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PaddleSpeech/audio/paddleaudio/third_party/kaldi-native-fbank/csrc/rfft.cc

67 lines
1.7 KiB

/**
* Copyright (c) 2022 Xiaomi Corporation (authors: Fangjun Kuang)
*
* See LICENSE 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
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
#include "kaldi-native-fbank/csrc/rfft.h"
#include <cmath>
#include <vector>
#include "kaldi-native-fbank/csrc/log.h"
// see fftsg.c
#ifdef __cplusplus
extern "C" void rdft(int n, int isgn, double *a, int *ip, double *w);
#else
void rdft(int n, int isgn, double *a, int *ip, double *w);
#endif
namespace knf {
class Rfft::RfftImpl {
public:
explicit RfftImpl(int32_t n) : n_(n), ip_(2 + std::sqrt(n / 2)), w_(n / 2) {
KNF_CHECK_EQ(n & (n - 1), 0);
}
void Compute(float *in_out) {
std::vector<double> d(in_out, in_out + n_);
Compute(d.data());
std::copy(d.begin(), d.end(), in_out);
}
void Compute(double *in_out) {
// 1 means forward fft
rdft(n_, 1, in_out, ip_.data(), w_.data());
}
private:
int32_t n_;
std::vector<int32_t> ip_;
std::vector<double> w_;
};
Rfft::Rfft(int32_t n) : impl_(std::make_unique<RfftImpl>(n)) {}
Rfft::~Rfft() = default;
void Rfft::Compute(float *in_out) { impl_->Compute(in_out); }
void Rfft::Compute(double *in_out) { impl_->Compute(in_out); }
} // namespace knf