Re-implement LM rescore for online transducer (#1231)
Co-authored-by: Martins Kronis <martins.kuznecovs@tilde.lv>
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@@ -13,13 +13,16 @@ namespace sherpa_onnx {
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void PybindOnlineLMConfig(py::module *m) {
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using PyClass = OnlineLMConfig;
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py::class_<PyClass>(*m, "OnlineLMConfig")
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.def(py::init<const std::string &, float, int32_t, const std::string &>(),
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.def(py::init<const std::string &, float, int32_t,
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const std::string &, bool>(),
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py::arg("model") = "", py::arg("scale") = 0.5f,
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py::arg("lm_num_threads") = 1, py::arg("lm_provider") = "cpu")
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py::arg("lm_num_threads") = 1, py::arg("lm_provider") = "cpu",
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py::arg("shallow_fusion") = true)
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.def_readwrite("model", &PyClass::model)
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.def_readwrite("scale", &PyClass::scale)
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.def_readwrite("lm_provider", &PyClass::lm_provider)
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.def_readwrite("lm_num_threads", &PyClass::lm_num_threads)
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.def_readwrite("shallow_fusion", &PyClass::shallow_fusion)
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.def("__str__", &PyClass::ToString);
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}
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