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Commit d8fb9bda authored by Michael Butler's avatar Michael Butler Committed by Automerger Merge Worker
Browse files

Merge "Move NN_TRY macro out of struct initialization" am: abb60604 

Original change: https://android-review.googlesource.com/c/platform/hardware/interfaces/+/2081599



Change-Id: I2cccba8bf0544f39bbaee9c84bb9676d107b065e
Signed-off-by: default avatarAutomerger Merge Worker <android-build-automerger-merge-worker@system.gserviceaccount.com>
parents c7be910b abb60604

neuralnetworks/1.0/utils/src/Conversions.cpp

+54 −29
Original line number Diff line number Diff line
@@ -110,8 +110,9 @@ nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_ 
            return NN_ERROR() << "Unable to convert invalid ashmem memory object with "

                              << memory.handle()->numInts << " numInts, but expected 0";

        }

        auto fd = NN_TRY(nn::dupFd(memory.handle()->data[0]));

        auto handle = nn::Memory::Ashmem{

                .fd = NN_TRY(nn::dupFd(memory.handle()->data[0])),

                .fd = std::move(fd),

                .size = static_cast<size_t>(memory.size()),

        };

        return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});
@@ -137,12 +138,13 @@ nn::GeneralResult<nn::SharedMemory> createSharedMemoryFromHidlMemory(const hidl_ 
    }



    if (memory.name() != "hardware_buffer_blob") {

        auto handle = nn::Memory::Unknown{

                .handle = NN_TRY(unknownHandleFromNativeHandle(memory.handle())),

        auto handle = NN_TRY(unknownHandleFromNativeHandle(memory.handle()));

        auto unknown = nn::Memory::Unknown{

                .handle = std::move(handle),

                .size = static_cast<size_t>(memory.size()),

                .name = memory.name(),

        };

        return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(handle)});

        return std::make_shared<const nn::Memory>(nn::Memory{.handle = std::move(unknown)});

    }



#ifdef __ANDROID__
@@ -245,19 +247,23 @@ GeneralResult<DataLocation> unvalidatedConvert(const hal::V1_0::DataLocation& lo 
}



GeneralResult<Operand> unvalidatedConvert(const hal::V1_0::Operand& operand) {

    const auto type = NN_TRY(unvalidatedConvert(operand.type));

    const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));

    const auto location = NN_TRY(unvalidatedConvert(operand.location));

    return Operand{

            .type = NN_TRY(unvalidatedConvert(operand.type)),

            .type = type,

            .dimensions = operand.dimensions,

            .scale = operand.scale,

            .zeroPoint = operand.zeroPoint,

            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),

            .location = NN_TRY(unvalidatedConvert(operand.location)),

            .lifetime = lifetime,

            .location = location,

    };

}



GeneralResult<Operation> unvalidatedConvert(const hal::V1_0::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -298,26 +304,30 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_0::Model& model) { 
        }

    }



    auto operands = NN_TRY(unvalidatedConvert(model.operands));

    auto main = Model::Subgraph{

            .operands = NN_TRY(unvalidatedConvert(model.operands)),

            .operands = std::move(operands),

            .operations = std::move(operations),

            .inputIndexes = model.inputIndexes,

            .outputIndexes = model.outputIndexes,

    };



    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    return Model{

            .main = std::move(main),

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

    };

}



GeneralResult<Request::Argument> unvalidatedConvert(const hal::V1_0::RequestArgument& argument) {

    const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE

                                              : Request::Argument::LifeTime::POOL;

    const auto location = NN_TRY(unvalidatedConvert(argument.location));

    return Request::Argument{

            .lifetime = lifetime,

            .location = NN_TRY(unvalidatedConvert(argument.location)),

            .location = location,

            .dimensions = argument.dimensions,

    };

}
@@ -328,9 +338,11 @@ GeneralResult<Request> unvalidatedConvert(const hal::V1_0::Request& request) { 
    pools.reserve(memories.size());

    std::move(memories.begin(), memories.end(), std::back_inserter(pools));



    auto inputs = NN_TRY(unvalidatedConvert(request.inputs));

    auto outputs = NN_TRY(unvalidatedConvert(request.outputs));

    return Request{

            .inputs = NN_TRY(unvalidatedConvert(request.inputs)),

            .outputs = NN_TRY(unvalidatedConvert(request.outputs)),

            .inputs = std::move(inputs),

            .outputs = std::move(outputs),

            .pools = std::move(pools),

    };

