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https://github.com/csukuangfj/kaldifeat.git
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94a567c638
* Change the way how FrameExtractionOptions is displayed * small fixes * Change the way how MelBankOptions is displayed * Change the way how SpectrogramOptions is displayed * Change the way how FbankOptions is displayed * Change the way how MfccOptions is displayed * Change the way how PlpOptions is displayed * Export num_frames * release v1.22
92 lines
3.5 KiB
C++
92 lines
3.5 KiB
C++
// kaldifeat/python/csrc/feature-spectrogram.cc
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//
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// Copyright (c) 2021 Xiaomi Corporation (authors: Fangjun Kuang)
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#include "kaldifeat/python/csrc/feature-spectrogram.h"
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#include <memory>
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#include <string>
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#include "kaldifeat/csrc/feature-spectrogram.h"
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#include "kaldifeat/python/csrc/utils.h"
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namespace kaldifeat {
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static void PybindSpectrogramOptions(py::module &m) {
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using PyClass = SpectrogramOptions;
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py::class_<PyClass>(m, "SpectrogramOptions")
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.def(py::init([](const FrameExtractionOptions &frame_opts =
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FrameExtractionOptions(),
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float energy_floor = 0.0, bool raw_energy = true,
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bool return_raw_fft = false,
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py::object device = py::str(
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"cpu")) -> std::unique_ptr<SpectrogramOptions> {
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auto opts = std::make_unique<SpectrogramOptions>();
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opts->frame_opts = frame_opts;
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opts->energy_floor = energy_floor;
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opts->raw_energy = raw_energy;
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opts->return_raw_fft = return_raw_fft;
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std::string s = static_cast<py::str>(device);
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opts->device = torch::Device(s);
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return opts;
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}),
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py::arg("frame_opts") = FrameExtractionOptions(),
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py::arg("energy_floor") = 0.0, py::arg("raw_energy") = true,
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py::arg("return_raw_fft") = false,
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py::arg("device") = py::str("cpu"))
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.def_readwrite("frame_opts", &PyClass::frame_opts)
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.def_readwrite("energy_floor", &PyClass::energy_floor)
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.def_readwrite("raw_energy", &PyClass::raw_energy)
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// .def_readwrite("return_raw_fft", &PyClass::return_raw_fft) // not
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// implemented yet
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.def_property(
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"device",
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[](const PyClass &self) -> py::object {
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py::object ans = py::module_::import("torch").attr("device");
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return ans(self.device.str());
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},
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[](PyClass &self, py::object obj) -> void {
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std::string s = static_cast<py::str>(obj);
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self.device = torch::Device(s);
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})
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.def("__str__",
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[](const PyClass &self) -> std::string { return self.ToString(); })
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.def("as_dict",
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[](const PyClass &self) -> py::dict { return AsDict(self); })
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.def_static("from_dict",
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[](py::dict dict) -> PyClass {
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return SpectrogramOptionsFromDict(dict);
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})
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.def(py::pickle(
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[](const PyClass &self) -> py::dict { return AsDict(self); },
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[](py::dict dict) -> PyClass {
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return SpectrogramOptionsFromDict(dict);
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}));
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}
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static void PybindSpectrogram(py::module &m) {
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using PyClass = Spectrogram;
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py::class_<PyClass>(m, "Spectrogram")
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.def(py::init<const SpectrogramOptions &>(), py::arg("opts"))
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.def("dim", &PyClass::Dim)
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.def_property_readonly("options", &PyClass::GetOptions)
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.def("compute_features", &PyClass::ComputeFeatures, py::arg("wave"),
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py::arg("vtln_warp"), py::call_guard<py::gil_scoped_release>())
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.def(py::pickle(
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[](const PyClass &self) -> py::dict {
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return AsDict(self.GetOptions());
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},
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[](py::dict dict) -> std::unique_ptr<PyClass> {
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return std::make_unique<PyClass>(SpectrogramOptionsFromDict(dict));
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}));
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}
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void PybindFeatureSpectrogram(py::module &m) {
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PybindSpectrogramOptions(m);
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PybindSpectrogram(m);
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}
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} // namespace kaldifeat
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