IVGCVSW-4473 Android R pre Hal 1_3 build changes
* Update ErrorStatus to V1_0::ErrorStatus
* Update Request to V1_0::Request
* Update OperandType to V1_2::OperandType
* Add namespace android::nn::hal in ArmnnDriverImpl for R only
* Add missing g_RelaxedFloat32toFloat16PerformancePowerUsageName
* Add namespace V1_0 or V1_1 where necessary
* Update Android.mk with R macro and android.hardware.neuralnetworks@1.3
* Remove androidnn.go
* include IAllocator in DriverTestHelpers
* Remove unused LOCAL_CFLAGS
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I1787f1ed6784b3bbec017536d87d49197405e853
Signed-off-by: Kevin May <kevin.may@arm.com>
diff --git a/ArmnnPreparedModel_1_2.cpp b/ArmnnPreparedModel_1_2.cpp
index 84ff6e2..9b79044 100644
--- a/ArmnnPreparedModel_1_2.cpp
+++ b/ArmnnPreparedModel_1_2.cpp
@@ -41,7 +41,7 @@
}
void NotifyCallbackAndCheck(const ::android::sp<V1_0::IExecutionCallback>& callback,
- ErrorStatus errorStatus,
+ V1_0::ErrorStatus errorStatus,
std::vector<OutputShape>,
const Timing,
std::string callingFunction)
@@ -56,7 +56,7 @@
}
void NotifyCallbackAndCheck(const ::android::sp<V1_2::IExecutionCallback>& callback,
- ErrorStatus errorStatus,
+ V1_0::ErrorStatus errorStatus,
std::vector<OutputShape> outputShapes,
const Timing timing,
std::string callingFunction)
@@ -172,16 +172,16 @@
}
template<typename HalVersion>
-Return <ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute(const Request& request,
+Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute(const V1_0::Request& request,
const ::android::sp<V1_0::IExecutionCallback>& callback)
{
if (callback.get() == nullptr)
{
ALOGE("ArmnnPreparedModel_1_2::execute invalid callback passed");
- return ErrorStatus::INVALID_ARGUMENT;
+ return V1_0::ErrorStatus::INVALID_ARGUMENT;
}
- auto cb = [callback](ErrorStatus errorStatus,
+ auto cb = [callback](V1_0::ErrorStatus errorStatus,
std::vector<OutputShape> outputShapes,
const Timing& timing,
std::string callingFunction)
@@ -193,17 +193,18 @@
}
template<typename HalVersion>
-Return <ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute_1_2(const Request& request,
- MeasureTiming measureTiming,
- const sp<V1_2::IExecutionCallback>& callback)
+Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute_1_2(
+ const V1_0::Request& request,
+ MeasureTiming measureTiming,
+ const sp<V1_2::IExecutionCallback>& callback)
{
if (callback.get() == nullptr)
{
ALOGE("ArmnnPreparedModel_1_2::execute_1_2 invalid callback passed");
- return ErrorStatus::INVALID_ARGUMENT;
+ return V1_0::ErrorStatus::INVALID_ARGUMENT;
}
- auto cb = [callback](ErrorStatus errorStatus,
+ auto cb = [callback](V1_0::ErrorStatus errorStatus,
std::vector<OutputShape> outputShapes,
const Timing& timing,
std::string callingFunction)
@@ -215,7 +216,7 @@
}
template<typename HalVersion>
-Return<void> ArmnnPreparedModel_1_2<HalVersion>::executeSynchronously(const Request& request,
+Return<void> ArmnnPreparedModel_1_2<HalVersion>::executeSynchronously(const V1_0::Request& request,
MeasureTiming measureTiming,
executeSynchronously_cb cb)
{
@@ -238,7 +239,7 @@
if (!android::nn::validateRequest(request, m_Model))
{
ALOGE("ArmnnPreparedModel_1_2::executeSynchronously invalid request model");
- cb(ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming);
return Void();
}
@@ -252,7 +253,7 @@
if (!setRunTimePoolInfosFromHidlMemories(pMemPools.get(), request.pools))
{
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
std::vector<OutputShape> outputShapes(request.outputs.size());
@@ -270,7 +271,7 @@
if (inputTensor.GetMemoryArea() == nullptr)
{
ALOGE("Cannot execute request. Error converting request input %u to tensor", i);
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
@@ -288,7 +289,7 @@
if (outputTensor.GetMemoryArea() == nullptr)
{
ALOGE("Cannot execute request. Error converting request output %u to tensor", i);
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
const size_t outputSize = outputTensorInfo.GetNumBytes();
@@ -310,7 +311,7 @@
if (bufferSize < outputSize)
{
ALOGW("ArmnnPreparedModel_1_2::Execute failed");
- cb(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, outputShapes, g_NoTiming);
+ cb(V1_0::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE, outputShapes, g_NoTiming);
return Void();
}
@@ -320,13 +321,13 @@
catch (armnn::Exception& e)
{
ALOGW("armnn::Exception caught while preparing for EnqueueWorkload: %s", e.what());
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
catch (std::exception& e)
{
ALOGE("std::exception caught while preparing for EnqueueWorkload: %s", e.what());
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
@@ -351,20 +352,20 @@
if (status != armnn::Status::Success)
{
ALOGW("EnqueueWorkload failed");
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
}
catch (armnn::Exception& e)
{
ALOGW("armnn::Exception caught from EnqueueWorkload: %s", e.what());
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
catch (std::exception& e)
{
ALOGE("std::exception caught from EnqueueWorkload: %s", e.what());
- cb(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming);
return Void();
}
@@ -375,8 +376,15 @@
// this is simpler and is what the CpuExecutor does.
