Merge "Make NN canonical->HIDL adapter execute* methods synchronous" am: f955569c8a
Original change: https://android-review.googlesource.com/c/platform/hardware/interfaces/+/2005130
Change-Id: Icff3acb7b47cc84518222e9f37b7515d6783cb73
diff --git a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
index 4c0b328..80ed41d 100644
--- a/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
+++ b/neuralnetworks/utils/adapter/aidl/include/nnapi/hal/aidl/Adapter.h
@@ -46,9 +46,6 @@
/**
* Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object.
*
- * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
- * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
- *
* @param device NNAPI canonical IDevice interface object to be adapted.
* @param executor Type-erased executor to handle executing tasks asynchronously.
* @return AIDL NN HAL IDevice interface object.
@@ -58,9 +55,6 @@
/**
* Adapt an NNAPI canonical interface object to a AIDL NN HAL interface object.
*
- * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
- * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
- *
* This function uses a default executor, which will execute tasks from a detached thread.
*
* @param device NNAPI canonical IDevice interface object to be adapted.
diff --git a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
index 6fba4ab..3bd93e0 100644
--- a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
+++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/Adapter.h
@@ -46,9 +46,6 @@
/**
* Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object.
*
- * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
- * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
- *
* @param device NNAPI canonical IDevice interface object to be adapted.
* @param executor Type-erased executor to handle executing tasks asynchronously.
* @return HIDL NN HAL IDevice interface object.
@@ -58,9 +55,6 @@
/**
* Adapt an NNAPI canonical interface object to a HIDL NN HAL interface object.
*
- * The IPreparedModel object created from IDevice::prepareModel or IDevice::preparedModelFromCache
- * must return "const nn::Model*" from IPreparedModel::getUnderlyingResource().
- *
* This function uses a default executor, which will execute tasks from a detached thread.
*
* @param device NNAPI canonical IDevice interface object to be adapted.
diff --git a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
index 9482b0d..01cd4bc 100644
--- a/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
+++ b/neuralnetworks/utils/adapter/hidl/include/nnapi/hal/PreparedModel.h
@@ -39,7 +39,7 @@
// Class that adapts nn::IPreparedModel to V1_3::IPreparedModel.
class PreparedModel final : public V1_3::IPreparedModel {
public:
- PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor);
+ explicit PreparedModel(nn::SharedPreparedModel preparedModel);
Return<V1_0::ErrorStatus> execute(const V1_0::Request& request,
const sp<V1_0::IExecutionCallback>& callback) override;
@@ -70,7 +70,6 @@
private:
const nn::SharedPreparedModel kPreparedModel;
- const Executor kExecutor;
};
} // namespace android::hardware::neuralnetworks::adapter
diff --git a/neuralnetworks/utils/adapter/hidl/src/Device.cpp b/neuralnetworks/utils/adapter/hidl/src/Device.cpp
index 0f44638..305a1b4 100644
--- a/neuralnetworks/utils/adapter/hidl/src/Device.cpp
+++ b/neuralnetworks/utils/adapter/hidl/src/Device.cpp
@@ -62,11 +62,11 @@
using PrepareModelResult = nn::GeneralResult<nn::SharedPreparedModel>;
-sp<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel, Executor executor) {
+sp<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel) {
if (preparedModel == nullptr) {
return nullptr;
}
- return sp<PreparedModel>::make(std::move(preparedModel), std::move(executor));
+ return sp<PreparedModel>::make(std::move(preparedModel));
}
void notify(V1_0::IPreparedModelCallback* callback, nn::ErrorStatus status,
@@ -105,14 +105,14 @@
}
template <typename CallbackType>
-void notify(CallbackType* callback, PrepareModelResult result, Executor executor) {
+void notify(CallbackType* callback, PrepareModelResult result) {
if (!result.has_value()) {
const auto [message, status] = std::move(result).error();
LOG(ERROR) << message;
notify(callback, status, nullptr);
} else {
auto preparedModel = std::move(result).value();
- auto hidlPreparedModel = adaptPreparedModel(std::move(preparedModel), std::move(executor));
+ auto hidlPreparedModel = adaptPreparedModel(std::move(preparedModel));
notify(callback, nn::ErrorStatus::NONE, std::move(hidlPreparedModel));
}
}
@@ -133,10 +133,10 @@
auto nnModel = NN_TRY(convertInput(model));
- Task task = [device, nnModel = std::move(nnModel), executor, callback] {
