Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix compilation issues when using KALDI_DOUBLEPRECISION=1 #470

Merged
merged 2 commits into from
Jan 28, 2016
Merged

Fix compilation issues when using KALDI_DOUBLEPRECISION=1 #470

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a422890
Fix compilation issues when using KALDI_DOUBLEPRECISION=1 caused by h…
funous Jan 26, 2016
f587473
remove redundant type hints
funous Jan 28, 2016
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
12 changes: 6 additions & 6 deletions src/feat/signal.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ void ElementwiseProductOfFft(const Vector<BaseFloat> &a, Vector<BaseFloat> *b) {
void ConvolveSignals(const Vector<BaseFloat> &filter, Vector<BaseFloat> *signal) {
int32 signal_length = signal->Dim();
int32 filter_length = filter.Dim();
Vector<float> signal_padded(signal_length + filter_length - 1);
Vector<BaseFloat> signal_padded(signal_length + filter_length - 1);
signal_padded.SetZero();
for (int32 i = 0; i < signal_length; i++) {
for (int32 j = 0; j < filter_length; j++) {
Expand All @@ -54,11 +54,11 @@ void FFTbasedConvolveSignals(const Vector<BaseFloat> &filter, Vector<BaseFloat>

SplitRadixRealFft<BaseFloat> srfft(fft_length);

Vector<float> filter_padded(fft_length);
Vector<BaseFloat> filter_padded(fft_length);
filter_padded.Range(0, filter_length).CopyFromVec(filter);
srfft.Compute(filter_padded.Data(), true);

Vector<float> signal_padded(fft_length);
Vector<BaseFloat> signal_padded(fft_length);
signal_padded.Range(0, signal_length).CopyFromVec(*signal);
srfft.Compute(signal_padded.Data(), true);

Expand All @@ -83,13 +83,13 @@ void FFTbasedBlockConvolveSignals(const Vector<BaseFloat> &filter, Vector<BaseFl
KALDI_VLOG(1) << "Block size is " << block_length;
SplitRadixRealFft<BaseFloat> srfft(fft_length);

Vector<float> filter_padded(fft_length);
Vector<BaseFloat> filter_padded(fft_length);
filter_padded.Range(0, filter_length).CopyFromVec(filter);
srfft.Compute(filter_padded.Data(), true);

Vector<float> temp_pad(filter_length - 1);
Vector<BaseFloat> temp_pad(filter_length - 1);
temp_pad.SetZero();
Vector<float> signal_block_padded(fft_length);
Vector<BaseFloat> signal_block_padded(fft_length);

for (int32 po = 0; po < signal_length; po += block_length) {
// get a block of the signal
Expand Down
8 changes: 4 additions & 4 deletions src/lm/kaldi-rnnlm.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -58,8 +58,8 @@ KaldiRnnlmWrapper::KaldiRnnlmWrapper(

BaseFloat KaldiRnnlmWrapper::GetLogProb(
int32 word, const std::vector<int32> &wseq,
const std::vector<BaseFloat> &context_in,
std::vector<BaseFloat> *context_out) {
const std::vector<float> &context_in,
std::vector<float> *context_out) {

std::vector<std::string> wseq_symbols(wseq.size());
for (int32 i = 0; i < wseq_symbols.size(); ++i) {
Expand All @@ -79,7 +79,7 @@ RnnlmDeterministicFst::RnnlmDeterministicFst(int32 max_ngram_order,

// Uses empty history for <s>.
std::vector<Label> bos;
std::vector<BaseFloat> bos_context(rnnlm->GetHiddenLayerSize(), 1.0f);
std::vector<float> bos_context(rnnlm->GetHiddenLayerSize(), 1.0);
state_to_wseq_.push_back(bos);
state_to_context_.push_back(bos_context);
wseq_to_state_[bos] = 0;
Expand All @@ -101,7 +101,7 @@ bool RnnlmDeterministicFst::GetArc(StateId s, Label ilabel, fst::StdArc *oarc) {
KALDI_ASSERT(static_cast<size_t>(s) < state_to_wseq_.size());

std::vector<Label> wseq = state_to_wseq_[s];
std::vector<BaseFloat> new_context(rnnlm_->GetHiddenLayerSize());
std::vector<float> new_context(rnnlm_->GetHiddenLayerSize());
BaseFloat logprob = rnnlm_->GetLogProb(ilabel, wseq,
state_to_context_[s], &new_context);