}
@@ -500,11 +512,13 @@ nn::GeneralResult<PerformanceInfo> unvalidatedConvert( 
}



nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {

    const auto float32Performance = NN_TRY(unvalidatedConvert(

            capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32)));

    const auto quantized8Performance = NN_TRY(unvalidatedConvert(

            capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM)));

    return Capabilities{

            .float32Performance = NN_TRY(unvalidatedConvert(

                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),

            .quantized8Performance = NN_TRY(unvalidatedConvert(

                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),

            .float32Performance = float32Performance,

            .quantized8Performance = quantized8Performance,

    };

}
@@ -517,20 +531,24 @@ nn::GeneralResult<DataLocation> unvalidatedConvert(const nn::DataLocation& locat 
}



nn::GeneralResult<Operand> unvalidatedConvert(const nn::Operand& operand) {

    const auto type = NN_TRY(unvalidatedConvert(operand.type));

    const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));

    const auto location = NN_TRY(unvalidatedConvert(operand.location));

    return Operand{

            .type = NN_TRY(unvalidatedConvert(operand.type)),

            .type = type,

            .dimensions = operand.dimensions,

            .numberOfConsumers = 0,

            .scale = operand.scale,

            .zeroPoint = operand.zeroPoint,

            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),

            .location = NN_TRY(unvalidatedConvert(operand.location)),

            .lifetime = lifetime,

            .location = location,

    };

}



nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -572,13 +590,16 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) { 
        operands[i].numberOfConsumers = numberOfConsumers[i];

    }



    auto operations = NN_TRY(unvalidatedConvert(model.main.operations));

    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    return Model{

            .operands = std::move(operands),

            .operations = NN_TRY(unvalidatedConvert(model.main.operations)),

            .operations = std::move(operations),

            .inputIndexes = model.main.inputIndexes,

            .outputIndexes = model.main.outputIndexes,

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

    };

}
@@ -589,9 +610,10 @@ nn::GeneralResult<RequestArgument> unvalidatedConvert( 
               << "Request cannot be unvalidatedConverted because it contains pointer-based memory";

    }

    const bool hasNoValue = requestArgument.lifetime == nn::Request::Argument::LifeTime::NO_VALUE;

    const auto location = NN_TRY(unvalidatedConvert(requestArgument.location));

    return RequestArgument{

            .hasNoValue = hasNoValue,

            .location = NN_TRY(unvalidatedConvert(requestArgument.location)),

            .location = location,

            .dimensions = requestArgument.dimensions,

    };

}
@@ -606,10 +628,13 @@ nn::GeneralResult<Request> unvalidatedConvert(const nn::Request& request) { 
               << "Request cannot be unvalidatedConverted because it contains pointer-based memory";

    }



    auto inputs = NN_TRY(unvalidatedConvert(request.inputs));

    auto outputs = NN_TRY(unvalidatedConvert(request.outputs));

    auto pools = NN_TRY(unvalidatedConvert(request.pools));

    return Request{

            .inputs = NN_TRY(unvalidatedConvert(request.inputs)),

            .outputs = NN_TRY(unvalidatedConvert(request.outputs)),

            .pools = NN_TRY(unvalidatedConvert(request.pools)),

            .inputs = std::move(inputs),

            .outputs = std::move(outputs),

            .pools = std::move(pools),

    };

}

neuralnetworks/1.1/utils/src/Conversions.cpp

+25 −14
Original line number Diff line number Diff line
@@ -88,8 +88,9 @@ GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_1::Capabilities& ca 
}



GeneralResult<Operation> unvalidatedConvert(const hal::V1_1::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -110,17 +111,20 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_1::Model& model) { 
        }

    }



    auto operands = NN_TRY(unvalidatedConvert(model.operands));

    auto main = Model::Subgraph{

            .operands = NN_TRY(unvalidatedConvert(model.operands)),

            .operands = std::move(operands),

            .operations = std::move(operations),

            .inputIndexes = model.inputIndexes,

            .outputIndexes = model.outputIndexes,

    };



    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    return Model{

            .main = std::move(main),

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,

    };

}
@@ -195,19 +199,23 @@ nn::GeneralResult<OperationType> unvalidatedConvert(const nn::OperationType& ope 
}



nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {

    const auto float32Performance = NN_TRY(unvalidatedConvert(

            capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32)));

    const auto quanitized8Performance = NN_TRY(unvalidatedConvert(

            capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM)));

    const auto relaxedFloat32toFloat16Performance =

            NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));

    return Capabilities{

            .float32Performance = NN_TRY(unvalidatedConvert(

                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),

            .quantized8Performance = NN_TRY(unvalidatedConvert(

                    capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_QUANT8_ASYMM))),

            .relaxedFloat32toFloat16Performance = NN_TRY(

                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),

            .float32Performance = float32Performance,

            .quantized8Performance = quanitized8Performance,

            .relaxedFloat32toFloat16Performance = relaxedFloat32toFloat16Performance,

    };

