Begin to support CTC models (#119)

Please see https://k2-fsa.github.io/sherpa/onnx/pretrained_models/offline-ctc/nemo/index.html for a list of pre-trained CTC models from NeMo.

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

@@ -0,0 +1,128 @@
+// sherpa-onnx/csrc/offline-recognizer-ctc-impl.h
+//
+// Copyright (c)  2022-2023  Xiaomi Corporation
+
+#ifndef SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_CTC_IMPL_H_
+#define SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_CTC_IMPL_H_
+
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+
+#include "sherpa-onnx/csrc/offline-ctc-decoder.h"
+#include "sherpa-onnx/csrc/offline-ctc-greedy-search-decoder.h"
+#include "sherpa-onnx/csrc/offline-ctc-model.h"
+#include "sherpa-onnx/csrc/offline-recognizer-impl.h"
+#include "sherpa-onnx/csrc/pad-sequence.h"
+#include "sherpa-onnx/csrc/symbol-table.h"
+
+namespace sherpa_onnx {
+
+static OfflineRecognitionResult Convert(const OfflineCtcDecoderResult &src,
+                                        const SymbolTable &sym_table) {
+  OfflineRecognitionResult r;
+  r.tokens.reserve(src.tokens.size());
+
+  std::string text;
+
+  for (int32_t i = 0; i != src.tokens.size(); ++i) {
+    auto sym = sym_table[src.tokens[i]];
+    text.append(sym);
+    r.tokens.push_back(std::move(sym));
+  }
+  r.text = std::move(text);
+
+  return r;
+}
+
+class OfflineRecognizerCtcImpl : public OfflineRecognizerImpl {
+ public:
+  explicit OfflineRecognizerCtcImpl(const OfflineRecognizerConfig &config)
+      : config_(config),
+        symbol_table_(config_.model_config.tokens),
+        model_(OfflineCtcModel::Create(config_.model_config)) {
+    config_.feat_config.nemo_normalize_type =
+        model_->FeatureNormalizationMethod();
+
+    if (config.decoding_method == "greedy_search") {
+      if (!symbol_table_.contains("<blk>")) {
+        SHERPA_ONNX_LOGE(
+            "We expect that tokens.txt contains "
+            "the symbol <blk> and its ID.");
+        exit(-1);
+      }
+
+      int32_t blank_id = symbol_table_["<blk>"];
+      decoder_ = std::make_unique<OfflineCtcGreedySearchDecoder>(blank_id);
+    } else {
+      SHERPA_ONNX_LOGE("Only greedy_search is supported at present. Given %s",
+                       config.decoding_method.c_str());
+      exit(-1);
+    }
+  }
+
+  std::unique_ptr<OfflineStream> CreateStream() const override {
+    return std::make_unique<OfflineStream>(config_.feat_config);
+  }
+
+  void DecodeStreams(OfflineStream **ss, int32_t n) const override {
+    auto memory_info =
+        Ort::MemoryInfo::CreateCpu(OrtDeviceAllocator, OrtMemTypeDefault);
+
+    int32_t feat_dim = config_.feat_config.feature_dim;
+
+    std::vector<Ort::Value> features;
+    features.reserve(n);
+
+    std::vector<std::vector<float>> features_vec(n);
+    std::vector<int64_t> features_length_vec(n);
+
+    for (int32_t i = 0; i != n; ++i) {
+      std::vector<float> f = ss[i]->GetFrames();
+
+      int32_t num_frames = f.size() / feat_dim;
+      features_vec[i] = std::move(f);
+
+      features_length_vec[i] = num_frames;
+
+      std::array<int64_t, 2> shape = {num_frames, feat_dim};
+
+      Ort::Value x = Ort::Value::CreateTensor(
+          memory_info, features_vec[i].data(), features_vec[i].size(),
+          shape.data(), shape.size());
+      features.push_back(std::move(x));
+    }  // for (int32_t i = 0; i != n; ++i)
+
+    std::vector<const Ort::Value *> features_pointer(n);
+    for (int32_t i = 0; i != n; ++i) {
+      features_pointer[i] = &features[i];
+    }
+
+    std::array<int64_t, 1> features_length_shape = {n};
+    Ort::Value x_length = Ort::Value::CreateTensor(
+        memory_info, features_length_vec.data(), n,
+        features_length_shape.data(), features_length_shape.size());
+
+    Ort::Value x = PadSequence(model_->Allocator(), features_pointer,
+                               -23.025850929940457f);
+    auto t = model_->Forward(std::move(x), std::move(x_length));
+
+    auto results = decoder_->Decode(std::move(t.first), std::move(t.second));
+
+    for (int32_t i = 0; i != n; ++i) {
+      auto r = Convert(results[i], symbol_table_);
+      ss[i]->SetResult(r);
+    }
+  }
+
+ private:
+  OfflineRecognizerConfig config_;
+  SymbolTable symbol_table_;
+  std::unique_ptr<OfflineCtcModel> model_;
+  std::unique_ptr<OfflineCtcDecoder> decoder_;
+};
+
+}  // namespace sherpa_onnx
+
+#endif  // SHERPA_ONNX_CSRC_OFFLINE_RECOGNIZER_CTC_IMPL_H_