Merge TP1A.220120.003

Change-Id: Ie5eba313ee102e452f5f96942ed2f3a7bb4e8f01

1 files changed, 304 insertions, 0 deletions

diff --git a/neuralnetworks/utils/adapter/aidl/src/Device.cpp b/neuralnetworks/utils/adapter/aidl/src/Device.cpp
new file mode 100644
index 0000000000..763be7f3fa
--- /dev/null
+++ b/neuralnetworks/utils/adapter/aidl/src/Device.cpp
@@ -0,0 +1,304 @@
+/*
+ * Copyright (C) 2021 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 "Adapter.h"
+#include "Buffer.h"
+#include "PreparedModel.h"
+
+#include <aidl/android/hardware/neuralnetworks/BnDevice.h>
+#include <aidl/android/hardware/neuralnetworks/BufferDesc.h>
+#include <aidl/android/hardware/neuralnetworks/BufferRole.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceBuffer.h>
+#include <aidl/android/hardware/neuralnetworks/DeviceType.h>
+#include <aidl/android/hardware/neuralnetworks/ErrorStatus.h>
+#include <aidl/android/hardware/neuralnetworks/ExecutionPreference.h>
+#include <aidl/android/hardware/neuralnetworks/Extension.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelCallback.h>
+#include <aidl/android/hardware/neuralnetworks/IPreparedModelParcel.h>
+#include <aidl/android/hardware/neuralnetworks/Model.h>
+#include <aidl/android/hardware/neuralnetworks/NumberOfCacheFiles.h>
+#include <aidl/android/hardware/neuralnetworks/Priority.h>
+#include <android-base/logging.h>
+#include <android/binder_auto_utils.h>
+#include <android/binder_interface_utils.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/aidl/Conversions.h>
+
+#include <chrono>
+#include <memory>
+#include <string>
+#include <vector>
+
+namespace aidl::android::hardware::neuralnetworks::adapter {
+namespace {
+
+template <typename Type>
+auto convertInput(const Type& object) -> decltype(nn::convert(std::declval<Type>())) {
+    auto result = nn::convert(object);
+    if (!result.has_value()) {
+        result.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return result;
+}
+
+nn::Duration makeDuration(int64_t durationNs) {
+    return nn::Duration(std::chrono::nanoseconds(durationNs));
+}
+
+nn::GeneralResult<nn::OptionalTimePoint> makeOptionalTimePoint(int64_t durationNs) {
+    if (durationNs < -1) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid time point " << durationNs;
+    }
+    return durationNs < 0 ? nn::OptionalTimePoint{} : nn::TimePoint(makeDuration(durationNs));
+}
+
+nn::GeneralResult<nn::CacheToken> convertCacheToken(const std::vector<uint8_t>& token) {
+    nn::CacheToken nnToken;
+    if (token.size() != nnToken.size()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid token";
+    }
+    std::copy(token.begin(), token.end(), nnToken.begin());
+    return nnToken;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> downcast(const IPreparedModelParcel& preparedModel) {
+    if (preparedModel.preparedModel == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "preparedModel is nullptr";
+    }
+    if (preparedModel.preparedModel->isRemote()) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Cannot convert remote models";
+    }
+
+    // This static_cast is safe because adapter::PreparedModel is the only class that implements
+    // the IPreparedModel interface in the adapter service code.
