android-nn-driver: adapt to S namespacing
This is a big sed that adapts the namespacing of a frameworks/ml file
from how the names were in Q to how they are in S.
These modifications more distinctly identify the names.
Test: local build
Change-Id: Ia029205691f1225044fed6a531ff12afe9c8e6bc
diff --git a/ArmnnPreparedModel_1_2.cpp b/ArmnnPreparedModel_1_2.cpp
index 2751d6d..06a3035 100644
--- a/ArmnnPreparedModel_1_2.cpp
+++ b/ArmnnPreparedModel_1_2.cpp
@@ -25,7 +25,7 @@
namespace {
-static const Timing g_NoTiming = {.timeOnDevice = UINT64_MAX, .timeInDriver = UINT64_MAX};
+static const V1_2::Timing g_NoTiming = {.timeOnDevice = UINT64_MAX, .timeInDriver = UINT64_MAX};
using namespace armnn_driver;
using TimePoint = std::chrono::steady_clock::time_point;
@@ -41,9 +41,9 @@
}
void NotifyCallbackAndCheck(const ::android::sp<V1_0::IExecutionCallback>& callback,
- ErrorStatus errorStatus,
- std::vector<OutputShape>,
- const Timing,
+ V1_0::ErrorStatus errorStatus,
+ std::vector<V1_2::OutputShape>,
+ const V1_2::Timing,
std::string callingFunction)
{
Return<void> returned = callback->notify(errorStatus);
@@ -56,9 +56,9 @@
}
void NotifyCallbackAndCheck(const ::android::sp<V1_2::IExecutionCallback>& callback,
- ErrorStatus errorStatus,
- std::vector<OutputShape> outputShapes,
- const Timing timing,
+ V1_0::ErrorStatus errorStatus,
+ std::vector<V1_2::OutputShape> outputShapes,
+ const V1_2::Timing timing,
std::string callingFunction)
{
Return<void> returned = callback->notify_1_2(errorStatus, outputShapes, timing);
@@ -70,7 +70,7 @@
}
}
-bool ValidateRequestArgument(const RequestArgument& requestArg, const armnn::TensorInfo& tensorInfo)
+bool ValidateRequestArgument(const V1_0::RequestArgument& requestArg, const armnn::TensorInfo& tensorInfo)
{
if (requestArg.dimensions.size() != 0)
{
@@ -95,7 +95,7 @@
return true;
}
-armnn::Tensor GetTensorForRequestArgument(const RequestArgument& requestArg,
+armnn::Tensor GetTensorForRequestArgument(const V1_0::RequestArgument& requestArg,
const armnn::TensorInfo& tensorInfo,
const std::vector<::android::nn::RunTimePoolInfo>& requestPools)
{
@@ -172,40 +172,40 @@
}
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,
- std::vector<OutputShape> outputShapes,
- const Timing& timing,
+ auto cb = [callback](V1_0::ErrorStatus errorStatus,
+ std::vector<V1_2::OutputShape> outputShapes,
+ const V1_2::Timing& timing,
std::string callingFunction)
{
NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction);
};
- return Execute(request, MeasureTiming::NO, cb);
+ return Execute(request, V1_2::MeasureTiming::NO, cb);
}
template<typename HalVersion>
-Return <ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute_1_2(const Request& request,
- MeasureTiming measureTiming,
+Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::execute_1_2(const V1_0::Request& request,
+ V1_2::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,
- std::vector<OutputShape> outputShapes,
- const Timing& timing,
+ auto cb = [callback](V1_0::ErrorStatus errorStatus,
+ std::vector<V1_2::OutputShape> outputShapes,
+ const V1_2::Timing& timing,
std::string callingFunction)
{
NotifyCallbackAndCheck(callback, errorStatus, outputShapes, timing, callingFunction);
@@ -215,8 +215,8 @@
}
template<typename HalVersion>
-Return<void> ArmnnPreparedModel_1_2<HalVersion>::executeSynchronously(const Request& request,
- MeasureTiming measureTiming,
+Return<void> ArmnnPreparedModel_1_2<HalVersion>::executeSynchronously(const V1_0::Request& request,
+ V1_2::MeasureTiming measureTiming,
executeSynchronously_cb cb)
{
ALOGV("ArmnnPreparedModel_1_2::executeSynchronously(): %s", GetModelSummary(m_Model).c_str());
@@ -230,7 +230,7 @@
TimePoint driverStart, driverEnd, deviceStart, deviceEnd;
- if (measureTiming == MeasureTiming::YES)
+ if (measureTiming == V1_2::MeasureTiming::YES)
{
driverStart = Now();
}
@@ -238,7 +238,7 @@
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();
}
@@ -252,10 +252,10 @@
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());
+ std::vector<V1_2::OutputShape> outputShapes(request.outputs.size());
try
{
@@ -270,7 +270,7 @@
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 +288,7 @@
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 +310,7 @@
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 +320,13 @@
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();
}
@@ -336,14 +336,14 @@
// run it
try
{
- if (measureTiming == MeasureTiming::YES)
+ if (measureTiming == V1_2::MeasureTiming::YES)
{
deviceStart = Now();
}
armnn::Status status = m_Runtime->EnqueueWorkload(m_NetworkId, *pInputTensors, *pOutputTensors);
- if (measureTiming == MeasureTiming::YES)
