## Problem statement Our team using mxnet for training and for inference. In recent time we have intention to run inference on Android devices so we compile mxnet using android ndk and it works fine. Now we have intention to accelerate inference on mobile devices using [android NN Api](https://developer.android.com/ndk/guides/neuralnetworks) which android support since version 8.1. This Api serve as common interface to hardware GPU/Accelerator drivers and provide api in the form of operators ( ANEURALNETWORKS_CONV_2D, ANEURALNETWORKS_AVERAGE_POOL_2D...).
## Proposed solutions My task is to implement a proxy between mxnet and android nn using subgraph api and actually i already on half a way. I already implement selector, subgraph property, register opearator, and impement addition of major operator to android nn model based on partitioned graph. The design is similar to TensorRT subgraph but we don't use onnx as interim. So the question is, is it wise to implement subgraph for running inference on mobile device using framework which initially not have intention to run inference on mobile. I mean mxnet size in apk is about 150 MB that is pretty thick. I use mxnet 1.7. Will there a lightweight version of mxnet in future like TFlite for tensorflow? Also, any suggestions and thoughts about more appropriate solution for our problem are welcome! -- You are receiving this because you are subscribed to this thread. Reply to this email directly or view it on GitHub: https://github.com/apache/incubator-mxnet/issues/19521