for (android::nn::RunTimePoolInfo& pool : *pMemPools)
{
- pool.update();
+ // Type android::nn::RunTimePoolInfo has changed between Android P & Q and Android R, where
+ // update() has been removed and flush() added.
+ #if defined(ARMNN_ANDROID_R) // Use the new Android implementation.
+ pool.flush();
+ #else
+ pool.update();
+ #endif
}
+
ALOGV("ArmnnPreparedModel_1_2::executeSynchronously() after Execution");
if (measureTiming == MeasureTiming::YES)
@@ -387,11 +395,11 @@
timing.timeInDriver = MicrosecondsDuration(driverEnd, driverStart);
ALOGV("ArmnnPreparedModel_1_2::executeSynchronously timing Device = %lu Driver = %lu", timing.timeOnDevice,
timing.timeInDriver);
- cb(ErrorStatus::NONE, outputShapes, timing);
+ cb(V1_0::ErrorStatus::NONE, outputShapes, timing);
}
else
{
- cb(ErrorStatus::NONE, outputShapes, g_NoTiming);
+ cb(V1_0::ErrorStatus::NONE, outputShapes, g_NoTiming);
}
return Void();
}
@@ -402,7 +410,7 @@
/// ml/+/refs/tags/android-10.0.0_r20/nn/common/ExecutionBurstServer.cpp
class ArmnnBurstExecutorWithCache : public ExecutionBurstServer::IBurstExecutorWithCache {
public:
- ArmnnBurstExecutorWithCache(IPreparedModel* preparedModel)
+ ArmnnBurstExecutorWithCache(V1_2::IPreparedModel* preparedModel)
: m_PreparedModel(preparedModel)
{}
@@ -422,8 +430,8 @@
m_MemoryCache.erase(slot);
}
- std::tuple<ErrorStatus, hidl_vec<OutputShape>, Timing> execute(
- const Request& request, const std::vector<int32_t>& slots,
+ std::tuple<V1_0::ErrorStatus, hidl_vec<OutputShape>, Timing> execute(
+ const V1_0::Request& request, const std::vector<int32_t>& slots,
MeasureTiming measure) override
{
ALOGV("ArmnnPreparedModel_1_2::BurstExecutorWithCache::execute");
@@ -434,14 +442,14 @@
return m_MemoryCache[slot];
});
- Request fullRequest = request;
+ V1_0::Request fullRequest = request;
fullRequest.pools = std::move(pools);
// Setup Callback
- ErrorStatus returnedStatus = ErrorStatus::GENERAL_FAILURE;
+ V1_0::ErrorStatus returnedStatus = V1_0::ErrorStatus::GENERAL_FAILURE;
hidl_vec<OutputShape> returnedOutputShapes;
Timing returnedTiming;
- auto cb = [&returnedStatus, &returnedOutputShapes, &returnedTiming](ErrorStatus status,
+ auto cb = [&returnedStatus, &returnedOutputShapes, &returnedTiming](V1_0::ErrorStatus status,
const hidl_vec<OutputShape>& outputShapes,
const Timing& timing)
{
@@ -454,7 +462,7 @@
ALOGV("ArmnnPreparedModel_1_2::BurstExecutorWithCache executing");
const Return<void> ret = m_PreparedModel->executeSynchronously(fullRequest, measure, cb);
- if (!ret.isOk() || returnedStatus != ErrorStatus::NONE)
+ if (!ret.isOk() || returnedStatus != V1_0::ErrorStatus::NONE)
{
ALOGE("ArmnnPreparedModel_1_2::BurstExecutorWithCache::error executing");
}
@@ -462,7 +470,7 @@
}
private:
- IPreparedModel* const m_PreparedModel;
+ V1_2::IPreparedModel* const m_PreparedModel;
std::map<int, hidl_memory> m_MemoryCache;
};
@@ -484,11 +492,11 @@
if (burst == nullptr)
{
- cb(ErrorStatus::GENERAL_FAILURE, {});
+ cb(V1_0::ErrorStatus::GENERAL_FAILURE, {});
}
else
{
- cb(ErrorStatus::NONE, burst);
+ cb(V1_0::ErrorStatus::NONE, burst);
}
return Void();
}
@@ -546,7 +554,7 @@
if (status != armnn::Status::Success)
{
ALOGW("EnqueueWorkload failed");
- cb.callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming,
+ cb.callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming,
"ArmnnPreparedModel_1_2::ExecuteGraph");
return;
}
@@ -554,13 +562,13 @@
catch (armnn::Exception& e)
{
ALOGW("armnn:Exception caught from EnqueueWorkload: %s", e.what());
- cb.callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::ExecuteGraph");
+ cb.callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::ExecuteGraph");
return;
}
catch (std::exception& e)
{
ALOGE("std::exception caught from EnqueueWorkload: %s", e.what());
- cb.callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::ExecuteGraph");
+ cb.callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::ExecuteGraph");
return;
}
@@ -571,7 +579,13 @@
// this is simpler and is what the CpuExecutor does.
