Implement NNAPI canonical interfaces
This CL implements the canonical IDevice, IPreparedModel, and IBuffer
interfaces for the 1.0, 1.1, 1.2, and 1.3 NN HIDL HAL interfaces.
Further, it introduces "Resilient" adapter interfaces to automatically
retrieve a handle to a recovered interface object after it has died and
rebooted.
This CL also updates the conversion code from returning nn::Result to
nn::GeneralResult, which includes a ErrorStatus code in the case of an
error.
Finally, this CL introduces a new static library
neuralnetworks_utils_hal_service which consists of a single function
::android::nn::hal::getDevices which can be used by the NNAPI runtime to
retrieve the HIDL services without knowing the underlying HIDL types.
Bug: 160668438
Test: mma
Test: NeuralNetworksTest_static
Change-Id: Iec6ae739df196b4034ffb35ea76781fd541ffec3
Merged-In: Iec6ae739df196b4034ffb35ea76781fd541ffec3
(cherry picked from commit 3670c385c4b12aef975ab67e5d2b0f5fe79134c2)
diff --git a/neuralnetworks/1.0/utils/Android.bp b/neuralnetworks/1.0/utils/Android.bp
index 57a052f..4d61fc0 100644
--- a/neuralnetworks/1.0/utils/Android.bp
+++ b/neuralnetworks/1.0/utils/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal/1.0/"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
"neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Callbacks.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Callbacks.h
new file mode 100644
index 0000000..65b75e5
--- /dev/null
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Callbacks.h
@@ -0,0 +1,67 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_CALLBACKS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+class PreparedModelCallback final : public IPreparedModelCallback,
+ public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::GeneralResult<nn::SharedPreparedModel>;
+
+ Return<void> notify(ErrorStatus status, const sp<IPreparedModel>& preparedModel) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+class ExecutionCallback final : public IExecutionCallback, public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+ Return<void> notify(ErrorStatus status) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_CALLBACKS_H
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
index 8ad98cb..fb77cb2 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Conversions.h
@@ -24,42 +24,44 @@
namespace android::nn {
-Result<OperandType> convert(const hal::V1_0::OperandType& operandType);
-Result<OperationType> convert(const hal::V1_0::OperationType& operationType);
-Result<Operand::LifeTime> convert(const hal::V1_0::OperandLifeTime& lifetime);
-Result<DeviceStatus> convert(const hal::V1_0::DeviceStatus& deviceStatus);
-Result<Capabilities::PerformanceInfo> convert(const hal::V1_0::PerformanceInfo& performanceInfo);
-Result<Capabilities> convert(const hal::V1_0::Capabilities& capabilities);
-Result<DataLocation> convert(const hal::V1_0::DataLocation& location);
-Result<Operand> convert(const hal::V1_0::Operand& operand);
-Result<Operation> convert(const hal::V1_0::Operation& operation);
-Result<Model::OperandValues> convert(const hardware::hidl_vec<uint8_t>& operandValues);
-Result<Memory> convert(const hardware::hidl_memory& memory);
-Result<Model> convert(const hal::V1_0::Model& model);
-Result<Request::Argument> convert(const hal::V1_0::RequestArgument& requestArgument);
-Result<Request> convert(const hal::V1_0::Request& request);
-Result<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status);
+GeneralResult<OperandType> convert(const hal::V1_0::OperandType& operandType);
+GeneralResult<OperationType> convert(const hal::V1_0::OperationType& operationType);
+GeneralResult<Operand::LifeTime> convert(const hal::V1_0::OperandLifeTime& lifetime);
+GeneralResult<DeviceStatus> convert(const hal::V1_0::DeviceStatus& deviceStatus);
+GeneralResult<Capabilities::PerformanceInfo> convert(
+ const hal::V1_0::PerformanceInfo& performanceInfo);
+GeneralResult<Capabilities> convert(const hal::V1_0::Capabilities& capabilities);
+GeneralResult<DataLocation> convert(const hal::V1_0::DataLocation& location);
+GeneralResult<Operand> convert(const hal::V1_0::Operand& operand);
+GeneralResult<Operation> convert(const hal::V1_0::Operation& operation);
+GeneralResult<Model::OperandValues> convert(const hardware::hidl_vec<uint8_t>& operandValues);
+GeneralResult<Memory> convert(const hardware::hidl_memory& memory);
+GeneralResult<Model> convert(const hal::V1_0::Model& model);
+GeneralResult<Request::Argument> convert(const hal::V1_0::RequestArgument& requestArgument);
+GeneralResult<Request> convert(const hal::V1_0::Request& request);
+GeneralResult<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status);
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_0::utils {
-nn::Result<OperandType> convert(const nn::OperandType& operandType);
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime);
-nn::Result<DeviceStatus> convert(const nn::DeviceStatus& deviceStatus);
-nn::Result<PerformanceInfo> convert(const nn::Capabilities::PerformanceInfo& performanceInfo);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<DataLocation> convert(const nn::DataLocation& location);
-nn::Result<Operand> convert(const nn::Operand& operand);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues);
-nn::Result<hidl_memory> convert(const nn::Memory& memory);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<RequestArgument> convert(const nn::Request::Argument& requestArgument);
-nn::Result<hidl_memory> convert(const nn::Request::MemoryPool& memoryPool);
-nn::Result<Request> convert(const nn::Request& request);
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& status);
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime);
+nn::GeneralResult<DeviceStatus> convert(const nn::DeviceStatus& deviceStatus);
+nn::GeneralResult<PerformanceInfo> convert(
+ const nn::Capabilities::PerformanceInfo& performanceInfo);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<DataLocation> convert(const nn::DataLocation& location);
+nn::GeneralResult<Operand> convert(const nn::Operand& operand);
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues);
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<RequestArgument> convert(const nn::Request::Argument& requestArgument);
+nn::GeneralResult<hidl_memory> convert(const nn::Request::MemoryPool& memoryPool);
+nn::GeneralResult<Request> convert(const nn::Request& request);
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& status);
} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Device.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Device.h
new file mode 100644
index 0000000..4403a57
--- /dev/null
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Device.h
@@ -0,0 +1,87 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.0/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+class Device final : public nn::IDevice {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+ sp<V1_0::IDevice> device);
+
+ Device(PrivateConstructorTag tag, std::string name, nn::Capabilities capabilities,
+ sp<V1_0::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ const std::string kName;
+ const std::string kVersionString = "UNKNOWN";
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ const sp<V1_0::IDevice> kDevice;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_DEVICE_H
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h
new file mode 100644
index 0000000..31f366d
--- /dev/null
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h
@@ -0,0 +1,64 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_PREPARED_MODEL_H
+
+#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+class PreparedModel final : public nn::IPreparedModel {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const PreparedModel>> create(
+ sp<V1_0::IPreparedModel> preparedModel);
+
+ PreparedModel(PrivateConstructorTag tag, sp<V1_0::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+ std::any getUnderlyingResource() const override;
+
+ private:
+ const sp<V1_0::IPreparedModel> kPreparedModel;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_PREPARED_MODEL_H
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Service.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Service.h
new file mode 100644
index 0000000..11fbb9e
--- /dev/null
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
index ec8da06..baa2b95 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Utils.h
@@ -22,6 +22,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.0/types.h>
#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
@@ -31,10 +32,14 @@
template <typename Type>
nn::Result<void> validate(const Type& halObject) {
- const auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeCanonical = nn::convert(halObject);
+ if (!maybeCanonical.has_value()) {
+ return nn::error() << maybeCanonical.error().message;
+ }
+ const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return {};
}
@@ -51,9 +56,14 @@
template <typename Type>
decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeVersion = nn::validate(canonical);
+ if (!maybeVersion.has_value()) {
+ return nn::error() << maybeVersion.error();
+ }
+ const auto version = maybeVersion.value();
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return canonical;
}
diff --git a/neuralnetworks/1.0/utils/src/Callbacks.cpp b/neuralnetworks/1.0/utils/src/Callbacks.cpp
new file mode 100644
index 0000000..f286bcc
--- /dev/null
+++ b/neuralnetworks/1.0/utils/src/Callbacks.cpp
@@ -0,0 +1,97 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Callbacks.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+namespace {
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<IPreparedModel>& preparedModel) {
+ return NN_TRY(utils::PreparedModel::create(preparedModel));
+}
+
+} // namespace
+
+Return<void> PreparedModelCallback::notify(ErrorStatus status,
+ const sp<IPreparedModel>& preparedModel) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+void PreparedModelCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+PreparedModelCallback::Data PreparedModelCallback::get() {
+ return mData.take();
+}
+
+void PreparedModelCallback::notifyInternal(PreparedModelCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+// ExecutionCallback methods begin here
+
+Return<void> ExecutionCallback::notify(ErrorStatus status) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal({});
+ }
+ return Void();
+}
+
+void ExecutionCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+ExecutionCallback::Data ExecutionCallback::get() {
+ return mData.take();
+}
+
+void ExecutionCallback::notifyInternal(ExecutionCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.0/utils/src/Conversions.cpp b/neuralnetworks/1.0/utils/src/Conversions.cpp
index 4a58f3b..f301065 100644
--- a/neuralnetworks/1.0/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.0/utils/src/Conversions.cpp
@@ -52,7 +52,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
std::vector<ConvertOutput<Type>> canonical;
canonical.reserve(arguments.size());
for (const auto& argument : arguments) {
@@ -63,30 +63,31 @@
} // anonymous namespace
-Result<OperandType> convert(const hal::V1_0::OperandType& operandType) {
+GeneralResult<OperandType> convert(const hal::V1_0::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-Result<OperationType> convert(const hal::V1_0::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_0::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-Result<Operand::LifeTime> convert(const hal::V1_0::OperandLifeTime& lifetime) {
+GeneralResult<Operand::LifeTime> convert(const hal::V1_0::OperandLifeTime& lifetime) {
return static_cast<Operand::LifeTime>(lifetime);
}
-Result<DeviceStatus> convert(const hal::V1_0::DeviceStatus& deviceStatus) {
+GeneralResult<DeviceStatus> convert(const hal::V1_0::DeviceStatus& deviceStatus) {
return static_cast<DeviceStatus>(deviceStatus);
}
-Result<Capabilities::PerformanceInfo> convert(const hal::V1_0::PerformanceInfo& performanceInfo) {
+GeneralResult<Capabilities::PerformanceInfo> convert(
+ const hal::V1_0::PerformanceInfo& performanceInfo) {
return Capabilities::PerformanceInfo{
.execTime = performanceInfo.execTime,
.powerUsage = performanceInfo.powerUsage,
};
}
-Result<Capabilities> convert(const hal::V1_0::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_0::Capabilities& capabilities) {
const auto quantized8Performance = NN_TRY(convert(capabilities.quantized8Performance));
const auto float32Performance = NN_TRY(convert(capabilities.float32Performance));
@@ -100,7 +101,7 @@
};
}
-Result<DataLocation> convert(const hal::V1_0::DataLocation& location) {
+GeneralResult<DataLocation> convert(const hal::V1_0::DataLocation& location) {
return DataLocation{
.poolIndex = location.poolIndex,
.offset = location.offset,
@@ -108,7 +109,7 @@
};
}
-Result<Operand> convert(const hal::V1_0::Operand& operand) {
+GeneralResult<Operand> convert(const hal::V1_0::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -119,7 +120,7 @@
};
}
-Result<Operation> convert(const hal::V1_0::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_0::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -127,15 +128,15 @@
};
}
-Result<Model::OperandValues> convert(const hidl_vec<uint8_t>& operandValues) {
+GeneralResult<Model::OperandValues> convert(const hidl_vec<uint8_t>& operandValues) {
return Model::OperandValues(operandValues.data(), operandValues.size());
}
-Result<Memory> convert(const hidl_memory& memory) {
+GeneralResult<Memory> convert(const hidl_memory& memory) {
return createSharedMemoryFromHidlMemory(memory);
}
-Result<Model> convert(const hal::V1_0::Model& model) {
+GeneralResult<Model> convert(const hal::V1_0::Model& model) {
auto operations = NN_TRY(convert(model.operations));
// Verify number of consumers.
@@ -144,9 +145,9 @@
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
- return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
- << numberOfConsumers[i] << " but found "
- << model.operands[i].numberOfConsumers;
+ return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
+ << "Invalid numberOfConsumers for operand " << i << ", expected "
+ << numberOfConsumers[i] << " but found " << model.operands[i].numberOfConsumers;
}
}
@@ -164,7 +165,7 @@
};
}
-Result<Request::Argument> convert(const hal::V1_0::RequestArgument& argument) {
+GeneralResult<Request::Argument> convert(const hal::V1_0::RequestArgument& argument) {
const auto lifetime = argument.hasNoValue ? Request::Argument::LifeTime::NO_VALUE
: Request::Argument::LifeTime::POOL;
return Request::Argument{
@@ -174,7 +175,7 @@
};
}
-Result<Request> convert(const hal::V1_0::Request& request) {
+GeneralResult<Request> convert(const hal::V1_0::Request& request) {
auto memories = NN_TRY(convert(request.pools));
std::vector<Request::MemoryPool> pools;
pools.reserve(memories.size());
@@ -187,7 +188,7 @@
};
}
-Result<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status) {
+GeneralResult<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status) {
switch (status) {
case hal::V1_0::ErrorStatus::NONE:
case hal::V1_0::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -196,7 +197,8 @@
case hal::V1_0::ErrorStatus::INVALID_ARGUMENT:
return static_cast<ErrorStatus>(status);
}
- return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+ return NN_ERROR(ErrorStatus::GENERAL_FAILURE)
+ << "Invalid ErrorStatus " << underlyingType(status);
}
} // namespace android::nn
@@ -208,7 +210,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
hidl_vec<ConvertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(utils::convert(arguments[i]));
@@ -218,33 +220,35 @@
} // anonymous namespace
-nn::Result<OperandType> convert(const nn::OperandType& operandType) {
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime) {
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime) {
if (lifetime == nn::Operand::LifeTime::POINTER) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
return static_cast<OperandLifeTime>(lifetime);
}
-nn::Result<DeviceStatus> convert(const nn::DeviceStatus& deviceStatus) {
+nn::GeneralResult<DeviceStatus> convert(const nn::DeviceStatus& deviceStatus) {
return static_cast<DeviceStatus>(deviceStatus);
}
-nn::Result<PerformanceInfo> convert(const nn::Capabilities::PerformanceInfo& performanceInfo) {
+nn::GeneralResult<PerformanceInfo> convert(
+ const nn::Capabilities::PerformanceInfo& performanceInfo) {
return PerformanceInfo{
.execTime = performanceInfo.execTime,
.powerUsage = performanceInfo.powerUsage,
};
}
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
return Capabilities{
.float32Performance = NN_TRY(convert(
capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
@@ -253,7 +257,7 @@
};
}
-nn::Result<DataLocation> convert(const nn::DataLocation& location) {
+nn::GeneralResult<DataLocation> convert(const nn::DataLocation& location) {
return DataLocation{
.poolIndex = location.poolIndex,
.offset = location.offset,
@@ -261,7 +265,7 @@
};
}
-nn::Result<Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<Operand> convert(const nn::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -273,7 +277,7 @@
};
}
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -281,20 +285,21 @@
};
}
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
return hidl_vec<uint8_t>(operandValues.data(), operandValues.data() + operandValues.size());
}
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
const auto hidlMemory = hidl_memory(memory.name, memory.handle->handle(), memory.size);
// Copy memory to force the native_handle_t to be copied.
