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Commit e5e67024 authored by Michael Butler's avatar Michael Butler Committed by Lev Proleev
Browse files

Add dynamic interface casting to NN utility code 

Prior to this CL, the NN utility code would always use the type of
IPreparedModel provided by IPreparedModeCallback::notify*. This means
that an IPreparedModel returned as a dynamic type of V1_X but static
type of V1_Y would be used by the utility code as V1_Y. This CL adds
dynamic casting, such that an IPreparedModel returned as a dynamic type
of V1_X but static type V1_Y will be dynamically cast to V1_X and used
as a V1_X::IPreparedModel.

This CL also adds the utility functions
V1_[0123]::convertFromNonCanonical to convert from a non-canonical type
to another non-canonical type by using canonical types as an
intermediate conversion "hop."

Bug: 178180472
Test: mma
Change-Id: I709b2a8944af2cc78b089aade55df1e2ab7b40cc
Merged-In: I709b2a8944af2cc78b089aade55df1e2ab7b40cc
(cherry picked from commit 49b5e4eb)
parent b755e019

neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h

+6 −0
Original line number Diff line number Diff line
@@ -44,6 +44,12 @@ bool valid(const Type& halObject) { 
    return result.has_value();

}



template <typename Type>

auto convertFromNonCanonical(const Type& nonCanonicalObject)

        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {

    return convert(NN_TRY(nn::convert(nonCanonicalObject)));

}



}  // namespace android::hardware::neuralnetworks::V1_0::utils



#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_H

neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h

+6 −0
Original line number Diff line number Diff line
@@ -47,6 +47,12 @@ bool valid(const Type& halObject) { 
    return result.has_value();

}



template <typename Type>

auto convertFromNonCanonical(const Type& nonCanonicalObject)

        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {

    return convert(NN_TRY(nn::convert(nonCanonicalObject)));

}



}  // namespace android::hardware::neuralnetworks::V1_1::utils



#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_H

neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h

+6 −0
Original line number Diff line number Diff line
@@ -54,6 +54,12 @@ bool valid(const Type& halObject) { 
    return result.has_value();

}



template <typename Type>

auto convertFromNonCanonical(const Type& nonCanonicalObject)

        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {

    return convert(NN_TRY(nn::convert(nonCanonicalObject)));

}



}  // namespace android::hardware::neuralnetworks::V1_2::utils



#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_H

neuralnetworks/1.2/utils/src/Callbacks.cpp

+10 −1
Original line number Diff line number Diff line
@@ -43,6 +43,15 @@ 
namespace android::hardware::neuralnetworks::V1_2::utils {

namespace {



nn::GeneralResult<nn::SharedPreparedModel> prepareModelCallback(

        V1_0::ErrorStatus status, const sp<V1_0::IPreparedModel>& preparedModel) {

    if (const auto dynamicPreparedModel =

                V1_2::IPreparedModel::castFrom(preparedModel).withDefault(nullptr)) {

        return V1_2::utils::prepareModelCallback(status, dynamicPreparedModel);

    }

    return V1_0::utils::prepareModelCallback(status, preparedModel);

}



nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>

convertExecutionGeneralResultsHelper(const hidl_vec<OutputShape>& outputShapes,

                                     const Timing& timing) {
@@ -72,7 +81,7 @@ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executi 


Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,

                                           const sp<V1_0::IPreparedModel>& preparedModel) {

    mData.put(V1_0::utils::prepareModelCallback(status, preparedModel));

    mData.put(prepareModelCallback(status, preparedModel));

    return Void();

}

neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h

+6 −0
Original line number Diff line number Diff line
@@ -49,6 +49,12 @@ bool valid(const Type& halObject) { 
    return result.has_value();

}



template <typename Type>

auto convertFromNonCanonical(const Type& nonCanonicalObject)

        -> decltype(convert(nn::convert(nonCanonicalObject).value())) {

    return convert(NN_TRY(nn::convert(nonCanonicalObject)));

}



}  // namespace android::hardware::neuralnetworks::V1_3::utils



#endif  // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_H