+ Task task = [device, nnModel = std::move(nnModel), callback] {
auto result = device->prepareModel(nnModel, nn::ExecutionPreference::DEFAULT,
nn::Priority::DEFAULT, {}, {}, {}, {}, {}, {});
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), {});
@@ -154,10 +154,10 @@
auto nnModel = NN_TRY(convertInput(model));
const auto nnPreference = NN_TRY(convertInput(preference));
- Task task = [device, nnModel = std::move(nnModel), nnPreference, executor, callback] {
+ Task task = [device, nnModel = std::move(nnModel), nnPreference, callback] {
auto result = device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {}, {}, {},
{}, {}, {});
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), {});
@@ -183,10 +183,10 @@
Task task = [device, nnModel = std::move(nnModel), nnPreference,
nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
- nnToken, executor, callback] {
+ nnToken, callback] {
auto result = device->prepareModel(nnModel, nnPreference, nn::Priority::DEFAULT, {},
nnModelCache, nnDataCache, nnToken, {}, {});
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), {});
@@ -213,10 +213,10 @@
Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline,
nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
- nnToken, executor, callback] {
+ nnToken, callback] {
auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline,
nnModelCache, nnDataCache, nnToken, {}, {});
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), nnDeadline);
@@ -238,9 +238,9 @@
const auto nnToken = nn::CacheToken(token);
Task task = [device, nnModelCache = std::move(nnModelCache),
- nnDataCache = std::move(nnDataCache), nnToken, executor, callback] {
+ nnDataCache = std::move(nnDataCache), nnToken, callback] {
auto result = device->prepareModelFromCache({}, nnModelCache, nnDataCache, nnToken);
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), {});
@@ -262,9 +262,9 @@
const auto nnToken = nn::CacheToken(token);
auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache),
- nnDataCache = std::move(nnDataCache), nnToken, executor, callback] {
+ nnDataCache = std::move(nnDataCache), nnToken, callback] {
auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken);
- notify(callback.get(), std::move(result), executor);
+ notify(callback.get(), std::move(result));
};
executor(std::move(task), nnDeadline);
diff --git a/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
index c6055a6..3570a74 100644
--- a/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
+++ b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
@@ -55,15 +55,6 @@
return result;
}
-nn::GeneralResult<nn::Version> validateRequestForModel(const nn::Request& request,
- const nn::Model& model) {
- nn::GeneralResult<nn::Version> version = nn::validateRequestForModel(request, model);
- if (!version.ok()) {
- version.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
- }
- return version;
-}
-
class FencedExecutionCallback final : public V1_3::IFencedExecutionCallback {
public:
explicit FencedExecutionCallback(const nn::ExecuteFencedInfoCallback& callback)
@@ -144,58 +135,48 @@
}
nn::GeneralResult<void> execute(const nn::SharedPreparedModel& preparedModel,
- const Executor& executor, const V1_0::Request& request,
+ const V1_0::Request& request,
const sp<V1_0::IExecutionCallback>& callback) {
if (callback.get() == nullptr) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
}
- auto nnRequest = NN_TRY(convertInput(request));
+ const auto nnRequest = NN_TRY(convertInput(request));
- const std::any resource = preparedModel->getUnderlyingResource();
- if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
- CHECK(*model != nullptr);
- NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+ auto result = preparedModel->execute(nnRequest, nn::MeasureTiming::NO, {}, {}, {}, {});
+
+ if (!result.ok() && result.error().code == nn::ErrorStatus::INVALID_ARGUMENT) {
+ const auto& [message, code, outputShapes] = result.error();
+ return nn::error(code) << message;
}
- Task task = [preparedModel, nnRequest = std::move(nnRequest), callback] {
- auto result = preparedModel->execute(nnRequest, nn::MeasureTiming::NO, {}, {}, {}, {});
- notify(callback.get(), std::move(result));
- };
- executor(std::move(task), {});
-
+ notify(callback.get(), std::move(result));
return {};
}
nn::GeneralResult<void> execute_1_2(const nn::SharedPreparedModel& preparedModel,
- const Executor& executor, const V1_0::Request& request,
- V1_2::MeasureTiming measure,
+ const V1_0::Request& request, V1_2::MeasureTiming measure,
const sp<V1_2::IExecutionCallback>& callback) {
if (callback.get() == nullptr) {
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
}
- auto nnRequest = NN_TRY(convertInput(request));