auto copiedMemory = hidlMemory;
return copiedMemory;
}
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
- return NN_ERROR() << "Mdoel cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Mdoel cannot be converted because it contains pointer-based memory";
}
auto operands = NN_TRY(convert(model.main.operands));
@@ -317,9 +322,10 @@
};
}
-nn::Result<RequestArgument> convert(const nn::Request::Argument& requestArgument) {
+nn::GeneralResult<RequestArgument> convert(const nn::Request::Argument& requestArgument) {
if (requestArgument.lifetime == nn::Request::Argument::LifeTime::POINTER) {
- return NN_ERROR() << "Request cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Request cannot be converted because it contains pointer-based memory";
}
const bool hasNoValue = requestArgument.lifetime == nn::Request::Argument::LifeTime::NO_VALUE;
return RequestArgument{
@@ -329,13 +335,14 @@
};
}
-nn::Result<hidl_memory> convert(const nn::Request::MemoryPool& memoryPool) {
+nn::GeneralResult<hidl_memory> convert(const nn::Request::MemoryPool& memoryPool) {
return convert(std::get<nn::Memory>(memoryPool));
}
-nn::Result<Request> convert(const nn::Request& request) {
+nn::GeneralResult<Request> convert(const nn::Request& request) {
if (!hal::utils::hasNoPointerData(request)) {
- return NN_ERROR() << "Request cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Request cannot be converted because it contains pointer-based memory";
}
return Request{
@@ -345,7 +352,7 @@
};
}
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& status) {
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& status) {
switch (status) {
case nn::ErrorStatus::NONE:
case nn::ErrorStatus::DEVICE_UNAVAILABLE:
diff --git a/neuralnetworks/1.0/utils/src/Device.cpp b/neuralnetworks/1.0/utils/src/Device.cpp
new file mode 100644
index 0000000..8292f17
--- /dev/null
+++ b/neuralnetworks/1.0/utils/src/Device.cpp
@@ -0,0 +1,199 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Device.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/IDevice.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+namespace {
+
+nn::GeneralResult<nn::Capabilities> initCapabilities(V1_0::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<nn::Capabilities> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ const auto cb = [&result](ErrorStatus status, const Capabilities& capabilities) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getCapabilities failed with " << toString(status);
+ } else {
+ result = validatedConvertToCanonical(capabilities);
+ }
+ };
+
+ const auto ret = device->getCapabilities(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+ sp<V1_0::IDevice> device) {
+ if (name.empty()) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_0::utils::Device::create must have non-empty name";
+ }
+ if (device == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_0::utils::Device::create must have non-null device";
+ }
+
+ auto capabilities = NN_TRY(initCapabilities(device.get()));
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+ return std::make_shared<const Device>(PrivateConstructorTag{}, std::move(name),
+ std::move(capabilities), std::move(device),
+ std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, nn::Capabilities capabilities,
+ sp<V1_0::IDevice> device, hal::utils::DeathHandler deathHandler)
+ : kName(std::move(name)),
+ kCapabilities(std::move(capabilities)),
+ kDevice(std::move(device)),
+ kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+ return kName;
+}
+
+const std::string& Device::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+ return nn::Version::ANDROID_OC_MR1;
+}
+
+nn::DeviceType Device::getType() const {
+ return nn::DeviceType::OTHER;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+ return std::make_pair(/*numModelCache=*/0, /*numDataCache=*/0);
+}
+
+nn::GeneralResult<void> Device::wait() const {
+ const auto ret = kDevice->ping();
+ return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result, &model](ErrorStatus status, const hidl_vec<bool>& supportedOperations) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "getSupportedOperations failed with " << toString(status);
+ } else if (supportedOperations.size() != model.main.operations.size()) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "getSupportedOperations returned vector of size "
+ << supportedOperations.size() << " but expected "
+ << model.main.operations.size();
+ } else {
+ result = supportedOperations;
+ }
+ };
+
+ const auto ret = kDevice->getSupportedOperations(hidlModel, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference /*preference*/, nn::Priority /*priority*/,
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& /*modelCache*/,
+ const std::vector<nn::NativeHandle>& /*dataCache*/, const nn::CacheToken& /*token*/) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModel(hidlModel, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModel failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& /*modelCache*/,
+ const std::vector<nn::NativeHandle>& /*dataCache*/, const nn::CacheToken& /*token*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::prepareModelFromCache not supported on 1.0 HAL service";
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+ const nn::BufferDesc& /*desc*/,
+ const std::vector<nn::SharedPreparedModel>& /*preparedModels*/,
+ const std::vector<nn::BufferRole>& /*inputRoles*/,
+ const std::vector<nn::BufferRole>& /*outputRoles*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::allocate not supported on 1.0 HAL service";
+}
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.0/utils/src/PreparedModel.cpp b/neuralnetworks/1.0/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..11ccbe3
--- /dev/null
+++ b/neuralnetworks/1.0/utils/src/PreparedModel.cpp
@@ -0,0 +1,100 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+ sp<V1_0::IPreparedModel> preparedModel) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_0::utils::PreparedModel::create must have non-null preparedModel";
+ }
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+ return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_0::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler)
+ : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+ const nn::Request& request, nn::MeasureTiming /*measure*/,
+ const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+ const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+
+ const auto cb = sp<ExecutionCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kPreparedModel->execute(hidlRequest, cb);
+ const auto status =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "execute failed with " << toString(status);
+ }
+
+ auto result = NN_TRY(cb->get());
+ NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(
+ const nn::Request& /*request*/, const std::vector<nn::SyncFence>& /*waitFor*/,
+ nn::MeasureTiming /*measure*/, const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/,
+ const nn::OptionalTimeoutDuration& /*timeoutDurationAfterFence*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IPreparedModel::executeFenced is not supported on 1.0 HAL service";
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+ sp<V1_0::IPreparedModel> resource = kPreparedModel;
+ return resource;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.0/utils/src/Service.cpp b/neuralnetworks/1.0/utils/src/Service.cpp
new file mode 100644
index 0000000..ec28b1d
--- /dev/null
+++ b/neuralnetworks/1.0/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_0::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+ hal::utils::ResilientDevice::Factory makeDevice =
+ [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+ auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+ if (service == nullptr) {
+ return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+ }
+ return Device::create(name, std::move(service));
+ };
+
+ return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.1/utils/Android.bp b/neuralnetworks/1.1/utils/Android.bp
index 85a32c5..909575b 100644
--- a/neuralnetworks/1.1/utils/Android.bp
+++ b/neuralnetworks/1.1/utils/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal/1.1/"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
"neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h
index d0c5397..16ddd53 100644
--- a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Conversions.h
@@ -24,21 +24,22 @@
namespace android::nn {
-Result<OperationType> convert(const hal::V1_1::OperationType& operationType);
-Result<Capabilities> convert(const hal::V1_1::Capabilities& capabilities);
-Result<Operation> convert(const hal::V1_1::Operation& operation);
-Result<Model> convert(const hal::V1_1::Model& model);
-Result<ExecutionPreference> convert(const hal::V1_1::ExecutionPreference& executionPreference);
+GeneralResult<OperationType> convert(const hal::V1_1::OperationType& operationType);
+GeneralResult<Capabilities> convert(const hal::V1_1::Capabilities& capabilities);
+GeneralResult<Operation> convert(const hal::V1_1::Operation& operation);
+GeneralResult<Model> convert(const hal::V1_1::Model& model);
+GeneralResult<ExecutionPreference> convert(
+ const hal::V1_1::ExecutionPreference& executionPreference);
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_1::utils {
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference);
} // namespace android::hardware::neuralnetworks::V1_1::utils
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Device.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Device.h
new file mode 100644
index 0000000..f55ac6c
--- /dev/null
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Device.h
@@ -0,0 +1,87 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.1/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+
+class Device final : public nn::IDevice {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+ sp<V1_1::IDevice> device);
+
+ Device(PrivateConstructorTag tag, std::string name, nn::Capabilities capabilities,
+ sp<V1_1::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ const std::string kName;
+ const std::string kVersionString = "UNKNOWN";
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ const sp<V1_1::IDevice> kDevice;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_1::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_DEVICE_H
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Service.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Service.h
new file mode 100644
index 0000000..a3ad3cf
--- /dev/null
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+} // namespace android::hardware::neuralnetworks::V1_1::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_1_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
index 6f9aa60..0fee628 100644
--- a/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
+++ b/neuralnetworks/1.1/utils/include/nnapi/hal/1.1/Utils.h
@@ -22,6 +22,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.1/types.h>
#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
#include <nnapi/hal/1.0/Conversions.h>
@@ -33,10 +34,14 @@
template <typename Type>
nn::Result<void> validate(const Type& halObject) {
- const auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeCanonical = nn::convert(halObject);
+ if (!maybeCanonical.has_value()) {
+ return nn::error() << maybeCanonical.error().message;
+ }
+ const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return {};
}
@@ -53,9 +58,14 @@
template <typename Type>
decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeVersion = nn::validate(canonical);
+ if (!maybeVersion.has_value()) {
+ return nn::error() << maybeVersion.error();
+ }
+ const auto version = maybeVersion.value();
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return canonical;
}
diff --git a/neuralnetworks/1.1/utils/src/Conversions.cpp b/neuralnetworks/1.1/utils/src/Conversions.cpp
index 7fee16b..ffe0752 100644
--- a/neuralnetworks/1.1/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.1/utils/src/Conversions.cpp
@@ -42,7 +42,7 @@
using convertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-Result<std::vector<convertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<convertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
std::vector<convertOutput<Type>> canonical;
canonical.reserve(arguments.size());
for (const auto& argument : arguments) {
@@ -53,11 +53,11 @@
} // anonymous namespace
-Result<OperationType> convert(const hal::V1_1::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_1::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-Result<Capabilities> convert(const hal::V1_1::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_1::Capabilities& capabilities) {
const auto quantized8Performance = NN_TRY(convert(capabilities.quantized8Performance));
const auto float32Performance = NN_TRY(convert(capabilities.float32Performance));
const auto relaxedFloat32toFloat16Performance =
@@ -73,7 +73,7 @@
};
}
-Result<Operation> convert(const hal::V1_1::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_1::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -81,7 +81,7 @@
};
}
-Result<Model> convert(const hal::V1_1::Model& model) {
+GeneralResult<Model> convert(const hal::V1_1::Model& model) {
auto operations = NN_TRY(convert(model.operations));
// Verify number of consumers.
@@ -90,9 +90,9 @@
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
- return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
- << numberOfConsumers[i] << " but found "
- << model.operands[i].numberOfConsumers;
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid numberOfConsumers for operand " << i << ", expected "
+ << numberOfConsumers[i] << " but found " << model.operands[i].numberOfConsumers;
}
}
@@ -111,7 +111,8 @@
};
}
-Result<ExecutionPreference> convert(const hal::V1_1::ExecutionPreference& executionPreference) {
+GeneralResult<ExecutionPreference> convert(
+ const hal::V1_1::ExecutionPreference& executionPreference) {
return static_cast<ExecutionPreference>(executionPreference);
}
@@ -122,20 +123,20 @@
using utils::convert;
-nn::Result<V1_0::PerformanceInfo> convert(
+nn::GeneralResult<V1_0::PerformanceInfo> convert(
const nn::Capabilities::PerformanceInfo& performanceInfo) {
return V1_0::utils::convert(performanceInfo);
}
-nn::Result<V1_0::Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<V1_0::Operand> convert(const nn::Operand& operand) {
return V1_0::utils::convert(operand);
}
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
return V1_0::utils::convert(operandValues);
}
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
return V1_0::utils::convert(memory);
}
@@ -143,7 +144,7 @@
using convertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-nn::Result<hidl_vec<convertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<convertOutput<Type>>> convert(const std::vector<Type>& arguments) {
hidl_vec<convertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(convert(arguments[i]));
@@ -153,11 +154,11 @@
} // anonymous namespace
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
return Capabilities{
.float32Performance = NN_TRY(convert(
capabilities.operandPerformance.lookup(nn::OperandType::TENSOR_FLOAT32))),
@@ -168,7 +169,7 @@
};
}
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -176,9 +177,10 @@
};
}
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
- return NN_ERROR() << "Mdoel cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Mdoel cannot be converted because it contains pointer-based memory";
}
auto operands = NN_TRY(convert(model.main.operands));
@@ -202,7 +204,7 @@
};
}
-nn::Result<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference) {
+nn::GeneralResult<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference) {
return static_cast<ExecutionPreference>(executionPreference);
}
diff --git a/neuralnetworks/1.1/utils/src/Device.cpp b/neuralnetworks/1.1/utils/src/Device.cpp
new file mode 100644
index 0000000..03b0d6e
--- /dev/null
+++ b/neuralnetworks/1.1/utils/src/Device.cpp
@@ -0,0 +1,202 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Device.h"
+
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/IDevice.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+namespace {
+
+nn::GeneralResult<nn::Capabilities> initCapabilities(V1_1::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<nn::Capabilities> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, const Capabilities& capabilities) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getCapabilities_1_1 failed with " << toString(status);
+ } else {
+ result = validatedConvertToCanonical(capabilities);
+ }
+ };
+
+ const auto ret = device->getCapabilities_1_1(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+ sp<V1_1::IDevice> device) {
+ if (name.empty()) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_1::utils::Device::create must have non-empty name";
+ }
+ if (device == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_1::utils::Device::create must have non-null device";
+ }
+
+ auto capabilities = NN_TRY(initCapabilities(device.get()));
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+ return std::make_shared<const Device>(PrivateConstructorTag{}, std::move(name),
+ std::move(capabilities), std::move(device),
+ std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, nn::Capabilities capabilities,
+ sp<V1_1::IDevice> device, hal::utils::DeathHandler deathHandler)
+ : kName(std::move(name)),
+ kCapabilities(std::move(capabilities)),
+ kDevice(std::move(device)),
+ kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+ return kName;
+}
+
+const std::string& Device::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+ return nn::Version::ANDROID_P;
+}
+
+nn::DeviceType Device::getType() const {
+ return nn::DeviceType::UNKNOWN;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+ return std::make_pair(/*numModelCache=*/0, /*numDataCache=*/0);
+}
+
+nn::GeneralResult<void> Device::wait() const {
+ const auto ret = kDevice->ping();
+ return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result, &model](V1_0::ErrorStatus status,
+ const hidl_vec<bool>& supportedOperations) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "getSupportedOperations_1_1 failed with " << toString(status);
+ } else if (supportedOperations.size() != model.main.operations.size()) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "getSupportedOperations_1_1 returned vector of size "
+ << supportedOperations.size() << " but expected "
+ << model.main.operations.size();
+ } else {
+ result = supportedOperations;
+ }
+ };
+
+ const auto ret = kDevice->getSupportedOperations_1_1(hidlModel, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority /*priority*/,
