package rockchip.hardware.neuralnetworks@1.0;

import ILoadModelCallback;
import IGetResultCallback;

interface IRKNeuralnetworks {
    @entry
    @exit
    @callflow(next={"*"})
    rknnInit(RKNNModel model, uint32_t size, uint32_t flag) generates (ErrorStatus status, RKNNContext context);

    @callflow(next={"*"})
    rknnDestroy(RKNNContext context) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnQuery(RKNNContext context, RKNNQueryCmd cmd, memory info, uint32_t size) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnInputsSet(RKNNContext context, Request request) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnRun(RKNNContext context, RKNNRunExtend extend) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnOutputsGet(RKNNContext context, Response response, RKNNOutputExtend extend) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnOutputsRelease(RKNNContext context, Response response) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnDestroyMemory(RKNNContext context, RKNNTensorMemory mem) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnSetIOMem(RKNNContext context, RKNNTensorMemory mem, RKNNTensorAttr attr) generates (ErrorStatus status);
    @callflow(next={"*"})
    rknnCreateMem(RKNNContext context, uint32_t size) generates (ErrorStatus status, RKNNTensorMemory mem);
    @callflow(next={"*"})
    rknnSetCoreMask(RKNNContext context, RKNNCoreMask coremask) generates (ErrorStatus status);

    // set callback for clients.
    registerCallback(ILoadModelCallback loadCallback, IGetResultCallback getCallback);
};