Implement NNAPI canonical interfaces am: 4b276a767b am: e91a56a78f

Original change: https://android-review.googlesource.com/c/platform/hardware/interfaces/+/1501391

Change-Id: I7d9c31e4e9daaa82eaad9b00e71ba486e0b6e46d

neuralnetworks/1.0/utils/Android.bp

@@ -20,6 +20,7 @@ cc_library_static {
     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",

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

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
 

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

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

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

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 @@ constexpr auto kVersion = nn::Version::ANDROID_OC_MR1;
 
 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 @@ bool valid(const Type& halObject) {
 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;
 }

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

neuralnetworks/1.0/utils/src/Conversions.cpp

@@ -52,7 +52,7 @@ template <typename Input>
 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 @@ Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments
 
 }  // 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<Capabilities> convert(const hal::V1_0::Capabilities& capabilities) {
     };
 }
 
-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<DataLocation> convert(const hal::V1_0::DataLocation& location) {
     };
 }
 
-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<Operand> convert(const hal::V1_0::Operand& operand) {
     };
 }
 
-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<Operation> convert(const hal::V1_0::Operation& operation) {
     };
 }
 
-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 @@ Result<Model> convert(const hal::V1_0::Model& model) {
     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<Model> convert(const hal::V1_0::Model& model) {
     };
 }
 
-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::Argument> convert(const hal::V1_0::RequestArgument& argument) {
     };
 }
 
-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<Request> convert(const hal::V1_0::Request& request) {
     };
 }
 
-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 @@ Result<ErrorStatus> convert(const hal::V1_0::ErrorStatus& status) {
         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 @@ template <typename Input>
 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 @@ nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& argum
 
 }  // 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<Capabilities> convert(const nn::Capabilities& capabilities) {
     };
 }
 
-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<DataLocation> convert(const nn::DataLocation& location) {
     };
 }
 
-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<Operand> convert(const nn::Operand& operand) {
     };
 }
 
-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<Operation> convert(const nn::Operation& operation) {
     };
 }
 
-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<Model> convert(const nn::Model& model) {
     };
 }
 
-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<RequestArgument> convert(const nn::Request::Argument& requestArgument
     };
 }
 
-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<Request> convert(const nn::Request& request) {
     };
 }
 
-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:

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

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

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

neuralnetworks/1.1/utils/Android.bp

@@ -20,6 +20,7 @@ cc_library_static {
     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",

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
 

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

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

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 @@ constexpr auto kVersion = nn::Version::ANDROID_P;
 
 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 @@ bool valid(const Type& halObject) {
 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;
 }

neuralnetworks/1.1/utils/src/Conversions.cpp

@@ -42,7 +42,7 @@ template <typename Input>
 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 @@ Result<std::vector<convertOutput<Type>>> convert(const hidl_vec<Type>& arguments
 
 }  // 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<Capabilities> convert(const hal::V1_1::Capabilities& capabilities) {
     };
 }
 
-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<Operation> convert(const hal::V1_1::Operation& operation) {
     };
 }
 
-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 @@ Result<Model> convert(const hal::V1_1::Model& model) {
     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<Model> convert(const hal::V1_1::Model& model) {
     };
 }
 
-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 @@ namespace {
 
 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 @@ template <typename Input>
 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 @@ nn::Result<hidl_vec<convertOutput<Type>>> convert(const std::vector<Type>& argum
 
 }  // 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<Capabilities> convert(const nn::Capabilities& capabilities) {
     };
 }
 
-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<Operation> convert(const nn::Operation& operation) {
     };
 }
 
-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<Model> convert(const nn::Model& model) {
     };
 }
 
-nn::Result<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference) {
+nn::GeneralResult<ExecutionPreference> convert(const nn::ExecutionPreference& executionPreference) {
     return static_cast<ExecutionPreference>(executionPreference);
 }
 

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

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

neuralnetworks/1.2/utils/Android.bp

@@ -20,6 +20,7 @@ cc_library_static {
     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",

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

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
 

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

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

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

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 @@ constexpr auto kVersion = nn::Version::ANDROID_Q;
 
 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 @@ bool valid(const Type& halObject) {
 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;
 }

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

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 @@ template <typename Input>
 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 @@ Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& argume
 }
 
 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 @@ Result<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
                 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 @@ Result<Capabilities> convert(const hal::V1_2::Capabilities& capabilities) {
             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> convert(const hal::V1_2::Capabilities& capabilities) {
     };
 }
 
-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<Capabilities::OperandPerformance> convert(
     };
 }
 
-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<Operation> convert(const hal::V1_2::Operation& operation) {
     };
 }
 
-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::SymmPerChannelQuantParams> convert(
     };
 }
 
-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> convert(const hal::V1_2::Operand& operand) {
     };
 }
 