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& /*modelCache*/,
+ const std::vector<nn::NativeHandle>& /*dataCache*/, const nn::CacheToken& /*token*/) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+ const auto hidlPreference = NN_TRY(convert(preference));
+
+ const auto cb = sp<V1_0::utils::PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModel_1_1(hidlModel, hidlPreference, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModel failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& /*modelCache*/,
+ const std::vector<nn::NativeHandle>& /*dataCache*/, const nn::CacheToken& /*token*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::prepareModelFromCache not supported on 1.1 HAL service";
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+ const nn::BufferDesc& /*desc*/,
+ const std::vector<nn::SharedPreparedModel>& /*preparedModels*/,
+ const std::vector<nn::BufferRole>& /*inputRoles*/,
+ const std::vector<nn::BufferRole>& /*outputRoles*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::allocate not supported on 1.1 HAL service";
+}
+
+} // namespace android::hardware::neuralnetworks::V1_1::utils
diff --git a/neuralnetworks/1.1/utils/src/Service.cpp b/neuralnetworks/1.1/utils/src/Service.cpp
new file mode 100644
index 0000000..e2d3240
--- /dev/null
+++ b/neuralnetworks/1.1/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_1::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+ hal::utils::ResilientDevice::Factory makeDevice =
+ [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+ auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+ if (service == nullptr) {
+ return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+ }
+ return Device::create(name, std::move(service));
+ };
+
+ return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_1::utils
diff --git a/neuralnetworks/1.2/utils/Android.bp b/neuralnetworks/1.2/utils/Android.bp
index a1dd3d0..22e8659 100644
--- a/neuralnetworks/1.2/utils/Android.bp
+++ b/neuralnetworks/1.2/utils/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal/1.2/"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
"neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Callbacks.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Callbacks.h
new file mode 100644
index 0000000..bc7d92a
--- /dev/null
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Callbacks.h
@@ -0,0 +1,76 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_CALLBACKS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+class PreparedModelCallback final : public IPreparedModelCallback,
+ public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::GeneralResult<nn::SharedPreparedModel>;
+
+ Return<void> notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status,
+ const sp<IPreparedModel>& preparedModel) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+class ExecutionCallback final : public IExecutionCallback, public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+ Return<void> notify(V1_0::ErrorStatus status) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status, const hidl_vec<OutputShape>& outputShapes,
+ const Timing& timing) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_CALLBACKS_H
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Conversions.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Conversions.h
index 81bf792..e6de011 100644
--- a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Conversions.h
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Conversions.h
@@ -24,62 +24,64 @@
namespace android::nn {
-Result<OperandType> convert(const hal::V1_2::OperandType& operandType);
-Result<OperationType> convert(const hal::V1_2::OperationType& operationType);
-Result<DeviceType> convert(const hal::V1_2::DeviceType& deviceType);
-Result<Capabilities> convert(const hal::V1_2::Capabilities& capabilities);
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<OperandType> convert(const hal::V1_2::OperandType& operandType);
+GeneralResult<OperationType> convert(const hal::V1_2::OperationType& operationType);
+GeneralResult<DeviceType> convert(const hal::V1_2::DeviceType& deviceType);
+GeneralResult<Capabilities> convert(const hal::V1_2::Capabilities& capabilities);
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_2::Capabilities::OperandPerformance& operandPerformance);
-Result<Operation> convert(const hal::V1_2::Operation& operation);
-Result<Operand::SymmPerChannelQuantParams> convert(
+GeneralResult<Operation> convert(const hal::V1_2::Operation& operation);
+GeneralResult<Operand::SymmPerChannelQuantParams> convert(
const hal::V1_2::SymmPerChannelQuantParams& symmPerChannelQuantParams);
-Result<Operand> convert(const hal::V1_2::Operand& operand);
-Result<Operand::ExtraParams> convert(const hal::V1_2::Operand::ExtraParams& extraParams);
-Result<Model> convert(const hal::V1_2::Model& model);
-Result<Model::ExtensionNameAndPrefix> convert(
+GeneralResult<Operand> convert(const hal::V1_2::Operand& operand);
+GeneralResult<Operand::ExtraParams> convert(const hal::V1_2::Operand::ExtraParams& extraParams);
+GeneralResult<Model> convert(const hal::V1_2::Model& model);
+GeneralResult<Model::ExtensionNameAndPrefix> convert(
const hal::V1_2::Model::ExtensionNameAndPrefix& extensionNameAndPrefix);
-Result<OutputShape> convert(const hal::V1_2::OutputShape& outputShape);
-Result<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming);
-Result<Timing> convert(const hal::V1_2::Timing& timing);
-Result<Extension> convert(const hal::V1_2::Extension& extension);
-Result<Extension::OperandTypeInformation> convert(
+GeneralResult<OutputShape> convert(const hal::V1_2::OutputShape& outputShape);
+GeneralResult<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming);
+GeneralResult<Timing> convert(const hal::V1_2::Timing& timing);
+GeneralResult<Extension> convert(const hal::V1_2::Extension& extension);
+GeneralResult<Extension::OperandTypeInformation> convert(
const hal::V1_2::Extension::OperandTypeInformation& operandTypeInformation);
-Result<NativeHandle> convert(const hardware::hidl_handle& handle);
+GeneralResult<NativeHandle> convert(const hardware::hidl_handle& handle);
-Result<std::vector<Extension>> convert(const hardware::hidl_vec<hal::V1_2::Extension>& extensions);
-Result<std::vector<NativeHandle>> convert(const hardware::hidl_vec<hardware::hidl_handle>& handles);
-Result<std::vector<OutputShape>> convert(
+GeneralResult<std::vector<Extension>> convert(
+ const hardware::hidl_vec<hal::V1_2::Extension>& extensions);
+GeneralResult<std::vector<NativeHandle>> convert(
+ const hardware::hidl_vec<hardware::hidl_handle>& handles);
+GeneralResult<std::vector<OutputShape>> convert(
const hardware::hidl_vec<hal::V1_2::OutputShape>& outputShapes);
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_2::utils {
-nn::Result<OperandType> convert(const nn::OperandType& operandType);
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<DeviceType> convert(const nn::DeviceType& deviceType);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<SymmPerChannelQuantParams> convert(
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<SymmPerChannelQuantParams> convert(
const nn::Operand::SymmPerChannelQuantParams& symmPerChannelQuantParams);
-nn::Result<Operand> convert(const nn::Operand& operand);
-nn::Result<Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<Model::ExtensionNameAndPrefix> convert(
+nn::GeneralResult<Operand> convert(const nn::Operand& operand);
+nn::GeneralResult<Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<Model::ExtensionNameAndPrefix> convert(
const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix);
-nn::Result<OutputShape> convert(const nn::OutputShape& outputShape);
-nn::Result<MeasureTiming> convert(const nn::MeasureTiming& measureTiming);
-nn::Result<Timing> convert(const nn::Timing& timing);
-nn::Result<Extension> convert(const nn::Extension& extension);
-nn::Result<Extension::OperandTypeInformation> convert(
+nn::GeneralResult<OutputShape> convert(const nn::OutputShape& outputShape);
+nn::GeneralResult<MeasureTiming> convert(const nn::MeasureTiming& measureTiming);
+nn::GeneralResult<Timing> convert(const nn::Timing& timing);
+nn::GeneralResult<Extension> convert(const nn::Extension& extension);
+nn::GeneralResult<Extension::OperandTypeInformation> convert(
const nn::Extension::OperandTypeInformation& operandTypeInformation);
-nn::Result<hidl_handle> convert(const nn::NativeHandle& handle);
+nn::GeneralResult<hidl_handle> convert(const nn::NativeHandle& handle);
-nn::Result<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions);
-nn::Result<hidl_vec<hidl_handle>> convert(const std::vector<nn::NativeHandle>& handles);
-nn::Result<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes);
+nn::GeneralResult<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions);
+nn::GeneralResult<hidl_vec<hidl_handle>> convert(const std::vector<nn::NativeHandle>& handles);
+nn::GeneralResult<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes);
} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Device.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Device.h
new file mode 100644
index 0000000..eb317b1
--- /dev/null
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Device.h
@@ -0,0 +1,98 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.2/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+nn::GeneralResult<std::string> initVersionString(V1_2::IDevice* device);
+nn::GeneralResult<nn::DeviceType> initDeviceType(V1_2::IDevice* device);
+nn::GeneralResult<std::vector<nn::Extension>> initExtensions(V1_2::IDevice* device);
+nn::GeneralResult<nn::Capabilities> initCapabilities(V1_2::IDevice* device);
+nn::GeneralResult<std::pair<uint32_t, uint32_t>> initNumberOfCacheFilesNeeded(
+ V1_2::IDevice* device);
+
+class Device final : public nn::IDevice {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+ sp<V1_2::IDevice> device);
+
+ Device(PrivateConstructorTag tag, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities, std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded,
+ sp<V1_2::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ const std::string kName;
+ const std::string kVersionString;
+ const nn::DeviceType kDeviceType;
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ const std::pair<uint32_t, uint32_t> kNumberOfCacheFilesNeeded;
+ const sp<V1_2::IDevice> kDevice;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_DEVICE_H
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h
new file mode 100644
index 0000000..65e1e8a
--- /dev/null
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h
@@ -0,0 +1,70 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_PREPARED_MODEL_H
+
+#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+class PreparedModel final : public nn::IPreparedModel {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const PreparedModel>> create(
+ sp<V1_2::IPreparedModel> preparedModel);
+
+ PreparedModel(PrivateConstructorTag tag, sp<V1_2::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+ std::any getUnderlyingResource() const override;
+
+ private:
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
+ const V1_0::Request& request, MeasureTiming measure) const;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeAsynchronously(
+ const V1_0::Request& request, MeasureTiming measure) const;
+
+ const sp<V1_2::IPreparedModel> kPreparedModel;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_PREPARED_MODEL_H
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Service.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Service.h
new file mode 100644
index 0000000..44f004f
--- /dev/null
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
index b1c2f1a..a9a6bae 100644
--- a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Utils.h
@@ -22,6 +22,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.2/types.h>
#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
#include <nnapi/hal/1.0/Conversions.h>
@@ -38,10 +39,14 @@
template <typename Type>
nn::Result<void> validate(const Type& halObject) {
- const auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeCanonical = nn::convert(halObject);
+ if (!maybeCanonical.has_value()) {
+ return nn::error() << maybeCanonical.error().message;
+ }
+ const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return {};
}
@@ -58,9 +63,14 @@
template <typename Type>
decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeVersion = nn::validate(canonical);
+ if (!maybeVersion.has_value()) {
+ return nn::error() << maybeVersion.error();
+ }
+ const auto version = maybeVersion.value();
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return canonical;
}
diff --git a/neuralnetworks/1.2/utils/src/Callbacks.cpp b/neuralnetworks/1.2/utils/src/Callbacks.cpp
new file mode 100644
index 0000000..cb739f0
--- /dev/null
+++ b/neuralnetworks/1.2/utils/src/Callbacks.cpp
@@ -0,0 +1,147 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Callbacks.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/1.0/PreparedModel.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+namespace {
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ return NN_TRY(V1_0::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<IPreparedModel>& preparedModel) {
+ return NN_TRY(utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResultsHelper(const hidl_vec<OutputShape>& outputShapes,
+ const Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResults(const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
+ return hal::utils::makeExecutionFailure(
+ convertExecutionGeneralResultsHelper(outputShapes, timing));
+}
+
+} // namespace
+
+Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
+ const sp<IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+void PreparedModelCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+PreparedModelCallback::Data PreparedModelCallback::get() {
+ return mData.take();
+}
+
+void PreparedModelCallback::notifyInternal(PreparedModelCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+// ExecutionCallback methods begin here
+
+Return<void> ExecutionCallback::notify(V1_0::ErrorStatus status) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal({});
+ }
+ return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_2(V1_0::ErrorStatus status,
+ const hidl_vec<OutputShape>& outputShapes,
+ const Timing& timing) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+ }
+ return Void();
+}
+
+void ExecutionCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+ExecutionCallback::Data ExecutionCallback::get() {
+ return mData.take();
+}
+
+void ExecutionCallback::notifyInternal(ExecutionCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.2/utils/src/Conversions.cpp b/neuralnetworks/1.2/utils/src/Conversions.cpp
index fed314b..378719a 100644
--- a/neuralnetworks/1.2/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.2/utils/src/Conversions.cpp
@@ -26,6 +26,7 @@
#include <nnapi/Types.h>
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
#include <algorithm>
#include <functional>
@@ -78,7 +79,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
std::vector<ConvertOutput<Type>> canonical;
canonical.reserve(arguments.size());
for (const auto& argument : arguments) {
@@ -88,25 +89,25 @@
}
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
return convertVec(arguments);
}
} // anonymous namespace
-Result<OperandType> convert(const hal::V1_2::OperandType& operandType) {
+GeneralResult<OperandType> convert(const hal::V1_2::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-Result<OperationType> convert(const hal::V1_2::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_2::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-Result<DeviceType> convert(const hal::V1_2::DeviceType& deviceType) {
+GeneralResult<DeviceType> convert(const hal::V1_2::DeviceType& deviceType) {
return static_cast<DeviceType>(deviceType);
}
-Result<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
const bool validOperandTypes = std::all_of(
capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
[](const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
@@ -114,7 +115,7 @@
return !maybeType.has_value() ? false : validOperandType(maybeType.value());
});
if (!validOperandTypes) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Invalid OperandType when converting OperandPerformance in Capabilities";
}
@@ -124,8 +125,9 @@
NN_TRY(convert(capabilities.relaxedFloat32toFloat16PerformanceTensor));
auto operandPerformance = NN_TRY(convert(capabilities.operandPerformance));
- auto table =
- NN_TRY(Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)));
+ auto table = NN_TRY(hal::utils::makeGeneralFailure(
+ Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+ nn::ErrorStatus::GENERAL_FAILURE));
return Capabilities{
.relaxedFloat32toFloat16PerformanceScalar = relaxedFloat32toFloat16PerformanceScalar,
@@ -134,7 +136,7 @@
};
}
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_2::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -142,7 +144,7 @@
};
}
-Result<Operation> convert(const hal::V1_2::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_2::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -150,7 +152,7 @@
};
}
-Result<Operand::SymmPerChannelQuantParams> convert(
+GeneralResult<Operand::SymmPerChannelQuantParams> convert(
const hal::V1_2::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
return Operand::SymmPerChannelQuantParams{
.scales = symmPerChannelQuantParams.scales,
@@ -158,7 +160,7 @@
};
}
-Result<Operand> convert(const hal::V1_2::Operand& operand) {
+GeneralResult<Operand> convert(const hal::V1_2::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -170,7 +172,7 @@
};
}
-Result<Operand::ExtraParams> convert(const hal::V1_2::Operand::ExtraParams& extraParams) {
+GeneralResult<Operand::ExtraParams> convert(const hal::V1_2::Operand::ExtraParams& extraParams) {
using Discriminator = hal::V1_2::Operand::ExtraParams::hidl_discriminator;
switch (extraParams.getDiscriminator()) {
case Discriminator::none:
@@ -180,11 +182,12 @@
case Discriminator::extension:
return extraParams.extension();
}
- return NN_ERROR() << "Unrecognized Operand::ExtraParams discriminator: "
- << underlyingType(extraParams.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Unrecognized Operand::ExtraParams discriminator: "
+ << underlyingType(extraParams.getDiscriminator());
}
-Result<Model> convert(const hal::V1_2::Model& model) {
+GeneralResult<Model> convert(const hal::V1_2::Model& model) {
auto operations = NN_TRY(convert(model.operations));
// Verify number of consumers.