Expand Down
6 changes: 3 additions & 3 deletions src/lm/kaldi-rnnlm.h
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -56,8 +56,8 @@ class KaldiRnnlmWrapper {
int32 GetEos() const { return eos_; }

BaseFloat GetLogProb(int32 word, const std::vector<int32> &wseq,
const std::vector<BaseFloat> &context_in,
std::vector<BaseFloat> *context_out);
const std::vector<float> &context_in,
std::vector<float> *context_out);

private:
rnnlm::CRnnLM rnnlm_;
Expand Down Expand Up @@ -96,7 +96,7 @@ class RnnlmDeterministicFst

KaldiRnnlmWrapper *rnnlm_;
int32 max_ngram_order_;
std::vector<std::vector<BaseFloat> > state_to_context_;
std::vector<std::vector<float> > state_to_context_;
};

} // namespace kaldi
Expand Down
12 changes: 6 additions & 6 deletions src/nnet2/nnet-component.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -3933,8 +3933,8 @@ void Convolutional1dComponent::Propagate(const ChunkInfo &in_info,
}

// apply all filters
AddMatMatBatched(1.0f, tgt_batch, patch_batch, kNoTrans, filter_params_batch,
kTrans, 1.0f);
AddMatMatBatched<BaseFloat>(1.0, tgt_batch, patch_batch, kNoTrans, filter_params_batch,
kTrans, 1.0);

// release memory
delete filter_params_elem;
Expand Down Expand Up @@ -4060,8 +4060,8 @@ void Convolutional1dComponent::Backprop(const ChunkInfo &in_info,
p * num_filters, num_filters)));
filter_params_batch.push_back(filter_params_elem);
}
AddMatMatBatched(1.0f, patch_deriv_batch, out_deriv_batch, kNoTrans,
filter_params_batch, kNoTrans, 0.0f);
AddMatMatBatched<BaseFloat>(1.0, patch_deriv_batch, out_deriv_batch, kNoTrans,
filter_params_batch, kNoTrans, 0.0);

// release memory
delete filter_params_elem;
Expand Down Expand Up @@ -4275,8 +4275,8 @@ void Convolutional1dComponent::Update(const CuMatrixBase<BaseFloat> &in_value,
p * filter_dim, filter_dim)));
}

AddMatMatBatched(1.0f, filters_grad_batch, diff_patch_batch, kTrans, patch_batch,
kNoTrans, 1.0f);
AddMatMatBatched<BaseFloat>(1.0, filters_grad_batch, diff_patch_batch, kTrans, patch_batch,
kNoTrans, 1.0);

// add the row blocks together to filters_grad
filters_grad.AddMatBlocks(1.0, filters_grad_blocks_batch);
Expand Down
2 changes: 1 addition & 1 deletion src/nnet2/nnet-precondition-online-test.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -307,7 +307,7 @@ void UnitTestPreconditionDirectionsOnline() {
AssertEqual(trace1, trace2 * gamma2 * gamma2, 1.0e-02);

AssertEqual(Mcopy1, Mcopy2);
AssertEqual(row_prod1, row_prod2, 1.0e-02f);
AssertEqual<BaseFloat>(row_prod1, row_prod2, 1.0e-02);
AssertEqual(gamma1, gamma2, 1.0e-02);

// make sure positive definite
Expand Down
2 changes: 1 addition & 1 deletion src/nnet3/natural-gradient-online-test.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -307,7 +307,7 @@ void UnitTestPreconditionDirectionsOnline() {
AssertEqual(trace1, trace2 * gamma2 * gamma2, 1.0e-02);

AssertEqual(Mcopy1, Mcopy2);
AssertEqual(row_prod1, row_prod2, 1.0e-02f);
AssertEqual<BaseFloat>(row_prod1, row_prod2, 1.0e-02);
AssertEqual(gamma1, gamma2, 1.0e-02);

// make sure positive definite
Expand Down