for (android::nn::RunTimePoolInfo& pool : *pMemPools)
{
- pool.update();
+ // Type android::nn::RunTimePoolInfo has changed between Android P & Q and Android R, where
+ // update() has been removed and flush() added.
+ #if defined(ARMNN_ANDROID_R) // Use the new Android implementation.
+ pool.flush();
+ #else
+ pool.update();
+ #endif
}
if (cb.measureTiming == MeasureTiming::YES)
@@ -580,9 +594,9 @@
Timing timing;
timing.timeOnDevice = MicrosecondsDuration(deviceEnd, deviceStart);
timing.timeInDriver = MicrosecondsDuration(driverEnd, cb.driverStart);
- cb.callback(ErrorStatus::NONE, outputShapes, timing, "ExecuteGraph");
+ cb.callback(V1_0::ErrorStatus::NONE, outputShapes, timing, "ExecuteGraph");
} else {
- cb.callback(ErrorStatus::NONE, outputShapes, g_NoTiming, "ExecuteGraph");
+ cb.callback(V1_0::ErrorStatus::NONE, outputShapes, g_NoTiming, "ExecuteGraph");
}
}
@@ -633,9 +647,9 @@
}
template<typename HalVersion>
-Return <ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::Execute(const Request& request,
- MeasureTiming measureTiming,
- armnnExecuteCallback_1_2 callback)
+Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::Execute(const V1_0::Request& request,
+ MeasureTiming measureTiming,
+ armnnExecuteCallback_1_2 callback)
{
TimePoint driverStart;
@@ -649,8 +663,8 @@
if (!android::nn::validateRequest(request, m_Model))
{
- callback(ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::INVALID_ARGUMENT;
+ callback(V1_0::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::INVALID_ARGUMENT;
}
if (!m_RequestInputsAndOutputsDumpDir.empty())
@@ -668,8 +682,8 @@
if (!setRunTimePoolInfosFromHidlMemories(pMemPools.get(), request.pools))
{
- callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::GENERAL_FAILURE;
+ callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::GENERAL_FAILURE;
}
// add the inputs and outputs with their data
@@ -686,8 +700,8 @@
if (inputTensor.GetMemoryArea() == nullptr)
{
ALOGE("Cannot execute request. Error converting request input %u to tensor", i);
- callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::GENERAL_FAILURE;
+ callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::GENERAL_FAILURE;
}
pInputTensors->emplace_back(i, inputTensor);
@@ -705,8 +719,8 @@
if (outputTensor.GetMemoryArea() == nullptr)
{
ALOGE("Cannot execute request. Error converting request output %u to tensor", i);
- callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::GENERAL_FAILURE;
+ callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::GENERAL_FAILURE;
}
const size_t outputSize = outputTensorInfo.GetNumBytes();
@@ -729,25 +743,25 @@
if (bufferSize < outputSize)
{
ALOGW("ArmnnPreparedModel_1_2::Execute failed");
- callback(ErrorStatus::OUTPUT_INSUFFICIENT_SIZE,
+ callback(V1_0::ErrorStatus::OUTPUT_INSUFFICIENT_SIZE,
outputShapes,
g_NoTiming,
"ArmnnPreparedModel_1_2::Execute");
- return ErrorStatus::NONE;
+ return V1_0::ErrorStatus::NONE;
}
}
}
catch (armnn::Exception& e)
{
ALOGW("armnn::Exception caught while preparing for EnqueueWorkload: %s", e.what());
- callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::GENERAL_FAILURE;
+ callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::GENERAL_FAILURE;
}
catch (std::exception& e)
{
ALOGE("std::exception caught while preparing for EnqueueWorkload: %s", e.what());
- callback(ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
- return ErrorStatus::GENERAL_FAILURE;
+ callback(V1_0::ErrorStatus::GENERAL_FAILURE, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
+ return V1_0::ErrorStatus::GENERAL_FAILURE;
}
ALOGV("ArmnnPreparedModel_1_2::execute(...) before PostMsg");
@@ -758,7 +772,7 @@
armnnCb.driverStart = driverStart;
m_RequestThread.PostMsg(this, pMemPools, pInputTensors, pOutputTensors, armnnCb);
ALOGV("ArmnnPreparedModel_1_2::execute(...) after PostMsg");
- return ErrorStatus::NONE;
+ return V1_0::ErrorStatus::NONE;
}
#ifdef ARMNN_ANDROID_NN_V1_2