@@ -193,9 +196,9 @@
CHECK(model.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < model.operands.size(); ++i) {
if (model.operands[i].numberOfConsumers != numberOfConsumers[i]) {
- return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
- << numberOfConsumers[i] << " but found "
- << model.operands[i].numberOfConsumers;
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid numberOfConsumers for operand " << i << ", expected "
+ << numberOfConsumers[i] << " but found " << model.operands[i].numberOfConsumers;
}
}
@@ -215,7 +218,7 @@
};
}
-Result<Model::ExtensionNameAndPrefix> convert(
+GeneralResult<Model::ExtensionNameAndPrefix> convert(
const hal::V1_2::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
return Model::ExtensionNameAndPrefix{
.name = extensionNameAndPrefix.name,
@@ -223,29 +226,29 @@
};
}
-Result<OutputShape> convert(const hal::V1_2::OutputShape& outputShape) {
+GeneralResult<OutputShape> convert(const hal::V1_2::OutputShape& outputShape) {
return OutputShape{
.dimensions = outputShape.dimensions,
.isSufficient = outputShape.isSufficient,
};
}
-Result<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming) {
+GeneralResult<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming) {
return static_cast<MeasureTiming>(measureTiming);
}
-Result<Timing> convert(const hal::V1_2::Timing& timing) {
+GeneralResult<Timing> convert(const hal::V1_2::Timing& timing) {
return Timing{.timeOnDevice = timing.timeOnDevice, .timeInDriver = timing.timeInDriver};
}
-Result<Extension> convert(const hal::V1_2::Extension& extension) {
+GeneralResult<Extension> convert(const hal::V1_2::Extension& extension) {
return Extension{
.name = extension.name,
.operandTypes = NN_TRY(convert(extension.operandTypes)),
};
}
-Result<Extension::OperandTypeInformation> convert(
+GeneralResult<Extension::OperandTypeInformation> convert(
const hal::V1_2::Extension::OperandTypeInformation& operandTypeInformation) {
return Extension::OperandTypeInformation{
.type = operandTypeInformation.type,
@@ -254,20 +257,21 @@
};
}
-Result<NativeHandle> convert(const hidl_handle& handle) {
+GeneralResult<NativeHandle> convert(const hidl_handle& handle) {
auto* cloned = native_handle_clone(handle.getNativeHandle());
return ::android::NativeHandle::create(cloned, /*ownsHandle=*/true);
}
-Result<std::vector<Extension>> convert(const hidl_vec<hal::V1_2::Extension>& extensions) {
+GeneralResult<std::vector<Extension>> convert(const hidl_vec<hal::V1_2::Extension>& extensions) {
return convertVec(extensions);
}
-Result<std::vector<NativeHandle>> convert(const hidl_vec<hidl_handle>& handles) {
+GeneralResult<std::vector<NativeHandle>> convert(const hidl_vec<hidl_handle>& handles) {
return convertVec(handles);
}
-Result<std::vector<OutputShape>> convert(const hidl_vec<hal::V1_2::OutputShape>& outputShapes) {
+GeneralResult<std::vector<OutputShape>> convert(
+ const hidl_vec<hal::V1_2::OutputShape>& outputShapes) {
return convertVec(outputShapes);
}
@@ -278,24 +282,24 @@
using utils::convert;
-nn::Result<V1_0::OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime) {
+nn::GeneralResult<V1_0::OperandLifeTime> convert(const nn::Operand::LifeTime& lifetime) {
return V1_0::utils::convert(lifetime);
}
-nn::Result<V1_0::PerformanceInfo> convert(
+nn::GeneralResult<V1_0::PerformanceInfo> convert(
const nn::Capabilities::PerformanceInfo& performanceInfo) {
return V1_0::utils::convert(performanceInfo);
}
-nn::Result<V1_0::DataLocation> convert(const nn::DataLocation& location) {
+nn::GeneralResult<V1_0::DataLocation> convert(const nn::DataLocation& location) {
return V1_0::utils::convert(location);
}
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
return V1_0::utils::convert(operandValues);
}
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
return V1_0::utils::convert(memory);
}
@@ -303,7 +307,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
hidl_vec<ConvertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(convert(arguments[i]));
@@ -312,22 +316,23 @@
}
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
return convertVec(arguments);
}
-nn::Result<Operand::ExtraParams> makeExtraParams(nn::Operand::NoParams /*noParams*/) {
+nn::GeneralResult<Operand::ExtraParams> makeExtraParams(nn::Operand::NoParams /*noParams*/) {
return Operand::ExtraParams{};
}
-nn::Result<Operand::ExtraParams> makeExtraParams(
+nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
const nn::Operand::SymmPerChannelQuantParams& channelQuant) {
Operand::ExtraParams ret;
ret.channelQuant(NN_TRY(convert(channelQuant)));
return ret;
}
-nn::Result<Operand::ExtraParams> makeExtraParams(const nn::Operand::ExtensionParams& extension) {
+nn::GeneralResult<Operand::ExtraParams> makeExtraParams(
+ const nn::Operand::ExtensionParams& extension) {
Operand::ExtraParams ret;
ret.extension(extension);
return ret;
@@ -335,28 +340,29 @@
} // anonymous namespace
-nn::Result<OperandType> convert(const nn::OperandType& operandType) {
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-nn::Result<DeviceType> convert(const nn::DeviceType& deviceType) {
+nn::GeneralResult<DeviceType> convert(const nn::DeviceType& deviceType) {
switch (deviceType) {
case nn::DeviceType::UNKNOWN:
- return NN_ERROR() << "Invalid DeviceType UNKNOWN";
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Invalid DeviceType UNKNOWN";
case nn::DeviceType::OTHER:
case nn::DeviceType::CPU:
case nn::DeviceType::GPU:
case nn::DeviceType::ACCELERATOR:
return static_cast<DeviceType>(deviceType);
}
- return NN_ERROR() << "Invalid DeviceType " << underlyingType(deviceType);
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid DeviceType " << underlyingType(deviceType);
}
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
std::copy_if(capabilities.operandPerformance.asVector().begin(),
@@ -375,7 +381,7 @@
};
}
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -383,7 +389,7 @@
};
}
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -391,7 +397,7 @@
};
}
-nn::Result<SymmPerChannelQuantParams> convert(
+nn::GeneralResult<SymmPerChannelQuantParams> convert(
const nn::Operand::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
return SymmPerChannelQuantParams{
.scales = symmPerChannelQuantParams.scales,
@@ -399,7 +405,7 @@
};
}
-nn::Result<Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<Operand> convert(const nn::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -412,13 +418,14 @@
};
}
-nn::Result<Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
+nn::GeneralResult<Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
return std::visit([](const auto& x) { return makeExtraParams(x); }, extraParams);
}
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
auto operands = NN_TRY(convert(model.main.operands));
@@ -443,7 +450,7 @@
};
}
-nn::Result<Model::ExtensionNameAndPrefix> convert(
+nn::GeneralResult<Model::ExtensionNameAndPrefix> convert(
const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
return Model::ExtensionNameAndPrefix{
.name = extensionNameAndPrefix.name,
@@ -451,27 +458,27 @@
};
}
-nn::Result<OutputShape> convert(const nn::OutputShape& outputShape) {
+nn::GeneralResult<OutputShape> convert(const nn::OutputShape& outputShape) {
return OutputShape{.dimensions = outputShape.dimensions,
.isSufficient = outputShape.isSufficient};
}
-nn::Result<MeasureTiming> convert(const nn::MeasureTiming& measureTiming) {
+nn::GeneralResult<MeasureTiming> convert(const nn::MeasureTiming& measureTiming) {
return static_cast<MeasureTiming>(measureTiming);
}
-nn::Result<Timing> convert(const nn::Timing& timing) {
+nn::GeneralResult<Timing> convert(const nn::Timing& timing) {
return Timing{.timeOnDevice = timing.timeOnDevice, .timeInDriver = timing.timeInDriver};
}
-nn::Result<Extension> convert(const nn::Extension& extension) {
+nn::GeneralResult<Extension> convert(const nn::Extension& extension) {
return Extension{
.name = extension.name,
.operandTypes = NN_TRY(convert(extension.operandTypes)),
};
}
-nn::Result<Extension::OperandTypeInformation> convert(
+nn::GeneralResult<Extension::OperandTypeInformation> convert(
const nn::Extension::OperandTypeInformation& operandTypeInformation) {
return Extension::OperandTypeInformation{
.type = operandTypeInformation.type,
@@ -480,22 +487,22 @@
};
}
-nn::Result<hidl_handle> convert(const nn::NativeHandle& handle) {
+nn::GeneralResult<hidl_handle> convert(const nn::NativeHandle& handle) {
const auto hidlHandle = hidl_handle(handle->handle());
// Copy memory to force the native_handle_t to be copied.
auto copiedHandle = hidlHandle;
return copiedHandle;
}
-nn::Result<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions) {
+nn::GeneralResult<hidl_vec<Extension>> convert(const std::vector<nn::Extension>& extensions) {
return convertVec(extensions);
}
-nn::Result<hidl_vec<hidl_handle>> convert(const std::vector<nn::NativeHandle>& handles) {
+nn::GeneralResult<hidl_vec<hidl_handle>> convert(const std::vector<nn::NativeHandle>& handles) {
return convertVec(handles);
}
-nn::Result<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes) {
+nn::GeneralResult<hidl_vec<OutputShape>> convert(const std::vector<nn::OutputShape>& outputShapes) {
return convertVec(outputShapes);
}
diff --git a/neuralnetworks/1.2/utils/src/Device.cpp b/neuralnetworks/1.2/utils/src/Device.cpp
new file mode 100644
index 0000000..ca236f1
--- /dev/null
+++ b/neuralnetworks/1.2/utils/src/Device.cpp
@@ -0,0 +1,318 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Device.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/IDevice.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.1/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+nn::GeneralResult<std::string> initVersionString(V1_2::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<std::string> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, const hidl_string& versionString) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getVersionString failed with " << toString(status);
+ } else {
+ result = versionString;
+ }
+ };
+
+ const auto ret = device->getVersionString(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::DeviceType> initDeviceType(V1_2::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<nn::DeviceType> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, DeviceType deviceType) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getDeviceType failed with " << toString(status);
+ } else {
+ result = nn::convert(deviceType);
+ }
+ };
+
+ const auto ret = device->getType(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<std::vector<nn::Extension>> initExtensions(V1_2::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<std::vector<nn::Extension>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, const hidl_vec<Extension>& extensions) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getExtensions failed with " << toString(status);
+ } else {
+ result = nn::convert(extensions);
+ }
+ };
+
+ const auto ret = device->getSupportedExtensions(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::Capabilities> initCapabilities(V1_2::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<nn::Capabilities> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, const Capabilities& capabilities) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getCapabilities_1_2 failed with " << toString(status);
+ } else {
+ result = validatedConvertToCanonical(capabilities);
+ }
+ };
+
+ const auto ret = device->getCapabilities_1_2(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<uint32_t, uint32_t>> initNumberOfCacheFilesNeeded(
+ V1_2::IDevice* device) {
+ CHECK(device != nullptr);
+
+ nn::GeneralResult<std::pair<uint32_t, uint32_t>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, uint32_t numModelCache,
+ uint32_t numDataCache) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "getNumberOfCacheFilesNeeded failed with " << toString(status);
+ } else {
+ result = std::make_pair(numModelCache, numDataCache);
+ }
+ };
+
+ const auto ret = device->getNumberOfCacheFilesNeeded(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+ sp<V1_2::IDevice> device) {
+ if (name.empty()) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_2::utils::Device::create must have non-empty name";
+ }
+ if (device == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_2::utils::Device::create must have non-null device";
+ }
+
+ auto versionString = NN_TRY(initVersionString(device.get()));
+ const auto deviceType = NN_TRY(initDeviceType(device.get()));
+ auto extensions = NN_TRY(initExtensions(device.get()));
+ auto capabilities = NN_TRY(initCapabilities(device.get()));
+ const auto numberOfCacheFilesNeeded = NN_TRY(initNumberOfCacheFilesNeeded(device.get()));
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+ return std::make_shared<const Device>(
+ PrivateConstructorTag{}, std::move(name), std::move(versionString), deviceType,
+ std::move(extensions), std::move(capabilities), numberOfCacheFilesNeeded,
+ std::move(device), std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities,
+ std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded, sp<V1_2::IDevice> device,
+ hal::utils::DeathHandler deathHandler)
+ : kName(std::move(name)),
+ kVersionString(std::move(versionString)),
+ kDeviceType(deviceType),
+ kExtensions(std::move(extensions)),
+ kCapabilities(std::move(capabilities)),
+ kNumberOfCacheFilesNeeded(numberOfCacheFilesNeeded),
+ kDevice(std::move(device)),
+ kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+ return kName;
+}
+
+const std::string& Device::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+ return nn::Version::ANDROID_Q;
+}
+
+nn::DeviceType Device::getType() const {
+ return kDeviceType;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+ return kNumberOfCacheFilesNeeded;
+}
+
+nn::GeneralResult<void> Device::wait() const {
+ const auto ret = kDevice->ping();
+ return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result, &model](V1_0::ErrorStatus status,
+ const hidl_vec<bool>& supportedOperations) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "getSupportedOperations_1_2 failed with " << toString(status);
+ } else if (supportedOperations.size() != model.main.operations.size()) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "getSupportedOperations_1_2 returned vector of size "
+ << supportedOperations.size() << " but expected "
+ << model.main.operations.size();
+ } else {
+ result = supportedOperations;
+ }
+ };
+
+ const auto ret = kDevice->getSupportedOperations_1_2(hidlModel, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority /*priority*/,
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+ const auto hidlPreference = NN_TRY(V1_1::utils::convert(preference));
+ const auto hidlModelCache = NN_TRY(convert(modelCache));
+ const auto hidlDataCache = NN_TRY(convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModel_1_2(hidlModel, hidlPreference, hidlModelCache,
+ hidlDataCache, hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModel_1_2 failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+ nn::OptionalTimePoint /*deadline*/, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ const auto hidlModelCache = NN_TRY(convert(modelCache));
+ const auto hidlDataCache = NN_TRY(convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModelFromCache(hidlModelCache, hidlDataCache, hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModelFromCache failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+ const nn::BufferDesc& /*desc*/,
+ const std::vector<nn::SharedPreparedModel>& /*preparedModels*/,
+ const std::vector<nn::BufferRole>& /*inputRoles*/,
+ const std::vector<nn::BufferRole>& /*outputRoles*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::allocate not supported on 1.2 HAL service";
+}
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.2/utils/src/PreparedModel.cpp b/neuralnetworks/1.2/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..ff9db21
--- /dev/null
+++ b/neuralnetworks/1.2/utils/src/PreparedModel.cpp
@@ -0,0 +1,161 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+namespace {
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionResultsHelper(const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
+ const hidl_vec<OutputShape>& outputShapes, const Timing& timing) {
+ return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+ sp<V1_2::IPreparedModel> preparedModel) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_2::utils::PreparedModel::create must have non-null preparedModel";
+ }
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+ return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_2::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler)
+ : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeSynchronously(const V1_0::Request& request, MeasureTiming measure) const {
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](V1_0::ErrorStatus status, const hidl_vec<OutputShape>& outputShapes,
+ const Timing& timing) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
+ } else {
+ result = convertExecutionResults(outputShapes, timing);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeSynchronously(request, measure, cb);
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+
+ return result;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeAsynchronously(const V1_0::Request& request, MeasureTiming measure) const {
+ const auto cb = sp<ExecutionCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kPreparedModel->execute_1_2(request, measure, cb);
+ const auto status =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "execute failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+ const auto hidlRequest =
+ NN_TRY(hal::utils::makeExecutionFailure(V1_0::utils::convert(requestInShared)));
+ const auto hidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const bool preferSynchronous = true;
+
+ // Execute synchronously if allowed.
+ if (preferSynchronous) {
+ result = executeSynchronously(hidlRequest, hidlMeasure);
+ }
+
+ // Run asymchronous execution if execution has not already completed.
+ if (!result.has_value()) {
+ result = executeAsynchronously(hidlRequest, hidlMeasure);
+ }
+
+ // Flush output buffers if suxcessful execution.