+ const auto nnRequest = NN_TRY(convertInput(request));
const auto nnMeasure = NN_TRY(convertInput(measure));
- const std::any resource = preparedModel->getUnderlyingResource();
- if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
- CHECK(*model != nullptr);
- NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+ auto result = preparedModel->execute(nnRequest, nnMeasure, {}, {}, {}, {});
+
+ if (!result.ok() && result.error().code == nn::ErrorStatus::INVALID_ARGUMENT) {
+ const auto& [message, code, outputShapes] = result.error();
+ return nn::error(code) << message;
}
- Task task = [preparedModel, nnRequest = std::move(nnRequest), nnMeasure, callback] {
- auto result = preparedModel->execute(nnRequest, nnMeasure, {}, {}, {}, {});
- notify(callback.get(), std::move(result));
- };
- executor(std::move(task), {});
-
+ notify(callback.get(), std::move(result));
return {};
}
nn::GeneralResult<void> execute_1_3(const nn::SharedPreparedModel& preparedModel,
- const Executor& executor, const V1_3::Request& request,
- V1_2::MeasureTiming measure,
+ const V1_3::Request& request, V1_2::MeasureTiming measure,
const V1_3::OptionalTimePoint& deadline,
const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
const sp<V1_3::IExecutionCallback>& callback) {
@@ -203,25 +184,20 @@
return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
}
- auto nnRequest = NN_TRY(convertInput(request));
+ const auto nnRequest = NN_TRY(convertInput(request));
const auto nnMeasure = NN_TRY(convertInput(measure));
const auto nnDeadline = NN_TRY(convertInput(deadline));
const auto nnLoopTimeoutDuration = NN_TRY(convertInput(loopTimeoutDuration));
- const std::any resource = preparedModel->getUnderlyingResource();
- if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
- CHECK(*model != nullptr);
- NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+ auto result =
+ preparedModel->execute(nnRequest, nnMeasure, nnDeadline, nnLoopTimeoutDuration, {}, {});
+
+ if (!result.ok() && result.error().code == nn::ErrorStatus::INVALID_ARGUMENT) {
+ const auto& [message, code, outputShapes] = result.error();
+ return nn::error(code) << message;
}
- Task task = [preparedModel, nnRequest = std::move(nnRequest), nnMeasure, nnDeadline,
- nnLoopTimeoutDuration, callback] {
- auto result = preparedModel->execute(nnRequest, nnMeasure, nnDeadline,
- nnLoopTimeoutDuration, {}, {});
- notify(callback.get(), std::move(result));
- };
- executor(std::move(task), nnDeadline);
-
+ notify(callback.get(), std::move(result));
return {};
}
@@ -304,10 +280,9 @@
} // namespace
-PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor)
- : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)) {
+PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel)
+ : kPreparedModel(std::move(preparedModel)) {
CHECK(kPreparedModel != nullptr);
- CHECK(kExecutor != nullptr);
}
nn::SharedPreparedModel PreparedModel::getUnderlyingPreparedModel() const {
@@ -316,7 +291,7 @@
Return<V1_0::ErrorStatus> PreparedModel::execute(const V1_0::Request& request,
const sp<V1_0::IExecutionCallback>& callback) {
- auto result = adapter::execute(kPreparedModel, kExecutor, request, callback);
+ auto result = adapter::execute(kPreparedModel, request, callback);
if (!result.has_value()) {
auto [message, code] = std::move(result).error();
LOG(ERROR) << "adapter::PreparedModel::execute failed with " << code << ": " << message;
@@ -329,7 +304,7 @@
Return<V1_0::ErrorStatus> PreparedModel::execute_1_2(const V1_0::Request& request,
V1_2::MeasureTiming measure,
const sp<V1_2::IExecutionCallback>& callback) {
- auto result = adapter::execute_1_2(kPreparedModel, kExecutor, request, measure, callback);
+ auto result = adapter::execute_1_2(kPreparedModel, request, measure, callback);
if (!result.has_value()) {
auto [message, code] = std::move(result).error();
LOG(ERROR) << "adapter::PreparedModel::execute_1_2 failed with " << code << ": " << message;
@@ -344,7 +319,7 @@
const V1_3::OptionalTimePoint& deadline,
const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
const sp<V1_3::IExecutionCallback>& callback) {
- auto result = adapter::execute_1_3(kPreparedModel, kExecutor, request, measure, deadline,
+ auto result = adapter::execute_1_3(kPreparedModel, request, measure, deadline,
loopTimeoutDuration, callback);
if (!result.has_value()) {
auto [message, code] = std::move(result).error();
@@ -405,8 +380,8 @@
cb(V1_2::utils::convert(code).value(), nullptr);
return Void();
}
- auto burstContext = std::move(result).value();
- cb(V1_0::ErrorStatus::NONE, std::move(burstContext));
+ const auto burstContext = std::move(result).value();
+ cb(V1_0::ErrorStatus::NONE, burstContext);
return Void();
}