+    const auto* casted = static_cast<const PreparedModel*>(preparedModel.preparedModel.get());
+    return casted->getUnderlyingPreparedModel();
+}
+
+nn::GeneralResult<std::vector<nn::SharedPreparedModel>> downcastAll(
+        const std::vector<IPreparedModelParcel>& preparedModels) {
+    std::vector<nn::SharedPreparedModel> canonical;
+    canonical.reserve(preparedModels.size());
+    for (const auto& preparedModel : preparedModels) {
+        canonical.push_back(NN_TRY(downcast(preparedModel)));
+    }
+    return canonical;
+}
+
+nn::GeneralResult<DeviceBuffer> allocate(const nn::IDevice& device, const BufferDesc& desc,
+                                         const std::vector<IPreparedModelParcel>& preparedModels,
+                                         const std::vector<BufferRole>& inputRoles,
+                                         const std::vector<BufferRole>& outputRoles) {
+    auto nnDesc = NN_TRY(convertInput(desc));
+    auto nnPreparedModels = NN_TRY(downcastAll(preparedModels));
+    auto nnInputRoles = NN_TRY(convertInput(inputRoles));
+    auto nnOutputRoles = NN_TRY(convertInput(outputRoles));
+
+    auto buffer = NN_TRY(device.allocate(nnDesc, nnPreparedModels, nnInputRoles, nnOutputRoles));
+    CHECK(buffer != nullptr);
+
+    const nn::Request::MemoryDomainToken token = buffer->getToken();
+    auto aidlBuffer = ndk::SharedRefBase::make<Buffer>(std::move(buffer));
+    return DeviceBuffer{.buffer = std::move(aidlBuffer), .token = static_cast<int32_t>(token)};
+}
+
+nn::GeneralResult<std::vector<bool>> getSupportedOperations(const nn::IDevice& device,
+                                                            const Model& model) {
+    const auto nnModel = NN_TRY(convertInput(model));
+    return device.getSupportedOperations(nnModel);
+}
+
+using PrepareModelResult = nn::GeneralResult<nn::SharedPreparedModel>;
+
+std::shared_ptr<PreparedModel> adaptPreparedModel(nn::SharedPreparedModel preparedModel) {
+    if (preparedModel == nullptr) {
+        return nullptr;
+    }
+    return ndk::SharedRefBase::make<PreparedModel>(std::move(preparedModel));
+}
+
+void notify(IPreparedModelCallback* callback, PrepareModelResult result) {
+    if (!result.has_value()) {
+        const auto& [message, status] = result.error();
+        LOG(ERROR) << message;
+        const auto aidlCode = utils::convert(status).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+    } else {
+        auto preparedModel = std::move(result).value();
+        auto aidlPreparedModel = adaptPreparedModel(std::move(preparedModel));
+        callback->notify(ErrorStatus::NONE, std::move(aidlPreparedModel));
+    }
+}
+
+nn::GeneralResult<void> prepareModel(const nn::SharedDevice& device, const Executor& executor,
+                                     const Model& model, ExecutionPreference preference,
+                                     Priority priority, int64_t deadlineNs,
+                                     const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                                     const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                                     const std::vector<uint8_t>& token,
+                                     const std::shared_ptr<IPreparedModelCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    auto nnModel = NN_TRY(convertInput(model));
+    const auto nnPreference = NN_TRY(convertInput(preference));
+    const auto nnPriority = NN_TRY(convertInput(priority));
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    auto nnModelCache = NN_TRY(convertInput(modelCache));
+    auto nnDataCache = NN_TRY(convertInput(dataCache));
+    const auto nnToken = NN_TRY(convertCacheToken(token));
+
+    Task task = [device, nnModel = std::move(nnModel), nnPreference, nnPriority, nnDeadline,
+                 nnModelCache = std::move(nnModelCache), nnDataCache = std::move(nnDataCache),
+                 nnToken, callback] {
+        auto result = device->prepareModel(nnModel, nnPreference, nnPriority, nnDeadline,
+                                           nnModelCache, nnDataCache, nnToken);
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), nnDeadline);
+
+    return {};
+}
+
+nn::GeneralResult<void> prepareModelFromCache(
+        const nn::SharedDevice& device, const Executor& executor, int64_t deadlineNs,
+        const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+        const std::vector<ndk::ScopedFileDescriptor>& dataCache, const std::vector<uint8_t>& token,