+ if (result.has_value()) {
+ NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+ }
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(
+ const nn::Request& /*request*/, const std::vector<nn::SyncFence>& /*waitFor*/,
+ nn::MeasureTiming /*measure*/, const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalTimeoutDuration& /*loopTimeoutDuration*/,
+ const nn::OptionalTimeoutDuration& /*timeoutDurationAfterFence*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IPreparedModel::executeFenced is not supported on 1.2 HAL service";
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+ sp<V1_0::IPreparedModel> resource = kPreparedModel;
+ return resource;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.2/utils/src/Service.cpp b/neuralnetworks/1.2/utils/src/Service.cpp
new file mode 100644
index 0000000..110188f
--- /dev/null
+++ b/neuralnetworks/1.2/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_2::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+ hal::utils::ResilientDevice::Factory makeDevice =
+ [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+ auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+ if (service == nullptr) {
+ return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+ }
+ return Device::create(name, std::move(service));
+ };
+
+ return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.3/utils/Android.bp b/neuralnetworks/1.3/utils/Android.bp
index 279b250..d5d897d 100644
--- a/neuralnetworks/1.3/utils/Android.bp
+++ b/neuralnetworks/1.3/utils/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal/1.3/"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
"neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
new file mode 100644
index 0000000..637179d
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
@@ -0,0 +1,52 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <memory>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Buffer final : public nn::IBuffer {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Buffer>> create(
+ sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token);
+
+ Buffer(PrivateConstructorTag tag, sp<V1_3::IBuffer> buffer,
+ nn::Request::MemoryDomainToken token);
+
+ nn::Request::MemoryDomainToken getToken() const override;
+
+ nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+ nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const override;
+
+ private:
+ const sp<V1_3::IBuffer> kBuffer;
+ const nn::Request::MemoryDomainToken kToken;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
new file mode 100644
index 0000000..d46b111
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
@@ -0,0 +1,83 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModelCallback final : public IPreparedModelCallback,
+ public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::GeneralResult<nn::SharedPreparedModel>;
+
+ Return<void> notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status,
+ const sp<V1_2::IPreparedModel>& preparedModel) override;
+ Return<void> notify_1_3(ErrorStatus status, const sp<IPreparedModel>& preparedModel) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+class ExecutionCallback final : public IExecutionCallback, public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+ Return<void> notify(V1_0::ErrorStatus status) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) override;
+ Return<void> notify_1_3(ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
index 43987a9..64aa96e 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
@@ -25,54 +25,54 @@
namespace android::nn {
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType);
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType);
-Result<Priority> convert(const hal::V1_3::Priority& priority);
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType);
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType);
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority);
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_3::Capabilities::OperandPerformance& operandPerformance);
-Result<Operation> convert(const hal::V1_3::Operation& operation);
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
-Result<Operand> convert(const hal::V1_3::Operand& operand);
-Result<Model> convert(const hal::V1_3::Model& model);
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
-Result<Request> convert(const hal::V1_3::Request& request);
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation);
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand);
+GeneralResult<Model> convert(const hal::V1_3::Model& model);
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
+GeneralResult<Request> convert(const hal::V1_3::Request& request);
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
+GeneralResult<OptionalTimeoutDuration> convert(
const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration);
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles);
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_3::utils {
-nn::Result<OperandType> convert(const nn::OperandType& operandType);
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<Priority> convert(const nn::Priority& priority);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<Priority> convert(const nn::Priority& priority);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
-nn::Result<Operand> convert(const nn::Operand& operand);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph);
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole);
-nn::Result<Request> convert(const nn::Request& request);
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
+nn::GeneralResult<Operand> convert(const nn::Operand& operand);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph);
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole);
+nn::GeneralResult<Request> convert(const nn::Request& request);
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
+nn::GeneralResult<OptionalTimeoutDuration> convert(
const nn::OptionalTimeoutDuration& optionalTimeoutDuration);
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
new file mode 100644
index 0000000..2f6c46a
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
@@ -0,0 +1,91 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Device final : public nn::IDevice {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+ sp<V1_3::IDevice> device);
+
+ Device(PrivateConstructorTag tag, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities, std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded,
+ sp<V1_3::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ const std::string kName;
+ const std::string kVersionString;
+ const nn::DeviceType kDeviceType;
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ const std::pair<uint32_t, uint32_t> kNumberOfCacheFilesNeeded;
+ const sp<V1_3::IDevice> kDevice;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
new file mode 100644
index 0000000..e0d69dd
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
@@ -0,0 +1,71 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModel final : public nn::IPreparedModel {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const PreparedModel>> create(
+ sp<V1_3::IPreparedModel> preparedModel);
+
+ PreparedModel(PrivateConstructorTag tag, sp<V1_3::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+ std::any getUnderlyingResource() const override;
+
+ private:
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
+ const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeAsynchronously(
+ const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const;
+
+ const sp<V1_3::IPreparedModel> kPreparedModel;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
new file mode 100644
index 0000000..2bc3257
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
index f8c975d..e61859d 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
@@ -22,6 +22,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.3/types.h>
#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
#include <nnapi/hal/1.0/Conversions.h>
@@ -35,10 +36,14 @@
template <typename Type>
nn::Result<void> validate(const Type& halObject) {
- const auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeCanonical = nn::convert(halObject);
+ if (!maybeCanonical.has_value()) {
+ return nn::error() << maybeCanonical.error().message;
+ }
+ const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return {};
}
@@ -55,9 +60,14 @@
template <typename Type>
decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeVersion = nn::validate(canonical);
+ if (!maybeVersion.has_value()) {
+ return nn::error() << maybeVersion.error();
+ }
+ const auto version = maybeVersion.value();
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return canonical;
}
diff --git a/neuralnetworks/1.3/utils/src/Buffer.cpp b/neuralnetworks/1.3/utils/src/Buffer.cpp
new file mode 100644
index 0000000..f3fe9b5
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Buffer.cpp
@@ -0,0 +1,93 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Buffer.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/HandleError.h>
+
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <memory>
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<std::shared_ptr<const Buffer>> Buffer::create(
+ sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token) {
+ if (buffer == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Buffer::create must have non-null buffer";
+ }
+ if (token == static_cast<nn::Request::MemoryDomainToken>(0)) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Buffer::create must have non-zero token";
+ }
+
+ return std::make_shared<const Buffer>(PrivateConstructorTag{}, std::move(buffer), token);
+}
+
+Buffer::Buffer(PrivateConstructorTag /*tag*/, sp<V1_3::IBuffer> buffer,
+ nn::Request::MemoryDomainToken token)
+ : kBuffer(std::move(buffer)), kToken(token) {
+ CHECK(kBuffer != nullptr);
+ CHECK(kToken != static_cast<nn::Request::MemoryDomainToken>(0));
+}
+
+nn::Request::MemoryDomainToken Buffer::getToken() const {
+ return kToken;
+}
+
+nn::GeneralResult<void> Buffer::copyTo(const nn::Memory& dst) const {
+ const auto hidlDst = NN_TRY(V1_0::utils::convert(dst));
+
+ const auto ret = kBuffer->copyTo(hidlDst);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "IBuffer::copyTo failed with " << toString(status);
+ }
+
+ return {};
+}
+
+nn::GeneralResult<void> Buffer::copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const {
+ const auto hidlSrc = NN_TRY(V1_0::utils::convert(src));
+ const auto hidlDimensions = hidl_vec<uint32_t>(dimensions);
+
+ const auto ret = kBuffer->copyFrom(hidlSrc, hidlDimensions);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "IBuffer::copyFrom failed with " << toString(status);
+ }
+
+ return {};
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Callbacks.cpp b/neuralnetworks/1.3/utils/src/Callbacks.cpp
new file mode 100644
index 0000000..ff81275
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Callbacks.cpp
@@ -0,0 +1,184 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Callbacks.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/1.0/PreparedModel.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/PreparedModel.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ return NN_TRY(V1_0::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<V1_2::IPreparedModel>& preparedModel) {
+ return NN_TRY(V1_2::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<IPreparedModel>& preparedModel) {
+ return NN_TRY(utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResults(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return hal::utils::makeExecutionFailure(
+ convertExecutionGeneralResultsHelper(outputShapes, timing));
+}
+
+} // namespace
+
+Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
+ const sp<V1_2::IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_3(ErrorStatus status,
+ const sp<IPreparedModel>& preparedModel) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+void PreparedModelCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+PreparedModelCallback::Data PreparedModelCallback::get() {
+ return mData.take();
+}
+
+void PreparedModelCallback::notifyInternal(PreparedModelCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+// ExecutionCallback methods begin here
+
+Return<void> ExecutionCallback::notify(V1_0::ErrorStatus status) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal({});
+ }
+ return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_2(V1_0::ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+ }
+ return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_3(ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+ }
+ return Void();
+}
+
+void ExecutionCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+ExecutionCallback::Data ExecutionCallback::get() {
+ return mData.take();
+}
+
+void ExecutionCallback::notifyInternal(ExecutionCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 4c54e3b..0dc0785 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -27,6 +27,7 @@
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/1.2/Conversions.h>
#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
#include <algorithm>
#include <chrono>
@@ -79,7 +80,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
std::vector<ConvertOutput<Type>> canonical;
canonical.reserve(arguments.size());
for (const auto& argument : arguments) {
@@ -89,25 +90,25 @@
}
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
return convertVec(arguments);
}
} // anonymous namespace
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType) {
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-Result<Priority> convert(const hal::V1_3::Priority& priority) {
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority) {
return static_cast<Priority>(priority);
}
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
const bool validOperandTypes = std::all_of(
capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
[](const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
@@ -115,13 +116,14 @@
return !maybeType.has_value() ? false : validOperandType(maybeType.value());
});
if (!validOperandTypes) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Invalid OperandType when converting OperandPerformance in Capabilities";
}
auto operandPerformance = NN_TRY(convert(capabilities.operandPerformance));
- auto table =
- NN_TRY(Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)));
+ auto table = NN_TRY(hal::utils::makeGeneralFailure(
+ Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+ nn::ErrorStatus::GENERAL_FAILURE));
return Capabilities{
.relaxedFloat32toFloat16PerformanceScalar =
@@ -134,7 +136,7 @@
};
}
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -142,7 +144,7 @@
};
}
-Result<Operation> convert(const hal::V1_3::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -150,11 +152,11 @@
};
}
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
return static_cast<Operand::LifeTime>(operandLifeTime);
}
-Result<Operand> convert(const hal::V1_3::Operand& operand) {
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -166,7 +168,7 @@
};
}
-Result<Model> convert(const hal::V1_3::Model& model) {
+GeneralResult<Model> convert(const hal::V1_3::Model& model) {
return Model{
.main = NN_TRY(convert(model.main)),
.referenced = NN_TRY(convert(model.referenced)),
@@ -177,7 +179,7 @@
};
}
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
auto operations = NN_TRY(convert(subgraph.operations));
// Verify number of consumers.
@@ -186,9 +188,10 @@
CHECK(subgraph.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < subgraph.operands.size(); ++i) {
if (subgraph.operands[i].numberOfConsumers != numberOfConsumers[i]) {
- return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
- << numberOfConsumers[i] << " but found "
- << subgraph.operands[i].numberOfConsumers;
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid numberOfConsumers for operand " << i << ", expected "
+ << numberOfConsumers[i] << " but found "
+ << subgraph.operands[i].numberOfConsumers;
}
}
@@ -200,11 +203,11 @@
};
}
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
return BufferDesc{.dimensions = bufferDesc.dimensions};
}
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
return BufferRole{
.modelIndex = bufferRole.modelIndex,
.ioIndex = bufferRole.ioIndex,
@@ -212,7 +215,7 @@
};
}
-Result<Request> convert(const hal::V1_3::Request& request) {
+GeneralResult<Request> convert(const hal::V1_3::Request& request) {
return Request{
.inputs = NN_TRY(convert(request.inputs)),
.outputs = NN_TRY(convert(request.outputs)),
@@ -220,7 +223,7 @@
};
}
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
using Discriminator = hal::V1_3::Request::MemoryPool::hidl_discriminator;
switch (memoryPool.getDiscriminator()) {
case Discriminator::hidlMemory:
@@ -228,15 +231,16 @@
case Discriminator::token:
return static_cast<Request::MemoryDomainToken>(memoryPool.token());
}
- return NN_ERROR() << "Invalid Request::MemoryPool discriminator "
- << underlyingType(memoryPool.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid Request::MemoryPool discriminator "
+ << underlyingType(memoryPool.getDiscriminator());
}
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
constexpr auto kTimePointMaxCount = TimePoint::max().time_since_epoch().count();
- const auto makeTimePoint = [](uint64_t count) -> Result<OptionalTimePoint> {
+ const auto makeTimePoint = [](uint64_t count) -> GeneralResult<OptionalTimePoint> {
if (count > kTimePointMaxCount) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimePoint because the count exceeds the max";
}
const auto nanoseconds = std::chrono::nanoseconds{count};
@@ -250,16 +254,17 @@
case Discriminator::nanosecondsSinceEpoch:
return makeTimePoint(optionalTimePoint.nanosecondsSinceEpoch());
}
- return NN_ERROR() << "Invalid OptionalTimePoint discriminator "
- << underlyingType(optionalTimePoint.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid OptionalTimePoint discriminator "
+ << underlyingType(optionalTimePoint.getDiscriminator());
}
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<OptionalTimeoutDuration> convert(
const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration) {
constexpr auto kTimeoutDurationMaxCount = TimeoutDuration::max().count();
- const auto makeTimeoutDuration = [](uint64_t count) -> Result<OptionalTimeoutDuration> {
+ const auto makeTimeoutDuration = [](uint64_t count) -> GeneralResult<OptionalTimeoutDuration> {
if (count > kTimeoutDurationMaxCount) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimeoutDuration because the count exceeds the max";
}
return TimeoutDuration{count};
@@ -272,11 +277,12 @@
case Discriminator::nanoseconds:
return makeTimeoutDuration(optionalTimeoutDuration.nanoseconds());
}
- return NN_ERROR() << "Invalid OptionalTimeoutDuration discriminator "
- << underlyingType(optionalTimeoutDuration.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid OptionalTimeoutDuration discriminator "
+ << underlyingType(optionalTimeoutDuration.getDiscriminator());
}
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
switch (status) {
case hal::V1_3::ErrorStatus::NONE:
case hal::V1_3::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -289,10 +295,11 @@
case hal::V1_3::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
return static_cast<ErrorStatus>(status);
}
- return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid ErrorStatus " << underlyingType(status);
}
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles) {
return convertVec(bufferRoles);
}
@@ -304,32 +311,32 @@
using utils::convert;
-nn::Result<V1_0::PerformanceInfo> convert(
+nn::GeneralResult<V1_0::PerformanceInfo> convert(
const nn::Capabilities::PerformanceInfo& performanceInfo) {
return V1_0::utils::convert(performanceInfo);
}
-nn::Result<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
+nn::GeneralResult<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
return V1_0::utils::convert(dataLocation);
}
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
return V1_0::utils::convert(operandValues);
}
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
return V1_0::utils::convert(memory);
}
-nn::Result<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
+nn::GeneralResult<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
return V1_0::utils::convert(argument);
}
-nn::Result<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
+nn::GeneralResult<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
return V1_2::utils::convert(extraParams);
}
-nn::Result<V1_2::Model::ExtensionNameAndPrefix> convert(
+nn::GeneralResult<V1_2::Model::ExtensionNameAndPrefix> convert(
const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
return V1_2::utils::convert(extensionNameAndPrefix);
}
@@ -338,7 +345,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
hidl_vec<ConvertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(convert(arguments[i]));
@@ -347,42 +354,41 @@
}
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
return convertVec(arguments);
}
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
Request::MemoryPool ret;
ret.hidlMemory(NN_TRY(convert(memory)));
return ret;
}
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
Request::MemoryPool ret;
ret.token(underlyingType(token));
return ret;
}
-nn::Result<Request::MemoryPool> makeMemoryPool(
- const std::shared_ptr<const nn::IBuffer>& /*buffer*/) {
- return NN_ERROR() << "Unable to make memory pool from IBuffer";
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::SharedBuffer& /*buffer*/) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Unable to make memory pool from IBuffer";
}
} // anonymous namespace
-nn::Result<OperandType> convert(const nn::OperandType& operandType) {
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-nn::Result<Priority> convert(const nn::Priority& priority) {
+nn::GeneralResult<Priority> convert(const nn::Priority& priority) {
return static_cast<Priority>(priority);
}
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
std::copy_if(capabilities.operandPerformance.asVector().begin(),
@@ -403,7 +409,7 @@
};
}
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -411,7 +417,7 @@
};
}
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -419,14 +425,15 @@
};
}
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
if (operandLifeTime == nn::Operand::LifeTime::POINTER) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
return static_cast<OperandLifeTime>(operandLifeTime);
}
-nn::Result<Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<Operand> convert(const nn::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -439,9 +446,10 @@
};
}
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
return Model{
@@ -454,7 +462,7 @@
};
}
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
auto operands = NN_TRY(convert(subgraph.operands));
// Update number of consumers.
