Hello @kulikovv,
Sorry for delay with reply.
If you are ok with supporting at the moment only armeabi-v7a, arm64-v8a, you can try to use LAPACK implementation from Qualcomm Math Library.
I experimented with linking it to pytorch_android with CMAKE_ARGS+=("-DUSE_LAPACK=ON")
It linked successfully for me.
I prepared PR with small instructions and changes in android/pytorch_android/CMakeLists.txt:

  
      github.com/pytorch/pytorch
  
  
    
  
    
  

  
    
      [NOT_FOR_COMMIT][android] Pytorch android build with USE_LAPACK and QML lib 8
    

    
      pytorch:master ← pytorch:ik_lapack_qml
    

    
      
        opened 
        
          
        
        Mar 23, 2020
      
      

      
        
          
          IvanKobzarev
        
      

      
        
          +20
          -0
        
      
    

  

  
  
    
    
  
  


Instructions from PR that I will duplicate here:

Download Qualcomm Math Library https://developer.qualcomm.com/software/qualcomm-math-library 13 (You might need to register new user to download it)
Unpack it in  ${PYTORCH_ROOT}/android/libs


QML can be used for armeabi-v7a, arm64-v8a android abis

sh ./scripts/build_pytorch_android.sh arm64-v8a,armeabi-v7a

I have not checked runtime using of it, if you test it, please reply here if it works or not.