* Creating an InferenceSession from an on-disk model file and a set of SessionOptions.
* Registering customized loggers.
* Registering customized allocators.
* Registering predefined providers and set the priority order. ONNXRuntime has a set of predefined execution providers,like CUDA, MKLDNN. User can register providers to their InferenceSession. The order of registration indicates the preference order as well.
* Running a model with inputs. These inputs must be in CPU memory, not GPU. If the model has multiple outputs, user can specify which outputs they want.
* Converting an in-memory ONNX Tensor encoded in protobuf format, to a pointer that can be used as model input.