remove unnecessary log

speechx/examples/decoder/offline_decoder_sliding_chunk_main.cc

@@ -136,14 +136,16 @@ int main(int argc, char* argv[]) {
         }
         std::string result;
         result = decoder.GetFinalBestPath();
-        KALDI_LOG << " the result of " << utt << " is " << result;
+        decodable->Reset();
+        decoder.Reset();
         if (result.empty()) {
             // the TokenWriter can not write empty string.
-            result = " ";
+            ++num_err;
+            KALDI_LOG << " the result of " << utt << " is empty";
+            continue;
         }
+        KALDI_LOG << " the result of " << utt << " is " << result;
         result_writer.Write(utt, result);
-        decodable->Reset();
-        decoder.Reset();
         ++num_done;
     }
 

speechx/examples/decoder/offline_wfst_decoder_main.cc

@@ -139,14 +139,16 @@ int main(int argc, char* argv[]) {
         }
         std::string result;
         result = decoder.GetFinalBestPath();
-        KALDI_LOG << " the result of " << utt << " is " << result;
+        decodable->Reset();
+        decoder.Reset();
         if (result.empty()) {
             // the TokenWriter can not write empty string.
-            result = " ";
+            ++num_err;
+            KALDI_LOG << " the result of " << utt << " is empty";
+            continue;
         }
+        KALDI_LOG << " the result of " << utt << " is " << result;
         result_writer.Write(utt, result);
-        decodable->Reset();
-        decoder.Reset();
         ++num_done;
     }
 

speechx/speechx/nnet/decodable.cc

@@ -78,7 +78,6 @@ bool Decodable::AdvanceChunk() {
 
     frame_offset_ = frames_ready_;
     frames_ready_ += nnet_cache_.NumRows();
-    LOG(INFO) << "nnet size: " << nnet_cache_.NumRows();
     return true;
 }
 

speechx/speechx/nnet/paddle_nnet.cc

@@ -177,7 +177,6 @@ void PaddleNnet::FeedForward(const Vector<BaseFloat>& features,
         LOG(INFO) << "predictor run occurs error";
     }
 
-    LOG(INFO) << "get the model success";
     std::unique_ptr<paddle_infer::Tensor> h_out =
         predictor->GetOutputHandle(output_names[2]);
     assert(h_cache->get_shape() == h_out->shape());