}



nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -229,13 +237,16 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) { 
        operands[i].numberOfConsumers = numberOfConsumers[i];

    }



    auto operations = NN_TRY(unvalidatedConvert(model.main.operations));

    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    return Model{

            .operands = std::move(operands),

            .operations = NN_TRY(unvalidatedConvert(model.main.operations)),

            .operations = std::move(operations),

            .inputIndexes = model.main.inputIndexes,

            .outputIndexes = model.main.outputIndexes,

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,

    };

}

neuralnetworks/1.2/utils/src/Conversions.cpp

+59 −32
Original line number Diff line number Diff line
@@ -131,15 +131,18 @@ GeneralResult<Capabilities> unvalidatedConvert(const hal::V1_2::Capabilities& ca 


GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(

        const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {

    const auto type = NN_TRY(unvalidatedConvert(operandPerformance.type));

    const auto info = NN_TRY(unvalidatedConvert(operandPerformance.info));

    return Capabilities::OperandPerformance{

            .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),

            .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),

            .type = type,

            .info = info,

    };

}



GeneralResult<Operation> unvalidatedConvert(const hal::V1_2::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -154,14 +157,18 @@ GeneralResult<Operand::SymmPerChannelQuantParams> unvalidatedConvert( 
}



GeneralResult<Operand> unvalidatedConvert(const hal::V1_2::Operand& operand) {

    const auto type = NN_TRY(unvalidatedConvert(operand.type));

    const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));

    const auto location = NN_TRY(unvalidatedConvert(operand.location));

    auto extraParams = NN_TRY(unvalidatedConvert(operand.extraParams));

    return Operand{

            .type = NN_TRY(unvalidatedConvert(operand.type)),

            .type = type,

            .dimensions = operand.dimensions,

            .scale = operand.scale,

            .zeroPoint = operand.zeroPoint,

            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),

            .location = NN_TRY(unvalidatedConvert(operand.location)),

            .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),

            .lifetime = lifetime,

            .location = location,

            .extraParams = std::move(extraParams),

    };

}
@@ -196,19 +203,23 @@ GeneralResult<Model> unvalidatedConvert(const hal::V1_2::Model& model) { 
        }

    }



    auto operands = NN_TRY(unvalidatedConvert(model.operands));

    auto main = Model::Subgraph{

            .operands = NN_TRY(unvalidatedConvert(model.operands)),

            .operands = std::move(operands),

            .operations = std::move(operations),

            .inputIndexes = model.inputIndexes,

            .outputIndexes = model.outputIndexes,

    };



    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));

    return Model{

            .main = std::move(main),

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,

            .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),

            .extensionNameToPrefix = std::move(extensionNameToPrefix),

    };

}
@@ -248,9 +259,10 @@ GeneralResult<Timing> unvalidatedConvert(const hal::V1_2::Timing& timing) { 
}



GeneralResult<Extension> unvalidatedConvert(const hal::V1_2::Extension& extension) {

    auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));

    return Extension{

            .name = extension.name,

            .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),

            .operandTypes = std::move(operandTypes),

    };

}
@@ -406,35 +418,41 @@ nn::GeneralResult<DeviceType> unvalidatedConvert(const nn::DeviceType& deviceTyp 
}



nn::GeneralResult<Capabilities> unvalidatedConvert(const nn::Capabilities& capabilities) {

    std::vector<nn::Capabilities::OperandPerformance> operandPerformance;

    operandPerformance.reserve(capabilities.operandPerformance.asVector().size());

    std::vector<nn::Capabilities::OperandPerformance> filteredOperandPerformances;

    filteredOperandPerformances.reserve(capabilities.operandPerformance.asVector().size());

    std::copy_if(capabilities.operandPerformance.asVector().begin(),

                 capabilities.operandPerformance.asVector().end(),

                 std::back_inserter(operandPerformance),

                 std::back_inserter(filteredOperandPerformances),

                 [](const nn::Capabilities::OperandPerformance& operandPerformance) {

                     return compliantVersion(operandPerformance.type).has_value();