@@ -473,11 +481,11 @@
};
}
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
return BufferDesc{.dimensions = bufferDesc.dimensions};
}
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole) {
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole) {
return BufferRole{
.modelIndex = bufferRole.modelIndex,
.ioIndex = bufferRole.ioIndex,
@@ -485,9 +493,10 @@
};
}
-nn::Result<Request> convert(const nn::Request& request) {
+nn::GeneralResult<Request> convert(const nn::Request& request) {
if (!hal::utils::hasNoPointerData(request)) {
- return NN_ERROR() << "Request cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Request cannot be converted because it contains pointer-based memory";
}
return Request{
@@ -497,30 +506,31 @@
};
}
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
return std::visit([](const auto& o) { return makeMemoryPool(o); }, memoryPool);
}
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
OptionalTimePoint ret;
if (optionalTimePoint.has_value()) {
const auto count = optionalTimePoint.value().time_since_epoch().count();
if (count < 0) {
- return NN_ERROR() << "Unable to convert OptionalTimePoint because time since epoch "
- "count is negative";
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Unable to convert OptionalTimePoint because time since epoch count is "
+ "negative";
}
ret.nanosecondsSinceEpoch(count);
}
return ret;
}
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<OptionalTimeoutDuration> convert(
const nn::OptionalTimeoutDuration& optionalTimeoutDuration) {
OptionalTimeoutDuration ret;
if (optionalTimeoutDuration.has_value()) {
const auto count = optionalTimeoutDuration.value().count();
if (count < 0) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimeoutDuration because count is negative";
}
ret.nanoseconds(count);
@@ -528,7 +538,7 @@
return ret;
}
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
switch (errorStatus) {
case nn::ErrorStatus::NONE:
case nn::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -545,7 +555,7 @@
}
}
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
return convertVec(bufferRoles);
}
diff --git a/neuralnetworks/1.3/utils/src/Device.cpp b/neuralnetworks/1.3/utils/src/Device.cpp
new file mode 100644
index 0000000..c215f39
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Device.cpp
@@ -0,0 +1,269 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Device.h"
+
+#include "Buffer.h"
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.1/Conversions.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/Device.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <any>
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<hidl_vec<sp<IPreparedModel>>> convert(
+ const std::vector<nn::SharedPreparedModel>& preparedModels) {
+ hidl_vec<sp<IPreparedModel>> hidlPreparedModels(preparedModels.size());
+ for (size_t i = 0; i < preparedModels.size(); ++i) {
+ std::any underlyingResource = preparedModels[i]->getUnderlyingResource();
+ if (const auto* hidlPreparedModel =
+ std::any_cast<sp<IPreparedModel>>(&underlyingResource)) {
+ hidlPreparedModels[i] = *hidlPreparedModel;
+ } else {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Unable to convert from nn::IPreparedModel to V1_3::IPreparedModel";
+ }
+ }
+ return hidlPreparedModels;
+}
+
+nn::GeneralResult<nn::SharedBuffer> convert(
+ nn::GeneralResult<std::shared_ptr<const Buffer>> result) {
+ return NN_TRY(std::move(result));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+ sp<V1_3::IDevice> device) {
+ if (name.empty()) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Device::create must have non-empty name";
+ }
+ if (device == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Device::create must have non-null device";
+ }
+
+ auto versionString = NN_TRY(V1_2::utils::initVersionString(device.get()));
+ const auto deviceType = NN_TRY(V1_2::utils::initDeviceType(device.get()));
+ auto extensions = NN_TRY(V1_2::utils::initExtensions(device.get()));
+ auto capabilities = NN_TRY(V1_2::utils::initCapabilities(device.get()));
+ const auto numberOfCacheFilesNeeded =
+ NN_TRY(V1_2::utils::initNumberOfCacheFilesNeeded(device.get()));
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+ return std::make_shared<const Device>(
+ PrivateConstructorTag{}, std::move(name), std::move(versionString), deviceType,
+ std::move(extensions), std::move(capabilities), numberOfCacheFilesNeeded,
+ std::move(device), std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities,
+ std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded, sp<V1_3::IDevice> device,
+ hal::utils::DeathHandler deathHandler)
+ : kName(std::move(name)),
+ kVersionString(std::move(versionString)),
+ kDeviceType(deviceType),
+ kExtensions(std::move(extensions)),
+ kCapabilities(std::move(capabilities)),
+ kNumberOfCacheFilesNeeded(numberOfCacheFilesNeeded),
+ kDevice(std::move(device)),
+ kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+ return kName;
+}
+
+const std::string& Device::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+ return nn::Version::ANDROID_R;
+}
+
+nn::DeviceType Device::getType() const {
+ return kDeviceType;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+ return kNumberOfCacheFilesNeeded;
+}
+
+nn::GeneralResult<void> Device::wait() const {
+ const auto ret = kDevice->ping();
+ return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result, &model](ErrorStatus status, const hidl_vec<bool>& supportedOperations) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "IDevice::getSupportedOperations_1_3 failed with " << toString(status);
+ } else if (supportedOperations.size() != model.main.operations.size()) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::getSupportedOperations_1_3 returned vector of size "
+ << supportedOperations.size() << " but expected "
+ << model.main.operations.size();
+ } else {
+ result = supportedOperations;
+ }
+ };
+
+ const auto ret = kDevice->getSupportedOperations_1_3(hidlModel, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+ const auto hidlPreference = NN_TRY(V1_1::utils::convert(preference));
+ const auto hidlPriority = NN_TRY(convert(priority));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+ const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret =
+ kDevice->prepareModel_1_3(hidlModel, hidlPreference, hidlPriority, hidlDeadline,
+ hidlModelCache, hidlDataCache, hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModel_1_3 failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+ const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModelFromCache_1_3(hidlDeadline, hidlModelCache, hidlDataCache,
+ hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModelFromCache_1_3 failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const {
+ const auto hidlDesc = NN_TRY(convert(desc));
+ const auto hidlPreparedModels = NN_TRY(convert(preparedModels));
+ const auto hidlInputRoles = NN_TRY(convert(inputRoles));
+ const auto hidlOutputRoles = NN_TRY(convert(outputRoles));
+
+ nn::GeneralResult<nn::SharedBuffer> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const sp<IBuffer>& buffer, uint32_t token) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "IDevice::allocate failed with " << toString(status);
+ } else if (buffer == nullptr) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned buffer is nullptr";
+ } else if (token == 0) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned token is invalid (0)";
+ } else {
+ result = convert(
+ Buffer::create(buffer, static_cast<nn::Request::MemoryDomainToken>(token)));
+ }
+ };
+
+ const auto ret =
+ kDevice->allocate(hidlDesc, hidlPreparedModels, hidlInputRoles, hidlOutputRoles, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/PreparedModel.cpp b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..df9b280
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
@@ -0,0 +1,267 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
+ const hidl_vec<V1_2::OutputShape>& outputShapes, const V1_2::Timing& timing) {
+ return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
+}
+
+nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
+ const std::vector<nn::SyncFence>& syncFences) {
+ hidl_vec<hidl_handle> handles(syncFences.size());
+ for (size_t i = 0; i < syncFences.size(); ++i) {
+ handles[i] = NN_TRY(V1_2::utils::convert(syncFences[i].getHandle()));
+ }
+ return handles;
+}
+
+nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> convertFencedExecutionCallbackResults(
+ const V1_2::Timing& timingLaunched, const V1_2::Timing& timingFenced) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(timingLaunched)),
+ NN_TRY(validatedConvertToCanonical(timingFenced)));
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+convertExecuteFencedResults(const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ auto resultSyncFence = nn::SyncFence::createAsSignaled();
+ if (syncFence.getNativeHandle() != nullptr) {
+ auto nativeHandle = NN_TRY(validatedConvertToCanonical(syncFence));
+ resultSyncFence = NN_TRY(hal::utils::makeGeneralFailure(
+ nn::SyncFence::create(std::move(nativeHandle)), nn::ErrorStatus::GENERAL_FAILURE));
+ }
+
+ if (callback == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "callback is null";
+ }
+
+ // Create callback which can be used to retrieve the execution error status and timings.
+ nn::ExecuteFencedInfoCallback resultCallback =
+ [callback]() -> nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> {
+ nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const V1_2::Timing& timingLaunched,
+ const V1_2::Timing& timingFenced) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical = validatedConvertToCanonical(status).value_or(
+ nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getExecutionInfo failed with " << toString(status);
+ } else {
+ result = convertFencedExecutionCallbackResults(timingLaunched, timingFenced);
+ }
+ };
+
+ const auto ret = callback->getExecutionInfo(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+ };
+
+ return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+ sp<V1_3::IPreparedModel> preparedModel) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::PreparedModel::create must have non-null preparedModel";
+ }
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+ return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_3::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler)
+ : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeSynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
+ } else {
+ result = convertExecutionResults(outputShapes, timing);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeSynchronously_1_3(request, measure, deadline,
+ loopTimeoutDuration, cb);
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+
+ return result;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeAsynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ const auto cb = sp<ExecutionCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret =
+ kPreparedModel->execute_1_3(request, measure, deadline, loopTimeoutDuration, cb);
+ const auto status =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "executeAsynchronously failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+ const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+ const auto hidlMeasure =
+ NN_TRY(hal::utils::makeExecutionFailure(V1_2::utils::convert(measure)));
+ const auto hidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+ const auto hidlLoopTimeoutDuration =
+ NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const bool preferSynchronous = true;
+
+ // Execute synchronously if allowed.
+ if (preferSynchronous) {
+ result = executeSynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Run asymchronous execution if execution has not already completed.
+ if (!result.has_value()) {
+ result = executeAsynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Flush output buffers if suxcessful execution.
+ if (result.has_value()) {
+ NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+ }
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared));
+
+ const auto hidlRequest = NN_TRY(convert(requestInShared));
+ const auto hidlWaitFor = NN_TRY(convertSyncFences(waitFor));
+ const auto hidlMeasure = NN_TRY(V1_2::utils::convert(measure));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+ const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeFenced failed with " << toString(status);
+ } else {
+ result = convertExecuteFencedResults(syncFence, callback);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeFenced(hidlRequest, hidlWaitFor, hidlMeasure,
+ hidlDeadline, hidlLoopTimeoutDuration,
+ hidlTimeoutDurationAfterFence, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+ auto [syncFence, callback] = NN_TRY(std::move(result));
+
+ // If executeFenced required the request memory to be moved into shared memory, block here until
+ // the fenced execution has completed and flush the memory back.
+ if (maybeRequestInShared.has_value()) {
+ const auto state = syncFence.syncWait({});
+ if (state != nn::SyncFence::FenceState::SIGNALED) {
+ return NN_ERROR() << "syncWait failed with " << state;
+ }
+ NN_TRY(hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared));
+ }
+
+ return std::make_pair(std::move(syncFence), std::move(callback));
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+ sp<V1_3::IPreparedModel> resource = kPreparedModel;
+ return resource;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Service.cpp b/neuralnetworks/1.3/utils/src/Service.cpp
new file mode 100644
index 0000000..62887fb
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+ hal::utils::ResilientDevice::Factory makeDevice =
+ [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+ auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+ if (service == nullptr) {
+ return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+ }
+ return Device::create(name, std::move(service));
+ };
+
+ return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/utils/common/Android.bp b/neuralnetworks/utils/common/Android.bp
index b61dc97..21562cf 100644
--- a/neuralnetworks/utils/common/Android.bp
+++ b/neuralnetworks/utils/common/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
],
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
index 8c01368..254a3d4 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
@@ -19,6 +19,7 @@
#include <nnapi/Result.h>
#include <nnapi/Types.h>
+#include <functional>
#include <vector>
// Shorthand
@@ -42,14 +43,16 @@
bool hasNoPointerData(const nn::Request& request);
// Relocate pointer-based data to shared memory.
-nn::Result<nn::Model> flushDataFromPointerToShared(const nn::Model& model);
-nn::Result<nn::Request> flushDataFromPointerToShared(const nn::Request& request);
+nn::GeneralResult<std::reference_wrapper<const nn::Model>> flushDataFromPointerToShared(
+ const nn::Model* model, std::optional<nn::Model>* maybeModelInSharedOut);
+nn::GeneralResult<std::reference_wrapper<const nn::Request>> flushDataFromPointerToShared(
+ const nn::Request* request, std::optional<nn::Request>* maybeRequestInSharedOut);
// Undoes `flushDataFromPointerToShared` on a Request object. More specifically,
// `unflushDataFromSharedToPointer` copies the output shared memory data from the transformed
// Request object back to the output pointer-based memory in the original Request object.
-nn::Result<void> unflushDataFromSharedToPointer(const nn::Request& request,
- const nn::Request& requestInShared);
+nn::GeneralResult<void> unflushDataFromSharedToPointer(
+ const nn::Request& request, const std::optional<nn::Request>& maybeRequestInShared);
std::vector<uint32_t> countNumberOfConsumers(size_t numberOfOperands,
const std::vector<nn::Operation>& operations);
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h b/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h
new file mode 100644
index 0000000..e4046b5
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/HandleError.h
@@ -0,0 +1,101 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <android/hidl/base/1.0/IBase.h>
+#include <hidl/HidlSupport.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+namespace android::hardware::neuralnetworks::utils {
+
+template <typename Type>
+nn::GeneralResult<Type> handleTransportError(const hardware::Return<Type>& ret) {
+ if (ret.isDeadObject()) {
+ return NN_ERROR(nn::ErrorStatus::DEAD_OBJECT)
+ << "Return<>::isDeadObject returned true: " << ret.description();
+ }
+ if (!ret.isOk()) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Return<>::isOk returned false: " << ret.description();
+ }
+ return ret;
+}
+
+template <>
+inline nn::GeneralResult<void> handleTransportError(const hardware::Return<void>& ret) {
+ if (ret.isDeadObject()) {
+ return NN_ERROR(nn::ErrorStatus::DEAD_OBJECT)
+ << "Return<>::isDeadObject returned true: " << ret.description();
+ }
+ if (!ret.isOk()) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Return<>::isOk returned false: " << ret.description();
+ }
+ return {};
+}
+
+template <typename Type>
+nn::GeneralResult<Type> makeGeneralFailure(nn::Result<Type> result, nn::ErrorStatus status) {
+ if (!result.has_value()) {
+ return nn::error(status) << std::move(result).error();
+ }
+ return std::move(result).value();
+}
+
+template <>
+inline nn::GeneralResult<void> makeGeneralFailure(nn::Result<void> result, nn::ErrorStatus status) {
+ if (!result.has_value()) {
+ return nn::error(status) << std::move(result).error();
+ }
+ return {};
+}
+
+template <typename Type>
+nn::ExecutionResult<Type> makeExecutionFailure(nn::Result<Type> result, nn::ErrorStatus status) {
+ if (!result.has_value()) {
+ return nn::error(status) << std::move(result).error();
+ }
+ return std::move(result).value();
+}
+
+template <>
+inline nn::ExecutionResult<void> makeExecutionFailure(nn::Result<void> result,
+ nn::ErrorStatus status) {
+ if (!result.has_value()) {
+ return nn::error(status) << std::move(result).error();
+ }
+ return {};
+}
+
+template <typename Type>
+nn::ExecutionResult<Type> makeExecutionFailure(nn::GeneralResult<Type> result) {
+ if (!result.has_value()) {
+ const auto [message, status] = std::move(result).error();
+ return nn::error(status) << message;
+ }
+ return std::move(result).value();
+}
+
+template <>
+inline nn::ExecutionResult<void> makeExecutionFailure(nn::GeneralResult<void> result) {
+ if (!result.has_value()) {
+ const auto [message, status] = std::move(result).error();
+ return nn::error(status) << message;
+ }
+ return {};
+}
+
+} // namespace android::hardware::neuralnetworks::utils
\ No newline at end of file
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ProtectCallback.h b/neuralnetworks/utils/common/include/nnapi/hal/ProtectCallback.h
new file mode 100644
index 0000000..85bd613
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ProtectCallback.h
@@ -0,0 +1,90 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_PROTECT_CALLBACK_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_PROTECT_CALLBACK_H
+
+#include <android-base/scopeguard.h>
+#include <android-base/thread_annotations.h>
+#include <android/hidl/base/1.0/IBase.h>
+#include <hidl/HidlSupport.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <mutex>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+class IProtectedCallback {
+ public:
+ /**
+ * Marks this object as a dead object.
