Merge TP1A.220120.003

Change-Id: Ie5eba313ee102e452f5f96942ed2f3a7bb4e8f01

1 files changed, 433 insertions, 0 deletions

diff --git a/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
new file mode 100644
index 0000000000..71060d5ca7
--- /dev/null
+++ b/neuralnetworks/utils/adapter/hidl/src/PreparedModel.cpp
@@ -0,0 +1,433 @@
+/*
+ * 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 "Burst.h"
+
+#include <android-base/logging.h>
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IBurstCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IFencedExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/Validation.h>
+#include <nnapi/hal/1.0/Utils.h>
+#include <nnapi/hal/1.2/Utils.h>
+#include <nnapi/hal/1.3/Conversions.h>
+#include <nnapi/hal/1.3/Utils.h>
+
+#include <memory>
+#include <thread>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
+// lifetimes across processes and for protecting asynchronous calls across HIDL.
+
+namespace 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::GeneralResult<nn::Version> validateRequestForModel(const nn::Request& request,
+                                                       const nn::Model& model) {
+    nn::GeneralResult<nn::Version> version = nn::validateRequestForModel(request, model);
+    if (!version.ok()) {
+        version.error().code = nn::ErrorStatus::INVALID_ARGUMENT;
+    }
+    return version;
+}
+
+class FencedExecutionCallback final : public V1_3::IFencedExecutionCallback {
+  public:
+    explicit FencedExecutionCallback(const nn::ExecuteFencedInfoCallback& callback)
+        : kCallback(callback) {
+        CHECK(callback != nullptr);
+    }
+
+    Return<void> getExecutionInfo(getExecutionInfo_cb cb) override {
+        const auto result = kCallback();
+        if (!result.has_value()) {
+            const auto& [message, code] = result.error();
+            const auto status =
+                    V1_3::utils::convert(code).value_or(V1_3::ErrorStatus::GENERAL_FAILURE);
+            LOG(ERROR) << message;
+            cb(status, V1_2::utils::kNoTiming, V1_2::utils::kNoTiming);
+            return Void();
+        }
+        const auto [timingLaunched, timingFenced] = result.value();
+        const auto hidlTimingLaunched = V1_3::utils::convert(timingLaunched).value();
+        const auto hidlTimingFenced = V1_3::utils::convert(timingFenced).value();
+        cb(V1_3::ErrorStatus::NONE, hidlTimingLaunched, hidlTimingFenced);
+        return Void();
+    }
+
+  private:
+    const nn::ExecuteFencedInfoCallback kCallback;
+};
+
+using ExecutionResult = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+void notify(V1_0::IExecutionCallback* callback, nn::ErrorStatus status,
+            const std::vector<nn::OutputShape>& /*outputShapes*/, const nn::Timing& /*timing*/) {
+    if (callback != nullptr) {
+        const auto hidlStatus = V1_0::utils::convert(status).value();
+        const auto ret = callback->notify(hidlStatus);
+        if (!ret.isOk()) {
+            LOG(ERROR) << "V1_0::IExecutionCallback::notify failed with " << ret.description();
+        }
+    }
+}
+
+void notify(V1_2::IExecutionCallback* callback, nn::ErrorStatus status,
+            const std::vector<nn::OutputShape>& outputShapes, const nn::Timing& timing) {
+    if (callback != nullptr) {
+        const auto hidlStatus = V1_2::utils::convert(status).value();
+        const auto hidlOutputShapes = V1_2::utils::convert(outputShapes).value();
+        const auto hidlTiming = V1_2::utils::convert(timing).value();
+        const auto ret = callback->notify_1_2(hidlStatus, hidlOutputShapes, hidlTiming);
+        if (!ret.isOk()) {
+            LOG(ERROR) << "V1_2::IExecutionCallback::notify_1_2 failed with " << ret.description();
+        }
+    }
+}
+
+void notify(V1_3::IExecutionCallback* callback, nn::ErrorStatus status,
+            const std::vector<nn::OutputShape>& outputShapes, const nn::Timing& timing) {
+    if (callback != nullptr) {
+        const auto hidlStatus = V1_3::utils::convert(status).value();
+        const auto hidlOutputShapes = V1_3::utils::convert(outputShapes).value();
+        const auto hidlTiming = V1_3::utils::convert(timing).value();
+        const auto ret = callback->notify_1_3(hidlStatus, hidlOutputShapes, hidlTiming);
+        if (!ret.isOk()) {
+            LOG(ERROR) << "V1_3::IExecutionCallback::notify_1_3 failed with " << ret.description();
+        }
+    }
+}
+
+template <typename CallbackType>
+void notify(CallbackType* callback, ExecutionResult result) {
+    if (!result.has_value()) {
+        const auto [message, status, outputShapes] = std::move(result).error();
