After loading your model into the Arm NN SDK, you are now ready to run inference. You must ensure that any inputs you run inference on have had the same pre-processing that you used for training. All models have different pre-processing requirements. The following are examples of some of the actions you perform during pre-processing:
- Format conversion.
- Mean subtraction.
You can optionally do batching for performance improvements.
Finally, you call the function to run inference. For an example of how to run inference 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.