Support TDNN models from the yesno recipe from icefall (#262)

sherpa-onnx/csrc/offline-tdnn-ctc-model.cc

@@ -0,0 +1,106 @@
+// sherpa-onnx/csrc/offline-tdnn-ctc-model.cc
+//
+// Copyright (c)  2023  Xiaomi Corporation
+
+#include "sherpa-onnx/csrc/offline-tdnn-ctc-model.h"
+
+#include "sherpa-onnx/csrc/macros.h"
+#include "sherpa-onnx/csrc/onnx-utils.h"
+#include "sherpa-onnx/csrc/session.h"
+#include "sherpa-onnx/csrc/text-utils.h"
+#include "sherpa-onnx/csrc/transpose.h"
+
+namespace sherpa_onnx {
+
+class OfflineTdnnCtcModel::Impl {
+ public:
+  explicit Impl(const OfflineModelConfig &config)
+      : config_(config),
+        env_(ORT_LOGGING_LEVEL_ERROR),
+        sess_opts_(GetSessionOptions(config)),
+        allocator_{} {
+    Init();
+  }
+
+  std::pair<Ort::Value, Ort::Value> Forward(Ort::Value features) {
+    auto nnet_out =
+        sess_->Run({}, input_names_ptr_.data(), &features, 1,
+                   output_names_ptr_.data(), output_names_ptr_.size());
+
+    std::vector<int64_t> nnet_out_shape =
+        nnet_out[0].GetTensorTypeAndShapeInfo().GetShape();
+
+    std::vector<int64_t> out_length_vec(nnet_out_shape[0], nnet_out_shape[1]);
+    std::vector<int64_t> out_length_shape(1, nnet_out_shape[0]);
+
+    auto memory_info =
+        Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
+
+    Ort::Value nnet_out_length = Ort::Value::CreateTensor(
+        memory_info, out_length_vec.data(), out_length_vec.size(),
+        out_length_shape.data(), out_length_shape.size());
+
+    return {std::move(nnet_out[0]), Clone(Allocator(), &nnet_out_length)};
+  }
+
+  int32_t VocabSize() const { return vocab_size_; }
+
+  OrtAllocator *Allocator() const { return allocator_; }
+
+ private:
+  void Init() {
+    auto buf = ReadFile(config_.tdnn.model);
+
+    sess_ = std::make_unique<Ort::Session>(env_, buf.data(), buf.size(),
+                                           sess_opts_);
+
+    GetInputNames(sess_.get(), &input_names_, &input_names_ptr_);
+
+    GetOutputNames(sess_.get(), &output_names_, &output_names_ptr_);
+
+    // get meta data
+    Ort::ModelMetadata meta_data = sess_->GetModelMetadata();
+    if (config_.debug) {
+      std::ostringstream os;
+      PrintModelMetadata(os, meta_data);
+      SHERPA_ONNX_LOGE("%s\n", os.str().c_str());
+    }
+
+    Ort::AllocatorWithDefaultOptions allocator;  // used in the macro below
+    SHERPA_ONNX_READ_META_DATA(vocab_size_, "vocab_size");
+  }
+
+ private:
+  OfflineModelConfig config_;
+  Ort::Env env_;
+  Ort::SessionOptions sess_opts_;
+  Ort::AllocatorWithDefaultOptions allocator_;
+
+  std::unique_ptr<Ort::Session> sess_;
+
+  std::vector<std::string> input_names_;
+  std::vector<const char *> input_names_ptr_;
+
+  std::vector<std::string> output_names_;
+  std::vector<const char *> output_names_ptr_;
+
+  int32_t vocab_size_ = 0;
+};
+
+OfflineTdnnCtcModel::OfflineTdnnCtcModel(const OfflineModelConfig &config)
+    : impl_(std::make_unique<Impl>(config)) {}
+
+OfflineTdnnCtcModel::~OfflineTdnnCtcModel() = default;
+
+std::pair<Ort::Value, Ort::Value> OfflineTdnnCtcModel::Forward(
+    Ort::Value features, Ort::Value /*features_length*/) {
+  return impl_->Forward(std::move(features));
+}
+
+int32_t OfflineTdnnCtcModel::VocabSize() const { return impl_->VocabSize(); }
+
+OrtAllocator *OfflineTdnnCtcModel::Allocator() const {
+  return impl_->Allocator();
+}
+
+}  // namespace sherpa_onnx