+        LOG(ERROR) << message;
+        notify(callback, status, outputShapes, {});
+    } else {
+        const auto [outputShapes, timing] = std::move(result).value();
+        notify(callback, nn::ErrorStatus::NONE, outputShapes, timing);
+    }
+}
+
+nn::GeneralResult<void> execute(const nn::SharedPreparedModel& preparedModel,
+                                const Executor& executor, const V1_0::Request& request,
+                                const sp<V1_0::IExecutionCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    auto nnRequest = NN_TRY(convertInput(request));
+
+    const std::any resource = preparedModel->getUnderlyingResource();
+    if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
+        CHECK(*model != nullptr);
+        NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+    }
+
+    Task task = [preparedModel, nnRequest = std::move(nnRequest), callback] {
+        auto result = preparedModel->execute(nnRequest, nn::MeasureTiming::NO, {}, {});
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), {});
+
+    return {};
+}
+
+nn::GeneralResult<void> execute_1_2(const nn::SharedPreparedModel& preparedModel,
+                                    const Executor& executor, const V1_0::Request& request,
+                                    V1_2::MeasureTiming measure,
+                                    const sp<V1_2::IExecutionCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasure = NN_TRY(convertInput(measure));
+
+    const std::any resource = preparedModel->getUnderlyingResource();
+    if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
+        CHECK(*model != nullptr);
+        NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+    }
+
+    Task task = [preparedModel, nnRequest = std::move(nnRequest), nnMeasure, callback] {
+        auto result = preparedModel->execute(nnRequest, nnMeasure, {}, {});
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), {});
+
+    return {};
+}
+
+nn::GeneralResult<void> execute_1_3(const nn::SharedPreparedModel& preparedModel,
+                                    const Executor& executor, const V1_3::Request& request,
+                                    V1_2::MeasureTiming measure,
+                                    const V1_3::OptionalTimePoint& deadline,
+                                    const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
+                                    const sp<V1_3::IExecutionCallback>& callback) {
+    if (callback.get() == nullptr) {
+        return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT) << "Invalid callback";
+    }
+
+    auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasure = NN_TRY(convertInput(measure));
+    const auto nnDeadline = NN_TRY(convertInput(deadline));
+    const auto nnLoopTimeoutDuration = NN_TRY(convertInput(loopTimeoutDuration));
+
+    const std::any resource = preparedModel->getUnderlyingResource();
+    if (const auto* model = std::any_cast<const nn::Model*>(&resource)) {
+        CHECK(*model != nullptr);
+        NN_TRY(adapter::validateRequestForModel(nnRequest, **model));
+    }
+
+    Task task = [preparedModel, nnRequest = std::move(nnRequest), nnMeasure, nnDeadline,
+                 nnLoopTimeoutDuration, callback] {
+        auto result =
+                preparedModel->execute(nnRequest, nnMeasure, nnDeadline, nnLoopTimeoutDuration);
+        notify(callback.get(), std::move(result));
+    };
+    executor(std::move(task), nnDeadline);
+
+    return {};
+}
+
+nn::ExecutionResult<std::pair<hidl_vec<V1_2::OutputShape>, V1_2::Timing>> executeSynchronously(
+        const nn::SharedPreparedModel& preparedModel, const V1_0::Request& request,
+        V1_2::MeasureTiming measure) {
+    const auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasure = NN_TRY(convertInput(measure));
+
+    const auto [outputShapes, timing] =
+            NN_TRY(preparedModel->execute(nnRequest, nnMeasure, {}, {}));
+
+    auto hidlOutputShapes = NN_TRY(V1_2::utils::convert(outputShapes));
+    const auto hidlTiming = NN_TRY(V1_2::utils::convert(timing));
+    return std::make_pair(std::move(hidlOutputShapes), hidlTiming);
+}
+
+nn::ExecutionResult<std::pair<hidl_vec<V1_2::OutputShape>, V1_2::Timing>> executeSynchronously_1_3(
+        const nn::SharedPreparedModel& preparedModel, const V1_3::Request& request,
+        V1_2::MeasureTiming measure, const V1_3::OptionalTimePoint& deadline,
+        const V1_3::OptionalTimeoutDuration& loopTimeoutDuration) {
+    const auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnMeasure = NN_TRY(convertInput(measure));
+    const auto nnDeadline = NN_TRY(convertInput(deadline));
