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

sherpa-onnx/csrc/offline-moonshine-model.h

@@ -0,0 +1,93 @@
+// sherpa-onnx/csrc/offline-moonshine-model.h
+//
+// Copyright (c)  2024  Xiaomi Corporation
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_MOONSHINE_MODEL_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_MOONSHINE_MODEL_H_
+
+#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 "onnxruntime_cxx_api.h"  // NOLINT
+#include "sherpa-onnx/csrc/offline-model-config.h"
+
+namespace sherpa_onnx {
+
+// please see
+// https://github.com/k2-fsa/sherpa-onnx/blob/master/scripts/moonshine/test.py
+class OfflineMoonshineModel {
+ public:
+  explicit OfflineMoonshineModel(const OfflineModelConfig &config);
+
+#if __ANDROID_API__ >= 9
+  OfflineMoonshineModel(AAssetManager *mgr, const OfflineModelConfig &config);
+#endif
+
+  ~OfflineMoonshineModel();
+
+  /** Run the preprocessor model.
+   *
+   * @param audio A float32 tensor of shape (batch_size, num_samples)
+   *
+   * @return Return a float32 tensor of shape (batch_size, T, dim) that
+   *         can be used as the input of ForwardEncoder()
+   */
+  Ort::Value ForwardPreprocessor(Ort::Value audio) const;
+
+  /** Run the encoder model.
+   *
+   * @param features A float32 tensor of shape (batch_size, T, dim)
+   * @param features_len A int32 tensor of shape (batch_size,)
+   * @returns A float32 tensor of shape (batch_size, T, dim).
+   */
+  Ort::Value ForwardEncoder(Ort::Value features, Ort::Value features_len) const;
+
+  /** Run the uncached decoder.
+   *
+   * @param token A int32 tensor of shape (batch_size, num_tokens)
+   * @param seq_len A int32 tensor of shape (batch_size,) containing number
+   *                of predicted tokens so far
+   * @param encoder_out A float32 tensor of shape (batch_size, T, dim)
+   *
+   * @returns Return a pair:
+   *
+   *          - logits, a float32 tensor of shape (batch_size, 1, dim)
+   *          - states, a list of states
+   */
+  std::pair<Ort::Value, std::vector<Ort::Value>> ForwardUnCachedDecoder(
+      Ort::Value token, Ort::Value seq_len, Ort::Value encoder_out) const;
+
+  /** Run the cached decoder.
+   *
+   * @param token A int32 tensor of shape (batch_size, num_tokens)
+   * @param seq_len A int32 tensor of shape (batch_size,) containing number
+   *                of predicted tokens so far
+   * @param encoder_out A float32 tensor of shape (batch_size, T, dim)
+   * @param states A list of previous states
+   *
+   * @returns Return a pair:
+   *          - logits, a float32 tensor of shape (batch_size, 1, dim)
+   *          - states, a list of new states
+   */
+  std::pair<Ort::Value, std::vector<Ort::Value>> ForwardCachedDecoder(
+      Ort::Value token, Ort::Value seq_len, Ort::Value encoder_out,
+      std::vector<Ort::Value> states) const;
+
+  /** Return an allocator for allocating memory
+   */
+  OrtAllocator *Allocator() const;
+
+ private:
+  class Impl;
+  std::unique_ptr<Impl> impl_;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_MOONSHINE_MODEL_H_