ko.Stream(), binary);
      }
      KALDI_LOG << "Written accs.";
      return (num_done != 0 ? 0 : 1);
    } catch(const std::exception &e) {
      std::cerr << e.what();
      return -1;
    }
  }