+    const auto nnLoopTimeoutDuration = NN_TRY(convertInput(loopTimeoutDuration));
+
+    const auto [outputShapes, timing] =
+            NN_TRY(preparedModel->execute(nnRequest, nnMeasure, nnDeadline, nnLoopTimeoutDuration));
+
+    auto hidlOutputShapes = NN_TRY(V1_3::utils::convert(outputShapes));
+    const auto hidlTiming = NN_TRY(V1_3::utils::convert(timing));
+    return std::make_pair(std::move(hidlOutputShapes), hidlTiming);
+}
+
+nn::GeneralResult<std::vector<nn::SyncFence>> convertSyncFences(
+        const hidl_vec<hidl_handle>& handles) {
+    auto nnHandles = NN_TRY(convertInput(handles));
+    std::vector<nn::SyncFence> syncFences;
+    syncFences.reserve(handles.size());
+    for (auto&& handle : nnHandles) {
+        if (auto syncFence = nn::SyncFence::create(std::move(handle)); !syncFence.ok()) {
+            return nn::error(nn::ErrorStatus::INVALID_ARGUMENT) << std::move(syncFence).error();
+        } else {
+            syncFences.push_back(std::move(syncFence).value());
+        }
+    }
+    return syncFences;
+}
+
+nn::GeneralResult<sp<V1_2::IBurstContext>> configureExecutionBurst(
+        const nn::SharedPreparedModel& preparedModel, const sp<V1_2::IBurstCallback>& callback,
+        const MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel,
+        const MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel) {
+    auto burstExecutor = NN_TRY(preparedModel->configureExecutionBurst());
+    return Burst::create(callback, requestChannel, resultChannel, std::move(burstExecutor),
+                         V1_2::utils::getBurstServerPollingTimeWindow());
+}
+
+nn::GeneralResult<std::pair<hidl_handle, sp<V1_3::IFencedExecutionCallback>>> executeFenced(
+        const nn::SharedPreparedModel& preparedModel, const V1_3::Request& request,
+        const hidl_vec<hidl_handle>& waitFor, V1_2::MeasureTiming measure,
+        const V1_3::OptionalTimePoint& deadline,
+        const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
+        const V1_3::OptionalTimeoutDuration& duration) {
+    const auto nnRequest = NN_TRY(convertInput(request));
+    const auto nnWaitFor = NN_TRY(convertSyncFences(waitFor));
+    const auto nnMeasure = NN_TRY(convertInput(measure));
+    const auto nnDeadline = NN_TRY(convertInput(deadline));
+    const auto nnLoopTimeoutDuration = NN_TRY(convertInput(loopTimeoutDuration));
+    const auto nnDuration = NN_TRY(convertInput(duration));
+
+    auto [syncFence, executeFencedCallback] = NN_TRY(preparedModel->executeFenced(
+            nnRequest, nnWaitFor, nnMeasure, nnDeadline, nnLoopTimeoutDuration, nnDuration));
+
+    auto hidlSyncFence = NN_TRY(V1_3::utils::convert(syncFence.getSharedHandle()));
+    auto hidlExecuteFencedCallback = sp<FencedExecutionCallback>::make(executeFencedCallback);
+    return std::make_pair(std::move(hidlSyncFence), std::move(hidlExecuteFencedCallback));
+}
+
+}  // namespace
+
+PreparedModel::PreparedModel(nn::SharedPreparedModel preparedModel, Executor executor)
+    : kPreparedModel(std::move(preparedModel)), kExecutor(std::move(executor)) {
+    CHECK(kPreparedModel != nullptr);
+    CHECK(kExecutor != nullptr);
+}
+
+nn::SharedPreparedModel PreparedModel::getUnderlyingPreparedModel() const {
+    return kPreparedModel;
+}
+
+Return<V1_0::ErrorStatus> PreparedModel::execute(const V1_0::Request& request,
+                                                 const sp<V1_0::IExecutionCallback>& callback) {
+    auto result = adapter::execute(kPreparedModel, kExecutor, request, callback);
+    if (!result.has_value()) {
+        auto [message, code] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::execute failed with " << code << ": " << message;
+        notify(callback.get(), code, {}, {});
+        return V1_0::utils::convert(code).value();
+    }
+    return V1_0::ErrorStatus::NONE;
+}
+
+Return<V1_0::ErrorStatus> PreparedModel::execute_1_2(const V1_0::Request& request,
+                                                     V1_2::MeasureTiming measure,
+                                                     const sp<V1_2::IExecutionCallback>& callback) {
+    auto result = adapter::execute_1_2(kPreparedModel, kExecutor, request, measure, callback);
+    if (!result.has_value()) {
+        auto [message, code] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::execute_1_2 failed with " << code << ": " << message;
+        notify(callback.get(), code, {}, {});
+        return V1_2::utils::convert(code).value();
+    }
+    return V1_0::ErrorStatus::NONE;
+}
+
+Return<V1_3::ErrorStatus> PreparedModel::execute_1_3(
+        const V1_3::Request& request, V1_2::MeasureTiming measure,
