From 4f8bce944e273e317cb84c7046ea514b9d958b4b Mon Sep 17 00:00:00 2001
From: zhuzizyf <42790740+zhuzizyf@users.noreply.github.com>
Date: 星期六, 22 四月 2023 14:54:49 +0800
Subject: [PATCH] Update FsmnVad.cc

---
 funasr/runtime/onnxruntime/src/FsmnVad.cc |   34 +++++++++++++++++++++++++---------
 1 files changed, 25 insertions(+), 9 deletions(-)

diff --git a/funasr/runtime/onnxruntime/src/FsmnVad.cc b/funasr/runtime/onnxruntime/src/FsmnVad.cc
index f75ead7..de63225 100644
--- a/funasr/runtime/onnxruntime/src/FsmnVad.cc
+++ b/funasr/runtime/onnxruntime/src/FsmnVad.cc
@@ -18,6 +18,7 @@
 
     read_model(vad_model);
     load_cmvn(vad_cmvn.c_str());
+    init_cache();
 
     fbank_opts.frame_opts.dither = 0;
     fbank_opts.mel_opts.num_bins = 80;
@@ -105,20 +106,18 @@
     }
     Ort::Value vad_feats_ort = Ort::Value::CreateTensor<float>(
             memory_info, vad_feats.data(), vad_feats.size(), vad_feats_shape, 3);
-    // cache node {batch,128,19,1}
-    const int64_t cache_feats_shape[4] = {1, 128, 19, 1};
-    std::vector<float> cache_feats(128 * 19 * 1, 0);
-    Ort::Value cache_feats_ort = Ort::Value::CreateTensor<float>(
-            memory_info, cache_feats.data(), cache_feats.size(), cache_feats_shape, 4);
-
+    
     // 3. Put nodes into onnx input vector
     std::vector<Ort::Value> vad_inputs;
     vad_inputs.emplace_back(std::move(vad_feats_ort));
     // 4 caches
-    for (int i = 0; i < 4; i++) {
-        vad_inputs.emplace_back(std::move(Ort::Value::CreateTensor<float>(
-                memory_info, cache_feats.data(), cache_feats.size(), cache_feats_shape, 4)));
+    // cache node {batch,128,19,1}
+    const int64_t cache_feats_shape[4] = {1, 128, 19, 1};
+    for (int i = 0; i < in_cache_.size(); i++) {
+      vad_inputs.emplace_back(std::move(Ort::Value::CreateTensor<float>(
+              memory_info, in_cache_[i].data(), in_cache_[i].size(), cache_feats_shape, 4)));
     }
+  
     // 4. Onnx infer
     std::vector<Ort::Value> vad_ort_outputs;
     try {
@@ -142,6 +141,12 @@
         (*out_prob)[i].resize(output_dim);
         memcpy((*out_prob)[i].data(), logp_data + i * output_dim,
                sizeof(float) * output_dim);
+    }
+  
+    // get 4 caches outputs,each size is 128*19
+    for (int i = 1; i < 5; i++) {
+      float* data = vad_ort_outputs[i].GetTensorMutableData<float>();
+      memcpy(in_cache_[i-1].data(), data, sizeof(float) * 128*19);
     }
 }
 
@@ -252,6 +257,17 @@
 
 }
 
+void FsmnVad::init_cache(){
+  std::vector<float> cache_feats(128 * 19 * 1, 0);
+  for (int i=0;i<4;i++){
+    in_cache_.emplace_back(cache_feats);
+  }
+};
+
+void FsmnVad::Reset(){
+  in_cache_.clear();
+  init_cache();
+};
 
 void FsmnVad::test() {
 

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