+ if (measureTiming == V1_2::MeasureTiming::YES)
{
deviceEnd = Now();
}
@@ -351,20 +351,20 @@
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();
}
@@ -379,19 +379,19 @@
}
ALOGV("ArmnnPreparedModel_1_2::executeSynchronously() after Execution");
- if (measureTiming == MeasureTiming::YES)
+ if (measureTiming == V1_2::MeasureTiming::YES)
{
driverEnd = Now();
- Timing timing;
+ V1_2::Timing timing;
timing.timeOnDevice = MicrosecondsDuration(deviceEnd, deviceStart);
timing.timeInDriver = MicrosecondsDuration(driverEnd, driverStart);
ALOGV("ArmnnPreparedModel_1_2::executeSynchronously timing Device = %" PRIu64 " Driver = %" PRIu64,
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 +402,7 @@
/// 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)
{}
@@ -422,9 +422,9 @@
m_MemoryCache.erase(slot);
}
- std::tuple<ErrorStatus, hidl_vec<OutputShape>, Timing> execute(
- const Request& request, const std::vector<int32_t>& slots,
- MeasureTiming measure) override
+ std::tuple<V1_0::ErrorStatus, hidl_vec<V1_2::OutputShape>, V1_2::Timing> execute(
+ const V1_0::Request& request, const std::vector<int32_t>& slots,
+ V1_2::MeasureTiming measure) override
{
ALOGV("ArmnnPreparedModel_1_2::BurstExecutorWithCache::execute");
hidl_vec<hidl_memory> pools(slots.size());
@@ -434,16 +434,16 @@
return m_MemoryCache[slot];
});
- Request fullRequest = request;
+ V1_0::Request fullRequest = request;
fullRequest.pools = std::move(pools);
// Setup Callback
- ErrorStatus returnedStatus = ErrorStatus::GENERAL_FAILURE;
- hidl_vec<OutputShape> returnedOutputShapes;
- Timing returnedTiming;
- auto cb = [&returnedStatus, &returnedOutputShapes, &returnedTiming](ErrorStatus status,
- const hidl_vec<OutputShape>& outputShapes,
- const Timing& timing)
+ V1_0::ErrorStatus returnedStatus = V1_0::ErrorStatus::GENERAL_FAILURE;
+ hidl_vec<V1_2::OutputShape> returnedOutputShapes;
+ V1_2::Timing returnedTiming;
+ auto cb = [&returnedStatus, &returnedOutputShapes, &returnedTiming](V1_0::ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing)
{
returnedStatus = status;
returnedOutputShapes = outputShapes;
@@ -454,7 +454,7 @@
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 +462,7 @@
}
private:
- IPreparedModel* const m_PreparedModel;
+ V1_2::IPreparedModel* const m_PreparedModel;
std::map<int, hidl_memory> m_MemoryCache;
};
@@ -484,11 +484,11 @@
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();
}
@@ -507,7 +507,7 @@
DumpTensorsIfRequired("Input", *pInputTensors);
std::vector<std::pair<int, armnn::Tensor> > outputTensors = *pOutputTensors.get();
- std::vector<OutputShape> outputShapes(outputTensors.size());
+ std::vector<V1_2::OutputShape> outputShapes(outputTensors.size());
for (unsigned int i = 0; i < outputTensors.size(); i++)
{
@@ -532,21 +532,21 @@
// run it
try
{
- if (cb.measureTiming == MeasureTiming::YES)
+ if (cb.measureTiming == V1_2::MeasureTiming::YES)
{
deviceStart = Now();
}
armnn::Status status = m_Runtime->EnqueueWorkload(m_NetworkId, *pInputTensors, *pOutputTensors);
- if (cb.measureTiming == MeasureTiming::YES)
+ if (cb.measureTiming == V1_2::MeasureTiming::YES)
{
deviceEnd = Now();
}
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 +554,13 @@
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;
}
@@ -574,15 +574,15 @@
pool.flush();
}
- if (cb.measureTiming == MeasureTiming::YES)
+ if (cb.measureTiming == V1_2::MeasureTiming::YES)
{
driverEnd = Now();
- Timing timing;
+ V1_2::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");
}
}
@@ -633,13 +633,13 @@
}
template<typename HalVersion>
-Return <ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::Execute(const Request& request,
- MeasureTiming measureTiming,
+Return <V1_0::ErrorStatus> ArmnnPreparedModel_1_2<HalVersion>::Execute(const V1_0::Request& request,
+ V1_2::MeasureTiming measureTiming,
armnnExecuteCallback_1_2 callback)
{
TimePoint driverStart;
- if (measureTiming == MeasureTiming::YES)
+ if (measureTiming == V1_2::MeasureTiming::YES)
{
driverStart = Now();
}
@@ -649,8 +649,8 @@
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 +668,8 @@
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
@@ -686,15 +686,15 @@
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);
}
pOutputTensors->reserve(request.outputs.size());
- std::vector<OutputShape> outputShapes(request.outputs.size());
+ std::vector<V1_2::OutputShape> outputShapes(request.outputs.size());
for (unsigned int i = 0; i < request.outputs.size(); i++)
{
@@ -705,8 +705,8 @@
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 +729,25 @@
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 +758,7 @@
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