[GitHub] WANG-MengJiao opened a new issue #13219: using C++ interface on CPU to extract feature vector, delete NDArray::WaitAll() generate incorrect result

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WANG-MengJiao opened a new issue #13219: using C++  interface on CPU to extract feature vector, delete NDArray::WaitAll() generate incorrect result
URL: https://github.com/apache/incubator-mxnet/issues/13219
 
 
   I am using a c++ api on CPU to extract a 512-dim feature vector from images. The feature vector will be printed out. 
   I encountered with the problem that with/without `NDArray::WaitAll()` generate totally different outputs. Among the results, with `NDArray::WaitAll()` can get correct vector. 
   However, the `NDArray::WaitAll()` is very time consuming. According to the comment in [feature_extract.cpp](https://github.com/apache/incubator-mxnet/blob/master/cpp-package/example/feature_extract/feature_extract.cpp), the `NDArray::WaitAll()` is needed only when copy between GPU and main memory. So I am wondering why the removal of `NDArray::WaitAll()` will cause incorrect output when I run the program on CPU. Is there any other tricks I should do?
   The code I used is as follows:
   ``` cpp
   using namespace std;
   using namespace mxnet::cpp;
   
   Context global_ctx(kCPU,0);
   
   class FeatureExtractor {
    private:
     /*the mean image, get from the pretrained model*/
     NDArray mean_img;
     /*the following two maps store all the paramters need by the model*/
     map<string, NDArray> args_map;
     map<string, NDArray> aux_map;
     Symbol net;
     Executor *executor;
     /*Get the feature layer we want to extract*/
     void GetFeatureSymbol() {
       net = Symbol::Load("/mymodelpath/model-r50-symbol.json")
                 .GetInternals()["fc1_output"];
     }
     /*Fill the trained paramters into the model, a.k.a. net, executor*/
     void LoadParameters() {
       map<string, NDArray> paramters;
       NDArray::Load("/mymodelpath/model-r50-0104.params", 0, &paramters);
       for (const auto &k : paramters) {
         if (k.first.substr(0, 4) == "aux:") {
           auto name = k.first.substr(4, k.first.size() - 4);
           aux_map[name] = k.second;
         }
         if (k.first.substr(0, 4) == "arg:") {
           auto name = k.first.substr(4, k.first.size() - 4);
   	    args_map[name] = k.second;
         }
       }
     }
   
    public:
     FeatureExtractor() {
       GetFeatureSymbol();
       LoadParameters();
     }
   
     void Extract(NDArray data) {
       data -= 127.5;
       data = data * 1.0 / 127.5;
       args_map["data"] = data;
       /*bind the executor*/
       executor = net.SimpleBind(global_ctx, args_map, map<string, NDArray>(), map<string, OpReqType>(), aux_map); 
       executor->Forward(false);    
       NDArray array = executor->outputs[0];
       NDArray::WaitAll();
       /*print out the features*/
       for (int i = 0; i < 512; ++i) {
         cout << array.At(0, i) << ",";
       }
       cout << endl;
     }
   };
   ```
   

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