decodable-matrix.cc
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// decoder/decodable-matrix.cc
// Copyright 2018 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 "decoder/decodable-matrix.h"
namespace kaldi {
DecodableMatrixMapped::DecodableMatrixMapped(
const TransitionModel &tm,
const MatrixBase<BaseFloat> &likes,
int32 frame_offset):
trans_model_(tm), likes_(&likes), likes_to_delete_(NULL),
frame_offset_(frame_offset) {
stride_ = likes.Stride();
raw_data_ = likes.Data() - (stride_ * frame_offset);
if (likes.NumCols() != tm.NumPdfs())
KALDI_ERR << "Mismatch, matrix has "
<< likes.NumCols() << " rows but transition-model has "
<< tm.NumPdfs() << " pdf-ids.";
}
DecodableMatrixMapped::DecodableMatrixMapped(
const TransitionModel &tm, const Matrix<BaseFloat> *likes,
int32 frame_offset):
trans_model_(tm), likes_(likes), likes_to_delete_(likes),
frame_offset_(frame_offset) {
stride_ = likes->Stride();
raw_data_ = likes->Data() - (stride_ * frame_offset_);
if (likes->NumCols() != tm.NumPdfs())
KALDI_ERR << "Mismatch, matrix has "
<< likes->NumCols() << " rows but transition-model has "
<< tm.NumPdfs() << " pdf-ids.";
}
BaseFloat DecodableMatrixMapped::LogLikelihood(int32 frame, int32 tid) {
int32 pdf_id = trans_model_.TransitionIdToPdfFast(tid);
#ifdef KALDI_PARANOID
return (*likes_)(frame - frame_offset_, pdf_id);
#else
return raw_data_[frame * stride_ + pdf_id];
#endif
}
int32 DecodableMatrixMapped::NumFramesReady() const {
return frame_offset_ + likes_->NumRows();
}
bool DecodableMatrixMapped::IsLastFrame(int32 frame) const {
KALDI_ASSERT(frame < NumFramesReady());
return (frame == NumFramesReady() - 1);
}
// Indices are one-based! This is for compatibility with OpenFst.
int32 DecodableMatrixMapped::NumIndices() const {
return trans_model_.NumTransitionIds();
}
DecodableMatrixMapped::~DecodableMatrixMapped() {
delete likes_to_delete_;
}
void DecodableMatrixMappedOffset::AcceptLoglikes(
Matrix<BaseFloat> *loglikes, int32 frames_to_discard) {
if (loglikes->NumRows() == 0) return;
KALDI_ASSERT(loglikes->NumCols() == trans_model_.NumPdfs());
KALDI_ASSERT(frames_to_discard <= loglikes_.NumRows() &&
frames_to_discard >= 0);
if (frames_to_discard == loglikes_.NumRows()) {
loglikes_.Swap(loglikes);
loglikes->Resize(0, 0);
} else {
int32 old_rows_kept = loglikes_.NumRows() - frames_to_discard,
new_num_rows = old_rows_kept + loglikes->NumRows();
Matrix<BaseFloat> new_loglikes(new_num_rows, loglikes->NumCols());
new_loglikes.RowRange(0, old_rows_kept).CopyFromMat(
loglikes_.RowRange(frames_to_discard, old_rows_kept));
new_loglikes.RowRange(old_rows_kept, loglikes->NumRows()).CopyFromMat(
*loglikes);
loglikes_.Swap(&new_loglikes);
}
frame_offset_ += frames_to_discard;
stride_ = loglikes_.Stride();
raw_data_ = loglikes_.Data() - (frame_offset_ * stride_);
}
} // end namespace kaldi.