+        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    const auto nnDeadline = NN_TRY(makeOptionalTimePoint(deadlineNs));
+    auto nnModelCache = NN_TRY(convertInput(modelCache));
+    auto nnDataCache = NN_TRY(convertInput(dataCache));
+    const auto nnToken = NN_TRY(convertCacheToken(token));
+
+    auto task = [device, nnDeadline, nnModelCache = std::move(nnModelCache),
+                 nnDataCache = std::move(nnDataCache), nnToken, callback] {
+        auto result = device->prepareModelFromCache(nnDeadline, nnModelCache, nnDataCache, nnToken);
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), nnDeadline);
+
+    return {};
+}
+
+}  // namespace
+
+Device::Device(::android::nn::SharedDevice device, Executor executor)
+    : kDevice(std::move(device)), kExecutor(std::move(executor)) {
+    CHECK(kDevice != nullptr);
+    CHECK(kExecutor != nullptr);
+}
+
+ndk::ScopedAStatus Device::allocate(const BufferDesc& desc,
+                                    const std::vector<IPreparedModelParcel>& preparedModels,
+                                    const std::vector<BufferRole>& inputRoles,
+                                    const std::vector<BufferRole>& outputRoles,
+                                    DeviceBuffer* buffer) {
+    auto result = adapter::allocate(*kDevice, desc, preparedModels, inputRoles, outputRoles);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *buffer = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getCapabilities(Capabilities* capabilities) {
+    *capabilities = utils::convert(kDevice->getCapabilities()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getNumberOfCacheFilesNeeded(NumberOfCacheFiles* numberOfCacheFiles) {
+    const auto [numModelCache, numDataCache] = kDevice->getNumberOfCacheFilesNeeded();
+    *numberOfCacheFiles = NumberOfCacheFiles{.numModelCache = static_cast<int32_t>(numModelCache),
+                                             .numDataCache = static_cast<int32_t>(numDataCache)};
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getSupportedExtensions(std::vector<Extension>* extensions) {
+    *extensions = utils::convert(kDevice->getSupportedExtensions()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getSupportedOperations(const Model& model,
+                                                  std::vector<bool>* supported) {
+    auto result = adapter::getSupportedOperations(*kDevice, model);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    *supported = std::move(result).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getType(DeviceType* deviceType) {
+    *deviceType = utils::convert(kDevice->getType()).value();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::getVersionString(std::string* version) {
+    *version = kDevice->getVersionString();
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::prepareModel(const Model& model, ExecutionPreference preference,
+                                        Priority priority, int64_t deadlineNs,
+                                        const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+                                        const std::vector<ndk::ScopedFileDescriptor>& dataCache,
+                                        const std::vector<uint8_t>& token,
+                                        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    const auto result = adapter::prepareModel(kDevice, kExecutor, model, preference, priority,
+                                              deadlineNs, modelCache, dataCache, token, callback);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+ndk::ScopedAStatus Device::prepareModelFromCache(
+        int64_t deadlineNs, const std::vector<ndk::ScopedFileDescriptor>& modelCache,
+        const std::vector<ndk::ScopedFileDescriptor>& dataCache, const std::vector<uint8_t>& token,
+        const std::shared_ptr<IPreparedModelCallback>& callback) {
+    const auto result = adapter::prepareModelFromCache(kDevice, kExecutor, deadlineNs, modelCache,
+                                                       dataCache, token, callback);
+    if (!result.has_value()) {
+        const auto& [message, code] = result.error();
+        const auto aidlCode = utils::convert(code).value_or(ErrorStatus::GENERAL_FAILURE);
+        callback->notify(aidlCode, nullptr);
+        return ndk::ScopedAStatus::fromServiceSpecificErrorWithMessage(
+                static_cast<int32_t>(aidlCode), message.c_str());
+    }
+    return ndk::ScopedAStatus::ok();
+}
+
+}  // namespace aidl::android::hardware::neuralnetworks::adapter