adding a python api for offline decode (#110)

sherpa-onnx/python/csrc/offline-stream.cc

@@ -0,0 +1,61 @@
+// sherpa-onnx/python/csrc/offline-stream.cc
+//
+// Copyright (c)  2023 by manyeyes
+
+#include "sherpa-onnx/python/csrc/offline-stream.h"
+
+#include "sherpa-onnx/csrc/offline-stream.h"
+
+namespace sherpa_onnx {
+
+constexpr const char *kAcceptWaveformUsage = R"(
+Process audio samples.
+
+Args:
+  sample_rate:
+    Sample rate of the input samples. If it is different from the one
+    expected by the model, we will do resampling inside.
+  waveform:
+    A 1-D float32 tensor containing audio samples. It must be normalized
+    to the range [-1, 1].
+)";
+
+static void PybindOfflineRecognitionResult(py::module *m) {  // NOLINT
+  using PyClass = OfflineRecognitionResult;
+  py::class_<PyClass>(*m, "OfflineRecognitionResult")
+      .def_property_readonly("text",
+                             [](const PyClass &self) { return self.text; })
+      .def_property_readonly("tokens",
+                             [](const PyClass &self) { return self.tokens; })
+      .def_property_readonly(
+          "timestamps", [](const PyClass &self) { return self.timestamps; });
+}
+
+
+static void PybindOfflineFeatureExtractorConfig(py::module *m) {
+  using PyClass = OfflineFeatureExtractorConfig;
+  py::class_<PyClass>(*m, "OfflineFeatureExtractorConfig")
+      .def(py::init<int32_t, int32_t>(), py::arg("sampling_rate") = 16000,
+           py::arg("feature_dim") = 80)
+      .def_readwrite("sampling_rate", &PyClass::sampling_rate)
+      .def_readwrite("feature_dim", &PyClass::feature_dim)
+      .def("__str__", &PyClass::ToString);
+}
+
+
+void PybindOfflineStream(py::module *m) {
+  PybindOfflineFeatureExtractorConfig(m);
+  PybindOfflineRecognitionResult(m);
+
+  using PyClass = OfflineStream;
+  py::class_<PyClass>(*m, "OfflineStream")
+      .def(
+          "accept_waveform",
+          [](PyClass &self, float sample_rate, py::array_t<float> waveform) {
+            self.AcceptWaveform(sample_rate, waveform.data(), waveform.size());
+          },
+          py::arg("sample_rate"), py::arg("waveform"), kAcceptWaveformUsage)
+        .def_property_readonly("result", &PyClass::GetResult);
+}
+
+}  // namespace sherpa_onnx