38c072dcb2
* add export of per-token scores (ys, lm, context) - for best path of the modified-beam-search decoding of transducer * refactoring JSON export of OnlineRecognitionResult, extending pybind11 API of OnlineRecognitionResult * export per-token scores also for greedy-search (online-transducer) - export un-scaled lm_probs (modified-beam search, online-transducer) - polishing * fill lm_probs/context_scores only if LM/ContextGraph is present (make Result smaller)
114 lines
4.6 KiB
C++
114 lines
4.6 KiB
C++
// sherpa-onnx/python/csrc/online-recongizer.cc
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//
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// Copyright (c) 2023 Xiaomi Corporation
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#include "sherpa-onnx/python/csrc/online-recognizer.h"
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#include <string>
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#include <vector>
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#include "sherpa-onnx/csrc/online-recognizer.h"
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namespace sherpa_onnx {
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static void PybindOnlineRecognizerResult(py::module *m) {
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using PyClass = OnlineRecognizerResult;
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py::class_<PyClass>(*m, "OnlineRecognizerResult")
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.def_property_readonly(
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"text",
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[](PyClass &self) -> py::str {
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return py::str(PyUnicode_DecodeUTF8(self.text.c_str(),
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self.text.size(), "ignore"));
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})
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.def_property_readonly(
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"tokens",
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[](PyClass &self) -> std::vector<std::string> { return self.tokens; })
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.def_property_readonly(
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"start_time",
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[](PyClass &self) -> float { return self.start_time; })
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.def_property_readonly(
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"timestamps",
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[](PyClass &self) -> std::vector<float> { return self.timestamps; })
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.def_property_readonly(
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"ys_probs",
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[](PyClass &self) -> std::vector<float> { return self.ys_probs; })
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.def_property_readonly(
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"lm_probs",
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[](PyClass &self) -> std::vector<float> { return self.lm_probs; })
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.def_property_readonly(
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"context_scores",
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[](PyClass &self) -> std::vector<float> {
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return self.context_scores;
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})
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.def_property_readonly(
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"segment",
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[](PyClass &self) -> int32_t { return self.segment; })
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.def_property_readonly(
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"is_final",
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[](PyClass &self) -> bool { return self.is_final; })
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.def("as_json_string", &PyClass::AsJsonString,
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py::call_guard<py::gil_scoped_release>());
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}
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static void PybindOnlineRecognizerConfig(py::module *m) {
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using PyClass = OnlineRecognizerConfig;
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py::class_<PyClass>(*m, "OnlineRecognizerConfig")
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.def(py::init<const FeatureExtractorConfig &, const OnlineModelConfig &,
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const OnlineLMConfig &, const EndpointConfig &, bool,
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const std::string &, int32_t, const std::string &, float,
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float>(),
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py::arg("feat_config"), py::arg("model_config"),
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py::arg("lm_config") = OnlineLMConfig(), py::arg("endpoint_config"),
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py::arg("enable_endpoint"), py::arg("decoding_method"),
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py::arg("max_active_paths") = 4, py::arg("hotwords_file") = "",
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py::arg("hotwords_score") = 0, py::arg("blank_penalty") = 0.0)
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.def_readwrite("feat_config", &PyClass::feat_config)
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.def_readwrite("model_config", &PyClass::model_config)
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.def_readwrite("lm_config", &PyClass::lm_config)
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.def_readwrite("endpoint_config", &PyClass::endpoint_config)
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.def_readwrite("enable_endpoint", &PyClass::enable_endpoint)
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.def_readwrite("decoding_method", &PyClass::decoding_method)
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.def_readwrite("max_active_paths", &PyClass::max_active_paths)
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.def_readwrite("hotwords_file", &PyClass::hotwords_file)
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.def_readwrite("hotwords_score", &PyClass::hotwords_score)
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.def_readwrite("blank_penalty", &PyClass::blank_penalty)
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.def("__str__", &PyClass::ToString);
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}
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void PybindOnlineRecognizer(py::module *m) {
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PybindOnlineRecognizerResult(m);
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PybindOnlineRecognizerConfig(m);
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using PyClass = OnlineRecognizer;
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py::class_<PyClass>(*m, "OnlineRecognizer")
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.def(py::init<const OnlineRecognizerConfig &>(), py::arg("config"),
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py::call_guard<py::gil_scoped_release>())
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.def(
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"create_stream",
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[](const PyClass &self) { return self.CreateStream(); },
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py::call_guard<py::gil_scoped_release>())
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.def(
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"create_stream",
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[](PyClass &self, const std::string &hotwords) {
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return self.CreateStream(hotwords);
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},
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py::arg("hotwords"), py::call_guard<py::gil_scoped_release>())
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.def("is_ready", &PyClass::IsReady,
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py::call_guard<py::gil_scoped_release>())
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.def("decode_stream", &PyClass::DecodeStream,
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py::call_guard<py::gil_scoped_release>())
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.def(
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"decode_streams",
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[](PyClass &self, std::vector<OnlineStream *> ss) {
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self.DecodeStreams(ss.data(), ss.size());
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},
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py::call_guard<py::gil_scoped_release>())
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.def("get_result", &PyClass::GetResult,
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py::call_guard<py::gil_scoped_release>())
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.def("is_endpoint", &PyClass::IsEndpoint,
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py::call_guard<py::gil_scoped_release>())
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.def("reset", &PyClass::Reset, py::call_guard<py::gil_scoped_release>());
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}
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} // namespace sherpa_onnx
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