jpsalada opened a new issue #20143:
URL: https://github.com/apache/incubator-mxnet/issues/20143


   ## Description
   Getting stack overflow in the file cudnn_cnn_infer64_8.dll when running 
inference on Windows 10 with MXNET 6.0+MKL+CUDA 10.1 cpp package, using GPU and 
IIS. The error will NOT occur if I run the same code and input from a console 
application.  MXNET was compiled locally (CMakeCache.txt 
[here](https://justpaste.it/8y59u)). I am trying to run RetinaFace Res50 model.
   
   ### Error Message
   Unhandled exception at 0x00007FFD8F563D88 (cudnn_cnn_infer64_8.dll) in 
w3wp.exe: 0xC00000FD: Stack overflow (parameters: 0x0000000000000001, 
0x0000002C7BFC3000).
   
   ## To Reproduce
       //load model and configure ctx with gpu
   
       mxnet::cpp::NDArray data(mxnet::cpp::Shape(batch_size, num_channels, 
height, width), ctx, false);
       data.SyncCopyFromCPU(img_data, batch_size * num_channels * height * 
width);
       data.WaitToRead();  
   
       args["data"] = data;
   
       Executor *exec = sym_net.SimpleBind(*Ctx, args, map<string, NDArray>(), 
map<string, OpReqType>(), aux);
       exec->Forward(false);
   
     
        
        vector<uint> cls_shape = exec->outputs[idx].GetShape();
        uint sz = 1;
        int i = 0;
        while (i < cls_shape.size()) {
                sz *= cls_shape[i++];
        }
        vector<float> cls_data(sz);
           //will crash in the next instruction
        exec->outputs[idx].SyncCopyToCPU((float*)&(cls_data[0]), 
static_cast<mx_uint>( sz));
   
   
   ``
   ### Steps to reproduce
   
   1. I have created a c++ dll which contains the above code. 
   2. The dll is called from a C# WebAPI deployed on Windows IIS.
   3. The application will always crash in the same instruction as exemplified 
previously.
   
   ## What have you tried to solve it?
   
   1. Since when I run the same code pipeline using a console application it 
does not crash, I checked with ProcessExplorer that both are using the same 
CUDA files
   2. I also tried to replace my code with used in the example 
image_classification_predict.cc, and the same behavior occured when getting the 
output from the model
   3. Make sure the image input arriving is okey and also there are not errors 
when loading the model.
   
   ## Environment
   
   
   <details>
   <summary>Environment Information</summary>
   
   ----------System Info----------
   Platform     : Windows-10-10.0.19041-SP0
   system       : Windows
   node         : RM-UK-DT-0165
   release      : 10
   version      : 10.0.19041
   ----------Hardware Info----------
   machine      : AMD64
   processor    : Intel64 Family 6 Model 158 Stepping 10, GenuineIntel
   Name
   Intel(R) Core(TM) i7-8700 CPU @ 3.20GHz
   
   Microsoft Remote Display Adapter
   NVIDIA GeForce RTX 2080
   
   </details>
   


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