Add C++ runtime and Python APIs for Moonshine models (#1473)

sherpa-onnx/csrc/offline-recognizer-moonshine-impl.h

@@ -0,0 +1,150 @@
+// sherpa-onnx/csrc/offline-recognizer-moonshine-impl.h
+//
+// Copyright (c)  2024  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_MOONSHINE_IMPL_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_MOONSHINE_IMPL_H_
+
+#include <algorithm>
+#include <cmath>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#if __ANDROID_API__ >= 9
+#include "android/asset_manager.h"
+#include "android/asset_manager_jni.h"
+#endif
+
+#include "sherpa-onnx/csrc/offline-model-config.h"
+#include "sherpa-onnx/csrc/offline-moonshine-decoder.h"
+#include "sherpa-onnx/csrc/offline-moonshine-greedy-search-decoder.h"
+#include "sherpa-onnx/csrc/offline-moonshine-model.h"
+#include "sherpa-onnx/csrc/offline-recognizer-impl.h"
+#include "sherpa-onnx/csrc/offline-recognizer.h"
+#include "sherpa-onnx/csrc/symbol-table.h"
+#include "sherpa-onnx/csrc/transpose.h"
+
+namespace sherpa_onnx {
+
+static OfflineRecognitionResult Convert(
+    const OfflineMoonshineDecoderResult &src, const SymbolTable &sym_table) {
+  OfflineRecognitionResult r;
+  r.tokens.reserve(src.tokens.size());
+
+  std::string text;
+  for (auto i : src.tokens) {
+    if (!sym_table.Contains(i)) {
+      continue;
+    }
+
+    const auto &s = sym_table[i];
+    text += s;
+    r.tokens.push_back(s);
+  }
+
+  r.text = text;
+
+  return r;
+}
+
+class OfflineRecognizerMoonshineImpl : public OfflineRecognizerImpl {
+ public:
+  explicit OfflineRecognizerMoonshineImpl(const OfflineRecognizerConfig &config)
+      : OfflineRecognizerImpl(config),
+        config_(config),
+        symbol_table_(config_.model_config.tokens),
+        model_(std::make_unique<OfflineMoonshineModel>(config.model_config)) {
+    Init();
+  }
+
+#if __ANDROID_API__ >= 9
+  OfflineRecognizerMoonshineImpl(AAssetManager *mgr,
+                                 const OfflineRecognizerConfig &config)
+      : OfflineRecognizerImpl(mgr, config),
+        config_(config),
+        symbol_table_(mgr, config_.model_config.tokens),
+        model_(
+            std::make_unique<OfflineMoonshineModel>(mgr, config.model_config)) {
+    Init();
+  }
+
+#endif
+
+  void Init() {
+    if (config_.decoding_method == "greedy_search") {
+      decoder_ =
+          std::make_unique<OfflineMoonshineGreedySearchDecoder>(model_.get());
+    } else {
+      SHERPA_ONNX_LOGE(
+          "Only greedy_search is supported at present for moonshine. Given %s",
+          config_.decoding_method.c_str());
+      exit(-1);
+    }
+  }
+
+  std::unique_ptr<OfflineStream> CreateStream() const override {
+    MoonshineTag tag;
+    return std::make_unique<OfflineStream>(tag);
+  }
+
+  void DecodeStreams(OfflineStream **ss, int32_t n) const override {
+    // batch decoding is not implemented yet
+    for (int32_t i = 0; i != n; ++i) {
+      DecodeStream(ss[i]);
+    }
+  }
+
+  OfflineRecognizerConfig GetConfig() const override { return config_; }
+
+ private:
+  void DecodeStream(OfflineStream *s) const {
+    auto memory_info =
+        Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
+
+    std::vector<float> audio = s->GetFrames();
+
+    try {
+      std::array<int64_t, 2> shape{1, static_cast<int64_t>(audio.size())};
+
+      Ort::Value audio_tensor = Ort::Value::CreateTensor(
+          memory_info, audio.data(), audio.size(), shape.data(), shape.size());
+
+      Ort::Value features =
+          model_->ForwardPreprocessor(std::move(audio_tensor));
+
+      int32_t features_len = features.GetTensorTypeAndShapeInfo().GetShape()[1];
+
+      int64_t features_shape = 1;
+
+      Ort::Value features_len_tensor = Ort::Value::CreateTensor(
+          memory_info, &features_len, 1, &features_shape, 1);
+
+      Ort::Value encoder_out = model_->ForwardEncoder(
+          std::move(features), std::move(features_len_tensor));
+
+      auto results = decoder_->Decode(std::move(encoder_out));
+
+      auto r = Convert(results[0], symbol_table_);
+      r.text = ApplyInverseTextNormalization(std::move(r.text));
+      s->SetResult(r);
+    } catch (const Ort::Exception &ex) {
+      SHERPA_ONNX_LOGE(
+          "\n\nCaught exception:\n\n%s\n\nReturn an empty result. Number of "
+          "audio samples: %d",
+          ex.what(), static_cast<int32_t>(audio.size()));
+      return;
+    }
+  }
+
+ private:
+  OfflineRecognizerConfig config_;
+  SymbolTable symbol_table_;
+  std::unique_ptr<OfflineMoonshineModel> model_;
+  std::unique_ptr<OfflineMoonshineDecoder> decoder_;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_MOONSHINE_IMPL_H_