-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 @@ Result<Operand::ExtraParams> convert(const hal::V1_2::Operand::ExtraParams& extr
         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 @@ Result<Model> convert(const hal::V1_2::Model& model) {
     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> convert(const hal::V1_2::Model& model) {
     };
 }
 
-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<Model::ExtensionNameAndPrefix> convert(
     };
 }
 
-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<Extension::OperandTypeInformation> convert(
     };
 }
 
-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 @@ namespace {
 
 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 @@ template <typename Input>
 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 @@ nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& ar
 }
 
 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 @@ nn::Result<Operand::ExtraParams> makeExtraParams(const nn::Operand::ExtensionPar
 
 }  // 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> convert(const nn::Capabilities& capabilities) {
     };
 }
 
-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<Capabilities::OperandPerformance> convert(
     };
 }
 
-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<Operation> convert(const nn::Operation& operation) {
     };
 }
 
-nn::Result<SymmPerChannelQuantParams> convert(
+nn::GeneralResult<SymmPerChannelQuantParams> convert(
         const nn::Operand::SymmPerChannelQuantParams& symmPerChannelQuantParams) {
     return SymmPerChannelQuantParams{
             .scales = symmPerChannelQuantParams.scales,
@@ -399,7 +405,7 @@ nn::Result<SymmPerChannelQuantParams> convert(
     };
 }
 
-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> convert(const nn::Operand& operand) {
     };
 }
 
-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> convert(const nn::Model& model) {
     };
 }
 
-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<Model::ExtensionNameAndPrefix> convert(
     };
 }
 
-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<Extension::OperandTypeInformation> convert(
     };
 }
 
-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);
 }
 

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

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

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

neuralnetworks/1.3/utils/Android.bp

@@ -20,6 +20,7 @@ cc_library_static {
     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",

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

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

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
 

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

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

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

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 @@ constexpr auto kVersion = nn::Version::ANDROID_R;
 
 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 @@ bool valid(const Type& halObject) {
 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;
 }

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

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

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 @@ template <typename Input>
 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 @@ Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& argume
 }
 
 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 @@ Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
                 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> convert(const hal::V1_3::Capabilities& capabilities) {
     };
 }
 
-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<Capabilities::OperandPerformance> convert(
     };
 }
 
-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<Operation> convert(const hal::V1_3::Operation& operation) {
     };
 }
 
-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<Operand> convert(const hal::V1_3::Operand& operand) {
     };
 }
 
-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> convert(const hal::V1_3::Model& model) {
     };
 }
 
-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 @@ Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
     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<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
     };
 }
 
-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<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
     };
 }
 
-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> convert(const hal::V1_3::Request& request) {
     };
 }
 
-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 @@ Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memory
         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 @@ Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTi
         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 @@ Result<OptionalTimeoutDuration> convert(
         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 @@ Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
         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 @@ namespace {
 
 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 @@ template <typename Input>
 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 @@ nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& ar
 }
 
 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> convert(const nn::Capabilities& capabilities) {
     };
 }
 
-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<Capabilities::OperandPerformance> convert(
     };
 }
 
-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<Operation> convert(const nn::Operation& operation) {
     };
 }
 
-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<Operand> convert(const nn::Operand& operand) {
     };
 }
 
-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<Model> convert(const nn::Model& model) {
     };
 }
 
-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<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
     };
 }
 
-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<BufferRole> convert(const nn::BufferRole& bufferRole) {
     };
 }
 
-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> convert(const nn::Request& request) {
     };
 }
 
-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 @@ nn::Result<OptionalTimeoutDuration> convert(
     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<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) {
     return convertVec(bufferRoles);
 }
 

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

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

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

neuralnetworks/utils/common/Android.bp

@@ -20,6 +20,7 @@ cc_library_static {
     srcs: ["src/*"],
     local_include_dirs: ["include/nnapi/hal"],
     export_include_dirs: ["include"],
+    cflags: ["-Wthread-safety"],
     static_libs: [
         "neuralnetworks_types",
     ],

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::Model& model);
 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);

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

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

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

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

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

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

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 @@ bool hasNoPointerData(const nn::Request& request) {
     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 @@ nn::Result<nn::Model> flushDataFromPointerToShared(const nn::Model& model) {
         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 @@ nn::Result<nn::Request> flushDataFromPointerToShared(const nn::Request& request)
         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());

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

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

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

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

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",
+    ],
+}

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

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,
+                         &registeredDevices);
+    getDevicesForVersion(V1_2::IDevice::descriptor, &V1_2::utils::getDevice, &devices,
+                         &registeredDevices);
+    getDevicesForVersion(V1_1::IDevice::descriptor, &V1_1::utils::getDevice, &devices,
+                         &registeredDevices);
+    getDevicesForVersion(V1_0::IDevice::descriptor, &V1_0::utils::getDevice, &devices,
+                         &registeredDevices);
+
+    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