                 });



    const auto relaxedFloat32toFloat16PerformanceScalar =

            NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar));

    const auto relaxedFloat32toFloat16PerformanceTensor =

            NN_TRY(unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor));

    auto operandPerformance = NN_TRY(unvalidatedConvert(filteredOperandPerformances));

    return Capabilities{

            .relaxedFloat32toFloat16PerformanceScalar = NN_TRY(

                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceScalar)),

            .relaxedFloat32toFloat16PerformanceTensor = NN_TRY(

                    unvalidatedConvert(capabilities.relaxedFloat32toFloat16PerformanceTensor)),

            .operandPerformance = NN_TRY(unvalidatedConvert(operandPerformance)),

            .relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,

            .relaxedFloat32toFloat16PerformanceTensor = relaxedFloat32toFloat16PerformanceTensor,

            .operandPerformance = std::move(operandPerformance),

    };

}



nn::GeneralResult<Capabilities::OperandPerformance> unvalidatedConvert(

        const nn::Capabilities::OperandPerformance& operandPerformance) {

    const auto type = NN_TRY(unvalidatedConvert(operandPerformance.type));

    const auto info = NN_TRY(unvalidatedConvert(operandPerformance.info));

    return Capabilities::OperandPerformance{

            .type = NN_TRY(unvalidatedConvert(operandPerformance.type)),

            .info = NN_TRY(unvalidatedConvert(operandPerformance.info)),

            .type = type,

            .info = info,

    };

}



nn::GeneralResult<Operation> unvalidatedConvert(const nn::Operation& operation) {

    const auto type = NN_TRY(unvalidatedConvert(operation.type));

    return Operation{

            .type = NN_TRY(unvalidatedConvert(operation.type)),

            .type = type,

            .inputs = operation.inputs,

            .outputs = operation.outputs,

    };
@@ -449,15 +467,19 @@ nn::GeneralResult<SymmPerChannelQuantParams> unvalidatedConvert( 
}



nn::GeneralResult<Operand> unvalidatedConvert(const nn::Operand& operand) {

    const auto type = NN_TRY(unvalidatedConvert(operand.type));

    const auto lifetime = NN_TRY(unvalidatedConvert(operand.lifetime));

    const auto location = NN_TRY(unvalidatedConvert(operand.location));

    auto extraParams = NN_TRY(unvalidatedConvert(operand.extraParams));

    return Operand{

            .type = NN_TRY(unvalidatedConvert(operand.type)),

            .type = type,

            .dimensions = operand.dimensions,

            .numberOfConsumers = 0,

            .scale = operand.scale,

            .zeroPoint = operand.zeroPoint,

            .lifetime = NN_TRY(unvalidatedConvert(operand.lifetime)),

            .location = NN_TRY(unvalidatedConvert(operand.location)),

            .extraParams = NN_TRY(unvalidatedConvert(operand.extraParams)),

            .lifetime = lifetime,

            .location = location,

            .extraParams = std::move(extraParams),

    };

}
@@ -482,15 +504,19 @@ nn::GeneralResult<Model> unvalidatedConvert(const nn::Model& model) { 
        operands[i].numberOfConsumers = numberOfConsumers[i];

    }



    auto operations = NN_TRY(unvalidatedConvert(model.main.operations));

    auto operandValues = NN_TRY(unvalidatedConvert(model.operandValues));

    auto pools = NN_TRY(unvalidatedConvert(model.pools));

    auto extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix));

    return Model{

            .operands = std::move(operands),

            .operations = NN_TRY(unvalidatedConvert(model.main.operations)),

            .operations = std::move(operations),

            .inputIndexes = model.main.inputIndexes,

            .outputIndexes = model.main.outputIndexes,

            .operandValues = NN_TRY(unvalidatedConvert(model.operandValues)),

            .pools = NN_TRY(unvalidatedConvert(model.pools)),

            .operandValues = std::move(operandValues),

            .pools = std::move(pools),

            .relaxComputationFloat32toFloat16 = model.relaxComputationFloat32toFloat16,

            .extensionNameToPrefix = NN_TRY(unvalidatedConvert(model.extensionNameToPrefix)),

            .extensionNameToPrefix = std::move(extensionNameToPrefix),

    };

}
@@ -524,9 +550,10 @@ nn::GeneralResult<Timing> unvalidatedConvert(const nn::Timing& timing) { 
}



nn::GeneralResult<Extension> unvalidatedConvert(const nn::Extension& extension) {

    auto operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes));

    return Extension{

            .name = extension.name,

            .operandTypes = NN_TRY(unvalidatedConvert(extension.operandTypes)),

            .operandTypes = std::move(operandTypes),

    };

}

neuralnetworks/1.3/utils/src/Conversions.cpp

+89 −48

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neuralnetworks/aidl/utils/src/Conversions.cpp

+135 −71

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