+ */
+ virtual void notifyAsDeadObject() = 0;
+
+ // Public virtual destructor to allow objects to be stored (and destroyed) as smart pointers.
+ // E.g., std::unique_ptr<IProtectedCallback>.
+ virtual ~IProtectedCallback() = default;
+
+ protected:
+ // Protect the non-destructor special member functions to prevent object slicing.
+ IProtectedCallback() = default;
+ IProtectedCallback(const IProtectedCallback&) = default;
+ IProtectedCallback(IProtectedCallback&&) noexcept = default;
+ IProtectedCallback& operator=(const IProtectedCallback&) = default;
+ IProtectedCallback& operator=(IProtectedCallback&&) noexcept = default;
+};
+
+// Thread safe class
+class DeathRecipient final : public hidl_death_recipient {
+ public:
+ void serviceDied(uint64_t /*cookie*/, const wp<hidl::base::V1_0::IBase>& /*who*/) override;
+ // Precondition: `killable` must be non-null.
+ void add(IProtectedCallback* killable) const;
+ // Precondition: `killable` must be non-null.
+ void remove(IProtectedCallback* killable) const;
+
+ private:
+ mutable std::mutex mMutex;
+ mutable std::vector<IProtectedCallback*> mObjects GUARDED_BY(mMutex);
+};
+
+class DeathHandler final {
+ public:
+ static nn::GeneralResult<DeathHandler> create(sp<hidl::base::V1_0::IBase> object);
+
+ DeathHandler(const DeathHandler&) = delete;
+ DeathHandler(DeathHandler&&) noexcept = default;
+ DeathHandler& operator=(const DeathHandler&) = delete;
+ DeathHandler& operator=(DeathHandler&&) noexcept = delete;
+ ~DeathHandler();
+
+ using Cleanup = std::function<void()>;
+ // Precondition: `killable` must be non-null.
+ [[nodiscard]] base::ScopeGuard<Cleanup> protectCallback(IProtectedCallback* killable) const;
+
+ private:
+ DeathHandler(sp<hidl::base::V1_0::IBase> object, sp<DeathRecipient> deathRecipient);
+
+ sp<hidl::base::V1_0::IBase> kObject;
+ sp<DeathRecipient> kDeathRecipient;
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_PROTECT_CALLBACK_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h
new file mode 100644
index 0000000..996ec1e
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientBuffer.h
@@ -0,0 +1,62 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_BUFFER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_BUFFER_H
+
+#include <android-base/thread_annotations.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+class ResilientBuffer final : public nn::IBuffer {
+ struct PrivateConstructorTag {};
+
+ public:
+ using Factory = std::function<nn::GeneralResult<nn::SharedBuffer>(bool blocking)>;
+
+ static nn::GeneralResult<std::shared_ptr<const ResilientBuffer>> create(Factory makeBuffer);
+
+ explicit ResilientBuffer(PrivateConstructorTag tag, Factory makeBuffer,
+ nn::SharedBuffer buffer);
+
+ nn::SharedBuffer getBuffer() const;
+ nn::SharedBuffer recover(const nn::IBuffer* failingBuffer, bool blocking) const;
+
+ nn::Request::MemoryDomainToken getToken() const override;
+
+ nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+
+ nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const override;
+
+ private:
+ const Factory kMakeBuffer;
+ mutable std::mutex mMutex;
+ mutable nn::SharedBuffer mBuffer GUARDED_BY(mMutex);
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_BUFFER_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientDevice.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientDevice.h
new file mode 100644
index 0000000..4f1afb9
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientDevice.h
@@ -0,0 +1,107 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_DEVICE_H
+
+#include <android-base/thread_annotations.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+class ResilientDevice final : public nn::IDevice,
+ public std::enable_shared_from_this<ResilientDevice> {
+ struct PrivateConstructorTag {};
+
+ public:
+ using Factory = std::function<nn::GeneralResult<nn::SharedDevice>(bool blocking)>;
+
+ static nn::GeneralResult<std::shared_ptr<const ResilientDevice>> create(Factory makeDevice);
+
+ explicit ResilientDevice(PrivateConstructorTag tag, Factory makeDevice, std::string name,
+ std::string versionString, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities, nn::SharedDevice device);
+
+ nn::SharedDevice getDevice() const;
+ nn::SharedDevice recover(const nn::IDevice* failingDevice, bool blocking) const;
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelInternal(
+ bool blocking, const nn::Model& model, nn::ExecutionPreference preference,
+ nn::Priority priority, nn::OptionalTimePoint deadline,
+ const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const;
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCacheInternal(
+ bool blocking, nn::OptionalTimePoint deadline,
+ const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const;
+ nn::GeneralResult<nn::SharedBuffer> allocateInternal(
+ bool blocking, const nn::BufferDesc& desc,
+ const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const;
+
+ const Factory kMakeDevice;
+ const std::string kName;
+ const std::string kVersionString;
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ mutable std::mutex mMutex;
+ mutable nn::SharedDevice mDevice GUARDED_BY(mMutex);
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_DEVICE_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h
new file mode 100644
index 0000000..c2940d1
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h
@@ -0,0 +1,70 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_PREPARED_MODEL_H
+
+#include <android-base/thread_annotations.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+class ResilientPreparedModel final : public nn::IPreparedModel {
+ struct PrivateConstructorTag {};
+
+ public:
+ using Factory = std::function<nn::GeneralResult<nn::SharedPreparedModel>(bool blocking)>;
+
+ static nn::GeneralResult<std::shared_ptr<const ResilientPreparedModel>> create(
+ Factory makePreparedModel);
+
+ explicit ResilientPreparedModel(PrivateConstructorTag tag, Factory makePreparedModel,
+ nn::SharedPreparedModel preparedModel);
+
+ nn::SharedPreparedModel getPreparedModel() const;
+ nn::SharedPreparedModel recover(const nn::IPreparedModel* failingPreparedModel,
+ bool blocking) const;
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+ std::any getUnderlyingResource() const override;
+
+ private:
+ const Factory kMakePreparedModel;
+ mutable std::mutex mMutex;
+ mutable nn::SharedPreparedModel mPreparedModel GUARDED_BY(mMutex);
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_PREPARED_MODEL_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/TransferValue.h b/neuralnetworks/utils/common/include/nnapi/hal/TransferValue.h
new file mode 100644
index 0000000..7103c6b
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/TransferValue.h
@@ -0,0 +1,66 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_TRANSFER_VALUE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_TRANSFER_VALUE_H
+
+#include <android-base/thread_annotations.h>
+
+#include <condition_variable>
+#include <mutex>
+#include <optional>
+
+namespace android::hardware::neuralnetworks::utils {
+
+// This class is thread safe.
+template <typename Type>
+class TransferValue final {
+ public:
+ void put(Type object) const;
+ [[nodiscard]] Type take() const;
+
+ private:
+ mutable std::mutex mMutex;
+ mutable std::condition_variable mCondition;
+ mutable std::optional<Type> mObject GUARDED_BY(mMutex);
+};
+
+// template implementation
+
+template <typename Type>
+void TransferValue<Type>::put(Type object) const {
+ {
+ std::lock_guard guard(mMutex);
+ // Immediately return if value already exists.
+ if (mObject.has_value()) return;
+ mObject.emplace(std::move(object));
+ }
+ mCondition.notify_all();
+}
+
+template <typename Type>
+Type TransferValue<Type>::take() const {
+ std::unique_lock lock(mMutex);
+ base::ScopedLockAssertion lockAssertion(mMutex);
+ mCondition.wait(lock, [this]() REQUIRES(mMutex) { return mObject.has_value(); });
+ std::optional<Type> object;
+ std::swap(object, mObject);
+ return std::move(object).value();
+}
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_TRANSFER_VALUE_H
diff --git a/neuralnetworks/utils/common/src/CommonUtils.cpp b/neuralnetworks/utils/common/src/CommonUtils.cpp
index 667189b..2565972 100644
--- a/neuralnetworks/utils/common/src/CommonUtils.cpp
+++ b/neuralnetworks/utils/common/src/CommonUtils.cpp
@@ -16,6 +16,8 @@
#include "CommonUtils.h"
+#include "HandleError.h"
+
#include <android-base/logging.h>
#include <nnapi/Result.h>
#include <nnapi/SharedMemory.h>
@@ -25,6 +27,7 @@
#include <algorithm>
#include <any>
+#include <functional>
#include <optional>
#include <variant>
#include <vector>
@@ -111,8 +114,18 @@
return hasNoPointerData(request.inputs) && hasNoPointerData(request.outputs);
}
-nn::Result<nn::Model> flushDataFromPointerToShared(const nn::Model& model) {
- auto modelInShared = model;
+nn::GeneralResult<std::reference_wrapper<const nn::Model>> flushDataFromPointerToShared(
+ const nn::Model* model, std::optional<nn::Model>* maybeModelInSharedOut) {
+ CHECK(model != nullptr);
+ CHECK(maybeModelInSharedOut != nullptr);
+
+ if (hasNoPointerData(*model)) {
+ return *model;
+ }
+
+ // Make a copy of the model in order to make modifications. The modified model is returned to
+ // the caller through `maybeModelInSharedOut` if the function succeeds.
+ nn::Model modelInShared = *model;
nn::ConstantMemoryBuilder memoryBuilder(modelInShared.pools.size());
copyPointersToSharedMemory(&modelInShared.main, &memoryBuilder);
@@ -126,11 +139,22 @@
modelInShared.pools.push_back(std::move(memory));
}
- return modelInShared;
+ *maybeModelInSharedOut = modelInShared;
+ return **maybeModelInSharedOut;
}
-nn::Result<nn::Request> flushDataFromPointerToShared(const nn::Request& request) {
- auto requestInShared = request;
+nn::GeneralResult<std::reference_wrapper<const nn::Request>> flushDataFromPointerToShared(
+ const nn::Request* request, std::optional<nn::Request>* maybeRequestInSharedOut) {
+ CHECK(request != nullptr);
+ CHECK(maybeRequestInSharedOut != nullptr);
+
+ if (hasNoPointerData(*request)) {
+ return *request;
+ }
+
+ // Make a copy of the request in order to make modifications. The modified request is returned
+ // to the caller through `maybeRequestInSharedOut` if the function succeeds.
+ nn::Request requestInShared = *request;
// Change input pointers to shared memory.
nn::ConstantMemoryBuilder inputBuilder(requestInShared.pools.size());
@@ -171,15 +195,17 @@
requestInShared.pools.push_back(std::move(memory));
}
- return requestInShared;
+ *maybeRequestInSharedOut = requestInShared;
+ return **maybeRequestInSharedOut;
}
-nn::Result<void> unflushDataFromSharedToPointer(const nn::Request& request,
- const nn::Request& requestInShared) {
- if (requestInShared.pools.empty() ||
- !std::holds_alternative<nn::Memory>(requestInShared.pools.back())) {
+nn::GeneralResult<void> unflushDataFromSharedToPointer(
+ const nn::Request& request, const std::optional<nn::Request>& maybeRequestInShared) {
+ if (!maybeRequestInShared.has_value() || maybeRequestInShared->pools.empty() ||
+ !std::holds_alternative<nn::Memory>(maybeRequestInShared->pools.back())) {
return {};
}
+ const auto& requestInShared = *maybeRequestInShared;
// Map the memory.
const auto& outputMemory = std::get<nn::Memory>(requestInShared.pools.back());
diff --git a/neuralnetworks/utils/common/src/ProtectCallback.cpp b/neuralnetworks/utils/common/src/ProtectCallback.cpp
new file mode 100644
index 0000000..1d9a307
--- /dev/null
+++ b/neuralnetworks/utils/common/src/ProtectCallback.cpp
@@ -0,0 +1,95 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ProtectCallback.h"
+
+#include <android-base/logging.h>
+#include <android-base/scopeguard.h>
+#include <android-base/thread_annotations.h>
+#include <android/hidl/base/1.0/IBase.h>
+#include <hidl/HidlSupport.h>
+#include <nnapi/Result.h>
+#include <nnapi/hal/HandleError.h>
+
+#include <algorithm>
+#include <functional>
+#include <mutex>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+void DeathRecipient::serviceDied(uint64_t /*cookie*/, const wp<hidl::base::V1_0::IBase>& /*who*/) {
+ std::lock_guard guard(mMutex);
+ std::for_each(mObjects.begin(), mObjects.end(),
+ [](IProtectedCallback* killable) { killable->notifyAsDeadObject(); });
+}
+
+void DeathRecipient::add(IProtectedCallback* killable) const {
+ CHECK(killable != nullptr);
+ std::lock_guard guard(mMutex);
+ mObjects.push_back(killable);
+}
+
+void DeathRecipient::remove(IProtectedCallback* killable) const {
+ CHECK(killable != nullptr);
+ std::lock_guard guard(mMutex);
+ const auto removedIter = std::remove(mObjects.begin(), mObjects.end(), killable);
+ mObjects.erase(removedIter);
+}
+
+nn::GeneralResult<DeathHandler> DeathHandler::create(sp<hidl::base::V1_0::IBase> object) {
+ if (object == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "utils::DeathHandler::create must have non-null object";
+ }
+ auto deathRecipient = sp<DeathRecipient>::make();
+
+ const auto ret = object->linkToDeath(deathRecipient, /*cookie=*/0);
+ const bool success = NN_TRY(handleTransportError(ret));
+ if (!success) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "IBase::linkToDeath returned false";
+ }
+
+ return DeathHandler(std::move(object), std::move(deathRecipient));
+}
+
+DeathHandler::DeathHandler(sp<hidl::base::V1_0::IBase> object, sp<DeathRecipient> deathRecipient)
+ : kObject(std::move(object)), kDeathRecipient(std::move(deathRecipient)) {
+ CHECK(kObject != nullptr);
+ CHECK(kDeathRecipient != nullptr);
+}
+
+DeathHandler::~DeathHandler() {
+ if (kObject != nullptr && kDeathRecipient != nullptr) {
+ const auto ret = kObject->unlinkToDeath(kDeathRecipient);
+ const auto maybeSuccess = handleTransportError(ret);
+ if (!maybeSuccess.has_value()) {
+ LOG(ERROR) << maybeSuccess.error().message;
+ } else if (!maybeSuccess.value()) {
+ LOG(ERROR) << "IBase::linkToDeath returned false";
+ }
+ }
+}
+
+[[nodiscard]] base::ScopeGuard<DeathHandler::Cleanup> DeathHandler::protectCallback(
+ IProtectedCallback* killable) const {
+ CHECK(killable != nullptr);
+ kDeathRecipient->add(killable);
+ return base::make_scope_guard(
+ [deathRecipient = kDeathRecipient, killable] { deathRecipient->remove(killable); });
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/src/ResilientBuffer.cpp b/neuralnetworks/utils/common/src/ResilientBuffer.cpp
new file mode 100644
index 0000000..984295b
--- /dev/null
+++ b/neuralnetworks/utils/common/src/ResilientBuffer.cpp
@@ -0,0 +1,75 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ResilientBuffer.h"
+
+#include <android-base/logging.h>
+#include <android-base/thread_annotations.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+nn::GeneralResult<std::shared_ptr<const ResilientBuffer>> ResilientBuffer::create(
+ Factory makeBuffer) {
+ if (makeBuffer == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "utils::ResilientBuffer::create must have non-empty makeBuffer";
+ }
+ auto buffer = NN_TRY(makeBuffer(/*blocking=*/true));
+ CHECK(buffer != nullptr);
+ return std::make_shared<const ResilientBuffer>(PrivateConstructorTag{}, std::move(makeBuffer),
+ std::move(buffer));
+}
+
+ResilientBuffer::ResilientBuffer(PrivateConstructorTag /*tag*/, Factory makeBuffer,
+ nn::SharedBuffer buffer)
+ : kMakeBuffer(std::move(makeBuffer)), mBuffer(std::move(buffer)) {
+ CHECK(kMakeBuffer != nullptr);
+ CHECK(mBuffer != nullptr);
+}
+
+nn::SharedBuffer ResilientBuffer::getBuffer() const {
+ std::lock_guard guard(mMutex);
+ return mBuffer;
+}
+nn::SharedBuffer ResilientBuffer::recover(const nn::IBuffer* /*failingBuffer*/,
+ bool /*blocking*/) const {
+ std::lock_guard guard(mMutex);
+ return mBuffer;
+}
+
+nn::Request::MemoryDomainToken ResilientBuffer::getToken() const {
+ return getBuffer()->getToken();
+}
+
+nn::GeneralResult<void> ResilientBuffer::copyTo(const nn::Memory& dst) const {
+ return getBuffer()->copyTo(dst);
+}
+
+nn::GeneralResult<void> ResilientBuffer::copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const {
+ return getBuffer()->copyFrom(src, dimensions);
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/src/ResilientDevice.cpp b/neuralnetworks/utils/common/src/ResilientDevice.cpp
new file mode 100644
index 0000000..95662d9
--- /dev/null
+++ b/neuralnetworks/utils/common/src/ResilientDevice.cpp
@@ -0,0 +1,236 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ResilientDevice.h"
+
+#include "ResilientBuffer.h"
+#include "ResilientPreparedModel.h"
+
+#include <android-base/logging.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+
+#include <algorithm>
+#include <memory>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+namespace {
+
+template <typename FnType>
+auto protect(const ResilientDevice& resilientDevice, const FnType& fn, bool blocking)
+ -> decltype(fn(*resilientDevice.getDevice())) {
+ auto device = resilientDevice.getDevice();
+ auto result = fn(*device);
+
+ // Immediately return if device is not dead.
