Improving your machine learning workflow using the Arm NN SDK

Loading the model into the Arm NN SDK runtime

If everything has been done correctly, your network is now ready for use with the Arm NN SDK. For a detailed example of how to load your model into the Arm NN SDK runtime, see Deploying a Caffe MNIST model using the Arm NN SDK or Deploying a TensorFlow MNIST model on Arm NN. This documentation includes example code.  

Briefly, to load your model into the Arm NN runtime, you must complete the following steps:

1. Link to the appropriate parser for your framework of choice and the core Arm NN runtime.
2. Instantiate the parser.
3. Load the model file using the parser.
4. Create a RunTime object using the lRuntime::Create() function.
5. Pass the DeviceSpec object and the input network object to the Optimize() function. The parser produces the input network object and you can query the DeviceSpec object using the Runtime::GetDeviceSpec() function.
6. Load the IOptimizedNetwork object that the Optimize() function produces into the runtime using the IRuntime::LoadNetwork() function.