1.0/ArmnnDriverImpl.cpp

//
// Copyright © 2017 Arm Ltd. All rights reserved.
// See LICENSE file in the project root for full license information.
//

#include "ArmnnDriverImpl.hpp"
#include "ModelToINetworkConverter.hpp"
#include "ArmnnPreparedModel.hpp"
#include "SystemPropertiesUtils.hpp"

#if defined(ARMNN_ANDROID_P)
// The headers of the ML framework have changed between Android O and Android P.
// The validation functions have been moved into their own header, ValidateHal.h.
#include <ValidateHal.h>
#endif

#include <log/log.h>

using namespace std;
using namespace android;
using namespace android::nn;
using namespace android::hardware;

namespace
{

const char *g_Float32PerformanceExecTimeName = "ArmNN.float32Performance.execTime";
const char *g_Float32PerformancePowerUsageName = "ArmNN.float32Performance.powerUsage";
const char *g_Quantized8PerformanceExecTimeName = "ArmNN.quantized8Performance.execTime";
const char *g_Quantized8PerformancePowerUsageName = "ArmNN.quantized8Performance.powerUsage";

void NotifyCallbackAndCheck(const sp<IPreparedModelCallback>& callback,
                            ErrorStatus errorStatus,
                            const sp<IPreparedModel>& preparedModelPtr)
{
    Return<void> returned = callback->notify(errorStatus, preparedModelPtr);
    // This check is required, if the callback fails and it isn't checked it will bring down the service
    if (!returned.isOk())
    {
        ALOGE("V1_0::ArmnnDriverImpl::prepareModel: hidl callback failed to return properly: %s ",
            returned.description().c_str());
    }
}

Return<ErrorStatus> FailPrepareModel(ErrorStatus error,
                                     const string& message,
                                     const sp<IPreparedModelCallback>& callback)
{
    ALOGW("V1_0::ArmnnDriverImpl::prepareModel: %s", message.c_str());
    NotifyCallbackAndCheck(callback, error, nullptr);
    return error;
}

} // namespace

namespace armnn_driver
{
namespace V1_0
{

Return<void> ArmnnDriverImpl::getCapabilities(
        const armnn::IRuntimePtr& runtime,
        neuralnetworks::V1_0::IDevice::getCapabilities_cb cb)
{
    ALOGV("V1_0::ArmnnDriverImpl::getCapabilities()");

    neuralnetworks::V1_0::Capabilities capabilities;
    if (runtime)
    {
        capabilities.float32Performance.execTime =
            ParseSystemProperty(g_Float32PerformanceExecTimeName, .1f);

        capabilities.float32Performance.powerUsage =
            ParseSystemProperty(g_Float32PerformancePowerUsageName, .1f);

        capabilities.quantized8Performance.execTime =
            ParseSystemProperty(g_Quantized8PerformanceExecTimeName, .1f);

        capabilities.quantized8Performance.powerUsage =
            ParseSystemProperty(g_Quantized8PerformancePowerUsageName, .1f);

        cb(ErrorStatus::NONE, capabilities);
    }
    else
    {
        capabilities.float32Performance.execTime = 0;
        capabilities.float32Performance.powerUsage = 0;
        capabilities.quantized8Performance.execTime = 0;
        capabilities.quantized8Performance.powerUsage = 0;

        cb(ErrorStatus::DEVICE_UNAVAILABLE, capabilities);
    }

    return Void();
}

Return<void> ArmnnDriverImpl::getSupportedOperations(
        const armnn::IRuntimePtr& runtime,
        const DriverOptions& options,
        const neuralnetworks::V1_0::Model& model,
        neuralnetworks::V1_0::IDevice::getSupportedOperations_cb cb)
{
    ALOGV("V1_0::ArmnnDriverImpl::getSupportedOperations()");

    vector<bool> result;

    if (!runtime)
    {
        cb(ErrorStatus::DEVICE_UNAVAILABLE, result);
        return Void();
    }

    // Run general model validation, if this doesn't pass we shouldn't analyse the model anyway
    if (!android::nn::validateModel(model))
    {
        cb(ErrorStatus::INVALID_ARGUMENT, result);
        return Void();
    }

    // Attempt to convert the model to an ArmNN input network (INetwork).
    armnn_driver::ModelToINetworkConverter<HalVersion_1_0> modelConverter(options.GetComputeDevice(),
        model, options.GetForcedUnsupportedOperations());

    if (modelConverter.GetConversionResult() != ConversionResult::Success
        && modelConverter.GetConversionResult() != ConversionResult::UnsupportedFeature)
    {
        cb(ErrorStatus::GENERAL_FAILURE, result);
        return Void();
    }

