I am starting to experiment with Pytorch C++ frontend in my C++ application.
My data is held in data arrays in my application and can easily be stored as DLTensors.
  
      
      github.com
  
  
    

dmlc/dlpack 2


  RFC for common in-memory tensor structure and operator interface for deep learning system

  
  
    
    
  
  


Is there a no copy way of initializing Pytorch Tensors using DLTensors or data arrays.
The only method I can find is torch::from_blob and for this, I need to clone the data to use it on GPU’s
Ideally, I’m looking for a no copy way to initialize tensors, like move semantics.