hi,
1 As we see, there is some framework or tools that could transform the pytroch model to NPU model just like RKNN.
Could we or anyone else could support the tools or code to complete this converting?
2 Quantinatization is a boring work, yet qat is so usefull for us when working on the a311d NPU. So is there any method to directly support the pytorch QAT (quantization aware training) ?
3 Have we got the statistics data with all the cnn framework available on the a311d NPU,which one is the efficientest? And how fast are they , and what is the best utilization ratioof information of them?
4 Could we support the arbitrary subgraph spliting? Which one should we choose for graph spliting and layer/graph level accelerating ?
BR
hi, 1 As we see, there is some framework or tools that could transform the pytroch model to NPU model just like RKNN. Could we or anyone else could support the tools or code to complete this converting? 2 Quantinatization is a boring work, yet qat is so usefull for us when working on the a311d NPU. So is there any method to directly support the pytorch QAT (quantization aware training) ? 3 Have we got the statistics data with all the cnn framework available on the a311d NPU,which one is the efficientest? And how fast are they , and what is the best utilization ratioof information of them? 4 Could we support the arbitrary subgraph spliting? Which one should we choose for graph spliting and layer/graph level accelerating ? BR
BR