+ if (result.has_value() || result.error().code != nn::ErrorStatus::DEAD_OBJECT) {
+ return result;
+ }
+
+ device = resilientDevice.recover(device.get(), blocking);
+ return fn(*device);
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const ResilientDevice>> ResilientDevice::create(
+ Factory makeDevice) {
+ if (makeDevice == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "utils::ResilientDevice::create must have non-empty makeDevice";
+ }
+ auto device = NN_TRY(makeDevice(/*blocking=*/true));
+ CHECK(device != nullptr);
+
+ auto name = device->getName();
+ auto versionString = device->getVersionString();
+ auto extensions = device->getSupportedExtensions();
+ auto capabilities = device->getCapabilities();
+
+ return std::make_shared<ResilientDevice>(PrivateConstructorTag{}, std::move(makeDevice),
+ std::move(name), std::move(versionString),
+ std::move(extensions), std::move(capabilities),
+ std::move(device));
+}
+
+ResilientDevice::ResilientDevice(PrivateConstructorTag /*tag*/, Factory makeDevice,
+ std::string name, std::string versionString,
+ std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities, nn::SharedDevice device)
+ : kMakeDevice(std::move(makeDevice)),
+ kName(std::move(name)),
+ kVersionString(std::move(versionString)),
+ kExtensions(std::move(extensions)),
+ kCapabilities(std::move(capabilities)),
+ mDevice(std::move(device)) {
+ CHECK(kMakeDevice != nullptr);
+ CHECK(mDevice != nullptr);
+}
+
+nn::SharedDevice ResilientDevice::getDevice() const {
+ std::lock_guard guard(mMutex);
+ return mDevice;
+}
+
+nn::SharedDevice ResilientDevice::recover(const nn::IDevice* failingDevice, bool blocking) const {
+ std::lock_guard guard(mMutex);
+
+ // Another caller updated the failing device.
+ if (mDevice.get() != failingDevice) {
+ return mDevice;
+ }
+
+ auto maybeDevice = kMakeDevice(blocking);
+ if (!maybeDevice.has_value()) {
+ const auto& [message, code] = maybeDevice.error();
+ LOG(ERROR) << "Failed to recover dead device with error " << code << ": " << message;
+ return mDevice;
+ }
+ auto device = std::move(maybeDevice).value();
+
+ // TODO(b/173081926): Instead of CHECKing to ensure the cache has not been changed, return an
+ // invalid/"null" IDevice object that always fails.
+ CHECK_EQ(kName, device->getName());
+ CHECK_EQ(kVersionString, device->getVersionString());
+ CHECK(kExtensions == device->getSupportedExtensions());
+ CHECK_EQ(kCapabilities, device->getCapabilities());
+
+ mDevice = std::move(device);
+ return mDevice;
+}
+
+const std::string& ResilientDevice::getName() const {
+ return kName;
+}
+
+const std::string& ResilientDevice::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version ResilientDevice::getFeatureLevel() const {
+ return getDevice()->getFeatureLevel();
+}
+
+nn::DeviceType ResilientDevice::getType() const {
+ return getDevice()->getType();
+}
+
+const std::vector<nn::Extension>& ResilientDevice::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& ResilientDevice::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> ResilientDevice::getNumberOfCacheFilesNeeded() const {
+ return getDevice()->getNumberOfCacheFilesNeeded();
+}
+
+nn::GeneralResult<void> ResilientDevice::wait() const {
+ const auto fn = [](const nn::IDevice& device) { return device.wait(); };
+ return protect(*this, fn, /*blocking=*/true);
+}
+
+nn::GeneralResult<std::vector<bool>> ResilientDevice::getSupportedOperations(
+ const nn::Model& model) const {
+ const auto fn = [&model](const nn::IDevice& device) {
+ return device.getSupportedOperations(model);
+ };
+ return protect(*this, fn, /*blocking=*/false);
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> ResilientDevice::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ auto self = shared_from_this();
+ ResilientPreparedModel::Factory makePreparedModel =
+ [device = std::move(self), model, preference, priority, deadline, modelCache, dataCache,
+ token](bool blocking) -> nn::GeneralResult<nn::SharedPreparedModel> {
+ return device->prepareModelInternal(blocking, model, preference, priority, deadline,
+ modelCache, dataCache, token);
+ };
+ return ResilientPreparedModel::create(std::move(makePreparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> ResilientDevice::prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ auto self = shared_from_this();
+ ResilientPreparedModel::Factory makePreparedModel =
+ [device = std::move(self), deadline, modelCache, dataCache,
+ token](bool blocking) -> nn::GeneralResult<nn::SharedPreparedModel> {
+ return device->prepareModelFromCacheInternal(blocking, deadline, modelCache, dataCache,
+ token);
+ };
+ return ResilientPreparedModel::create(std::move(makePreparedModel));
+}
+
+nn::GeneralResult<nn::SharedBuffer> ResilientDevice::allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const {
+ auto self = shared_from_this();
+ ResilientBuffer::Factory makeBuffer =
+ [device = std::move(self), desc, preparedModels, inputRoles,
+ outputRoles](bool blocking) -> nn::GeneralResult<nn::SharedBuffer> {
+ return device->allocateInternal(blocking, desc, preparedModels, inputRoles, outputRoles);
+ };
+ return ResilientBuffer::create(std::move(makeBuffer));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> ResilientDevice::prepareModelInternal(
+ bool blocking, const nn::Model& model, nn::ExecutionPreference preference,
+ nn::Priority priority, nn::OptionalTimePoint deadline,
+ const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ const auto fn = [&model, preference, priority, deadline, &modelCache, &dataCache,
+ token](const nn::IDevice& device) {
+ return device.prepareModel(model, preference, priority, deadline, modelCache, dataCache,
+ token);
+ };
+ return protect(*this, fn, blocking);
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> ResilientDevice::prepareModelFromCacheInternal(
+ bool blocking, nn::OptionalTimePoint deadline,
+ const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ const auto fn = [deadline, &modelCache, &dataCache, token](const nn::IDevice& device) {
+ return device.prepareModelFromCache(deadline, modelCache, dataCache, token);
+ };
+ return protect(*this, fn, blocking);
+}
+
+nn::GeneralResult<nn::SharedBuffer> ResilientDevice::allocateInternal(
+ bool blocking, const nn::BufferDesc& desc,
+ const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const {
+ const auto fn = [&desc, &preparedModels, &inputRoles, &outputRoles](const nn::IDevice& device) {
+ return device.allocate(desc, preparedModels, inputRoles, outputRoles);
+ };
+ return protect(*this, fn, blocking);
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp b/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp
new file mode 100644
index 0000000..1c9ecba
--- /dev/null
+++ b/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp
@@ -0,0 +1,85 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "ResilientPreparedModel.h"
+
+#include <android-base/logging.h>
+#include <android-base/thread_annotations.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+nn::GeneralResult<std::shared_ptr<const ResilientPreparedModel>> ResilientPreparedModel::create(
+ Factory makePreparedModel) {
+ if (makePreparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "utils::ResilientPreparedModel::create must have non-empty makePreparedModel";
+ }
+ auto preparedModel = NN_TRY(makePreparedModel(/*blocking=*/true));
+ CHECK(preparedModel != nullptr);
+ return std::make_shared<ResilientPreparedModel>(
+ PrivateConstructorTag{}, std::move(makePreparedModel), std::move(preparedModel));
+}
+
+ResilientPreparedModel::ResilientPreparedModel(PrivateConstructorTag /*tag*/,
+ Factory makePreparedModel,
+ nn::SharedPreparedModel preparedModel)
+ : kMakePreparedModel(std::move(makePreparedModel)), mPreparedModel(std::move(preparedModel)) {
+ CHECK(kMakePreparedModel != nullptr);
+ CHECK(mPreparedModel != nullptr);
+}
+
+nn::SharedPreparedModel ResilientPreparedModel::getPreparedModel() const {
+ std::lock_guard guard(mMutex);
+ return mPreparedModel;
+}
+
+nn::SharedPreparedModel ResilientPreparedModel::recover(
+ const nn::IPreparedModel* /*failingPreparedModel*/, bool /*blocking*/) const {
+ std::lock_guard guard(mMutex);
+ return mPreparedModel;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+ResilientPreparedModel::execute(const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const {
+ return getPreparedModel()->execute(request, measure, deadline, loopTimeoutDuration);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+ResilientPreparedModel::executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const {
+ return getPreparedModel()->executeFenced(request, waitFor, measure, deadline,
+ loopTimeoutDuration, timeoutDurationAfterFence);
+}
+
+std::any ResilientPreparedModel::getUnderlyingResource() const {
+ return getPreparedModel()->getUnderlyingResource();
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/service/Android.bp b/neuralnetworks/utils/service/Android.bp
new file mode 100644
index 0000000..87d27c7
--- /dev/null
+++ b/neuralnetworks/utils/service/Android.bp
@@ -0,0 +1,36 @@
+//
+// Copyright (C) 2020 The Android Open Source Project
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+// http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+//
+
+cc_library_static {
+ name: "neuralnetworks_utils_hal_service",
+ defaults: ["neuralnetworks_utils_defaults"],
+ srcs: ["src/*"],
+ local_include_dirs: ["include/nnapi/hal"],
+ export_include_dirs: ["include"],
+ static_libs: [
+ "neuralnetworks_types",
+ "neuralnetworks_utils_hal_1_0",
+ "neuralnetworks_utils_hal_1_1",
+ "neuralnetworks_utils_hal_1_2",
+ "neuralnetworks_utils_hal_1_3",
+ ],
+ shared_libs: [
+ "android.hardware.neuralnetworks@1.0",
+ "android.hardware.neuralnetworks@1.1",
+ "android.hardware.neuralnetworks@1.2",
+ "android.hardware.neuralnetworks@1.3",
+ ],
+}
diff --git a/neuralnetworks/utils/service/include/nnapi/hal/Service.h b/neuralnetworks/utils/service/include/nnapi/hal/Service.h
new file mode 100644
index 0000000..e339627
--- /dev/null
+++ b/neuralnetworks/utils/service/include/nnapi/hal/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Types.h>
+#include <memory>
+#include <vector>
+
+namespace android::nn::hal {
+
+std::vector<nn::SharedDevice> getDevices();
+
+} // namespace android::nn::hal
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_SERVICE_H
diff --git a/neuralnetworks/utils/service/src/Service.cpp b/neuralnetworks/utils/service/src/Service.cpp
new file mode 100644
index 0000000..a59549d
--- /dev/null
+++ b/neuralnetworks/utils/service/src/Service.cpp
@@ -0,0 +1,94 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <android-base/logging.h>
+#include <android/hardware/neuralnetworks/1.0/IDevice.h>
+#include <android/hardware/neuralnetworks/1.1/IDevice.h>
+#include <android/hardware/neuralnetworks/1.2/IDevice.h>
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <android/hidl/manager/1.2/IServiceManager.h>
+#include <hidl/ServiceManagement.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Service.h>
+#include <nnapi/hal/1.1/Service.h>
+#include <nnapi/hal/1.2/Service.h>
+#include <nnapi/hal/1.3/Service.h>
+
+#include <functional>
+#include <memory>
+#include <string>
+#include <type_traits>
+#include <unordered_set>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::service {
+namespace {
+
+using getDeviceFn = std::add_pointer_t<nn::GeneralResult<nn::SharedDevice>(const std::string&)>;
+
+void getDevicesForVersion(const std::string& descriptor, getDeviceFn getDevice,
+ std::vector<nn::SharedDevice>* devices,
+ std::unordered_set<std::string>* registeredDevices) {
+ CHECK(devices != nullptr);
+ CHECK(registeredDevices != nullptr);
+
+ const auto names = getAllHalInstanceNames(descriptor);
+ for (const auto& name : names) {
+ if (const auto [it, unregistered] = registeredDevices->insert(name); unregistered) {
+ auto maybeDevice = getDevice(name);
+ if (maybeDevice.has_value()) {
+ auto device = std::move(maybeDevice).value();
+ CHECK(device != nullptr);
+ devices->push_back(std::move(device));
+ } else {
+ LOG(ERROR) << "getDevice(" << name << ") failed with " << maybeDevice.error().code
+ << ": " << maybeDevice.error().message;
+ }
+ }
+ }
+}
+
+std::vector<nn::SharedDevice> getDevices() {
+ std::vector<nn::SharedDevice> devices;
+ std::unordered_set<std::string> registeredDevices;
+
+ getDevicesForVersion(V1_3::IDevice::descriptor, &V1_3::utils::getDevice, &devices,
+ ®isteredDevices);
+ getDevicesForVersion(V1_2::IDevice::descriptor, &V1_2::utils::getDevice, &devices,
+ ®isteredDevices);
+ getDevicesForVersion(V1_1::IDevice::descriptor, &V1_1::utils::getDevice, &devices,
+ ®isteredDevices);
+ getDevicesForVersion(V1_0::IDevice::descriptor, &V1_0::utils::getDevice, &devices,
+ ®isteredDevices);
+
+ return devices;
+}
+
+} // namespace
+} // namespace android::hardware::neuralnetworks::service
+
+namespace android::nn::hal {
+
+std::vector<nn::SharedDevice> getDevices() {
+ return hardware::neuralnetworks::service::getDevices();
+}
+
+} // namespace android::nn::hal