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src/nnet/nnet-pdf-prior.h 2.29 KB
8dcb6dfcb   Yannick Estève   first commit
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  // nnet/nnet-pdf-prior.h
  
  // Copyright 2013  Brno University of Technology (Author: Karel Vesely)
  
  // 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.
  
  #ifndef KALDI_NNET_NNET_PDF_PRIOR_H_
  #define KALDI_NNET_NNET_PDF_PRIOR_H_
  
  #include <cfloat>
  #include <string>
  
  #include "base/kaldi-common.h"
  #include "util/common-utils.h"
  #include "matrix/matrix-lib.h"
  #include "cudamatrix/cu-matrix.h"
  #include "cudamatrix/cu-vector.h"
  
  namespace kaldi {
  namespace nnet1 {
  
  struct PdfPriorOptions {
    std::string class_frame_counts;
    BaseFloat prior_scale;
    BaseFloat prior_floor;
  
    PdfPriorOptions():
      class_frame_counts(""),
      prior_scale(1.0),
      prior_floor(1e-10)
    { }
  
    void Register(OptionsItf *opts) {
      opts->Register("class-frame-counts", &class_frame_counts,
                     "Vector with frame-counts of pdfs to compute log-priors."
                     " (priors are typically subtracted from log-posteriors"
                     " or pre-softmax activations)");
      opts->Register("prior-scale", &prior_scale,
                     "Scaling factor to be applied on pdf-log-priors");
      opts->Register("prior-floor", &prior_floor,
                     "Flooring constatnt for prior probability "
                     "(i.e. label rel. frequency)");
    }
  };
  
  class PdfPrior {
   public:
    /// Initialize pdf-prior from options
    explicit PdfPrior(const PdfPriorOptions &opts);
  
    /// Subtract pdf priors from log-posteriors to get pseudo log-likelihoods
    void SubtractOnLogpost(CuMatrixBase<BaseFloat> *llk);
  
   private:
    BaseFloat prior_scale_;
    CuVector<BaseFloat> log_priors_;
  
    KALDI_DISALLOW_COPY_AND_ASSIGN(PdfPrior);
  };
  
  }  // namespace nnet1
  }  // namespace kaldi
  
  #endif  // KALDI_NNET_NNET_PDF_PRIOR_H_