    // Check each operation if it was converted successfully and copy the flags
    // into the result (vector<bool>) that we need to return to Android
    result.reserve(model.operations.size());
    for (uint32_t operationIdx = 0; operationIdx < model.operations.size(); operationIdx++)
    {
        bool operationSupported = modelConverter.IsOperationSupported(operationIdx);
        result.push_back(operationSupported);
    }

    cb(ErrorStatus::NONE, result);
    return Void();
}

Return<ErrorStatus> ArmnnDriverImpl::prepareModel(
        const armnn::IRuntimePtr& runtime,
        const armnn::IGpuAccTunedParametersPtr& clTunedParameters,
        const DriverOptions& options,
        const neuralnetworks::V1_0::Model& model,
        const sp<IPreparedModelCallback>& cb,
        bool  float32ToFloat16)
{
    ALOGV("V1_0::ArmnnDriverImpl::prepareModel()");

    if (cb.get() == nullptr)
    {
        ALOGW("V1_0::ArmnnDriverImpl::prepareModel: Invalid callback passed to prepareModel");
        return ErrorStatus::INVALID_ARGUMENT;
    }

    if (!runtime)
    {
        return FailPrepareModel(ErrorStatus::DEVICE_UNAVAILABLE,
                                "V1_0::ArmnnDriverImpl::prepareModel: Device unavailable", cb);
    }

    if (!android::nn::validateModel(model))
    {
        return FailPrepareModel(ErrorStatus::INVALID_ARGUMENT,
                                "V1_0::ArmnnDriverImpl::prepareModel: Invalid model passed as input", cb);
    }

    // Deliberately ignore any unsupported operations requested by the options -
    // at this point we're being asked to prepare a model that we've already declared support for
    // and the operation indices may be different to those in getSupportedOperations anyway.
    set<unsigned int> unsupportedOperations;
    armnn_driver::ModelToINetworkConverter<HalVersion_1_0> modelConverter(options.GetComputeDevice(), model,
        unsupportedOperations);

    if (modelConverter.GetConversionResult() != ConversionResult::Success)
    {
        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, "ModelToINetworkConverter failed", cb);
        return ErrorStatus::NONE;
    }

    // optimize the network
    armnn::IOptimizedNetworkPtr optNet(nullptr, nullptr);
    armnn::OptimizerOptions OptOptions;
    OptOptions.m_ReduceFp32ToFp16 = float32ToFloat16;

    try
    {
        optNet = armnn::Optimize(*modelConverter.GetINetwork(),
                                 {options.GetComputeDevice()},
                                 runtime->GetDeviceSpec(),
                                 OptOptions);
    }
    catch (armnn::Exception &e)
    {
        stringstream message;
        message << "armnn::Exception (" << e.what() << ") caught from optimize.";
        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, message.str(), cb);
        return ErrorStatus::NONE;
    }

    // Check that the optimized network is valid.
    if (!optNet)
    {
        FailPrepareModel(ErrorStatus::GENERAL_FAILURE,
                         "V1_0::ArmnnDriverImpl::prepareModel: Invalid optimized network", cb);
        return ErrorStatus::NONE;
    }

    // Export the optimized network graph to a dot file if an output dump directory
    // has been specified in the drivers' arguments.
    ExportNetworkGraphToDotFile(*optNet,
                                options.GetRequestInputsAndOutputsDumpDir(),
                                model);

    // load it into the runtime
    armnn::NetworkId netId = 0;
    try
    {
        if (runtime->LoadNetwork(netId, move(optNet)) != armnn::Status::Success)
        {
            return FailPrepareModel(ErrorStatus::GENERAL_FAILURE,
                "V1_0::ArmnnDriverImpl::prepareModel: Network could not be loaded", cb);
        }
    }
    catch (armnn::Exception& e)
    {
        stringstream message;
        message << "armnn::Exception (" << e.what()<< ") caught from LoadNetwork.";
        FailPrepareModel(ErrorStatus::GENERAL_FAILURE, message.str(), cb);
        return ErrorStatus::NONE;
    }

    unique_ptr<ArmnnPreparedModel> preparedModel(new ArmnnPreparedModel(
        netId,
        runtime.get(),
        model,
        options.GetRequestInputsAndOutputsDumpDir(),
        options.IsGpuProfilingEnabled()
    ));

    // Run a single 'dummy' inference of the model. This means that CL kernels will get compiled (and tuned if
    // this is enabled) before the first 'real' inference which removes the overhead of the first inference.
    preparedModel->ExecuteWithDummyInputs();

    if (clTunedParameters &&
        options.GetClTunedParametersMode() == armnn::IGpuAccTunedParameters::Mode::UpdateTunedParameters)
    {
        // Now that we've done one inference the CL kernel parameters will have been tuned, so save the updated file.
        try
        {
            clTunedParameters->Save(options.GetClTunedParametersFile().c_str());
        }
        catch (const armnn::Exception& error)
        {
            ALOGE("V1_0::ArmnnDriverImpl: Failed to save CL tuned parameters file '%s': %s",
                options.GetClTunedParametersFile().c_str(), error.what());
        }
    }

    NotifyCallbackAndCheck(cb, ErrorStatus::NONE, preparedModel.release());

    return ErrorStatus::NONE;
}

Return<DeviceStatus> ArmnnDriverImpl::getStatus()
{
    ALOGV("V1_0::ArmnnDriverImpl::getStatus()");

    return DeviceStatus::AVAILABLE;
}

} // armnn_driver::namespace V1_0
} // namespace armnn_driver