+        const V1_3::OptionalTimePoint& deadline,
+        const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
+        const sp<V1_3::IExecutionCallback>& callback) {
+    auto result = adapter::execute_1_3(kPreparedModel, kExecutor, request, measure, deadline,
+                                       loopTimeoutDuration, callback);
+    if (!result.has_value()) {
+        auto [message, code] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::execute_1_3 failed with " << code << ": " << message;
+        notify(callback.get(), code, {}, {});
+        return V1_3::utils::convert(code).value();
+    }
+    return V1_3::ErrorStatus::NONE;
+}
+
+Return<void> PreparedModel::executeSynchronously(const V1_0::Request& request,
+                                                 V1_2::MeasureTiming measure,
+                                                 executeSynchronously_cb cb) {
+    auto result = adapter::executeSynchronously(kPreparedModel, request, measure);
+    if (!result.has_value()) {
+        auto [message, code, outputShapes] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::executeSynchronously failed with " << code << ": "
+                   << message;
+        cb(V1_2::utils::convert(code).value(), V1_2::utils::convert(outputShapes).value(),
+           V1_2::utils::kNoTiming);
+        return Void();
+    }
+    auto [outputShapes, timing] = std::move(result).value();
+    cb(V1_0::ErrorStatus::NONE, outputShapes, timing);
+    return Void();
+}
+
+Return<void> PreparedModel::executeSynchronously_1_3(
+        const V1_3::Request& request, V1_2::MeasureTiming measure,
+        const V1_3::OptionalTimePoint& deadline,
+        const V1_3::OptionalTimeoutDuration& loopTimeoutDuration, executeSynchronously_1_3_cb cb) {
+    auto result = adapter::executeSynchronously_1_3(kPreparedModel, request, measure, deadline,
+                                                    loopTimeoutDuration);
+    if (!result.has_value()) {
+        auto [message, code, outputShapes] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::executeSynchronously_1_3 failed with " << code
+                   << ": " << message;
+        cb(V1_3::utils::convert(code).value(), V1_3::utils::convert(outputShapes).value(),
+           V1_2::utils::kNoTiming);
+        return Void();
+    }
+    auto [outputShapes, timing] = std::move(result).value();
+    cb(V1_3::ErrorStatus::NONE, outputShapes, timing);
+    return Void();
+}
+
+Return<void> PreparedModel::configureExecutionBurst(
+        const sp<V1_2::IBurstCallback>& callback,
+        const MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel,
+        const MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel,
+        configureExecutionBurst_cb cb) {
+    auto result = adapter::configureExecutionBurst(kPreparedModel, callback, requestChannel,
+                                                   resultChannel);
+    if (!result.has_value()) {
+        auto [message, code] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::configureExecutionBurst failed with " << code << ": "
+                   << message;
+        cb(V1_2::utils::convert(code).value(), nullptr);
+        return Void();
+    }
+    auto burstContext = std::move(result).value();
+    cb(V1_0::ErrorStatus::NONE, std::move(burstContext));
+    return Void();
+}
+
+Return<void> PreparedModel::executeFenced(const V1_3::Request& request,
+                                          const hidl_vec<hidl_handle>& waitFor,
+                                          V1_2::MeasureTiming measure,
+                                          const V1_3::OptionalTimePoint& deadline,
+                                          const V1_3::OptionalTimeoutDuration& loopTimeoutDuration,
+                                          const V1_3::OptionalTimeoutDuration& duration,
+                                          executeFenced_cb callback) {
+    auto result = adapter::executeFenced(kPreparedModel, request, waitFor, measure, deadline,
+                                         loopTimeoutDuration, duration);
+    if (!result.has_value()) {
+        auto [message, code] = std::move(result).error();
+        LOG(ERROR) << "adapter::PreparedModel::executeFenced failed with " << code << ": "
+                   << message;
+        callback(V1_3::utils::convert(code).value(), {}, nullptr);
+        return Void();
+    }
+    auto [syncFence, executeFencedCallback] = std::move(result).value();
+    callback(V1_3::ErrorStatus::NONE, syncFence, executeFencedCallback);
+    return Void();
+}
+
+}  // namespace android::hardware::neuralnetworks::adapter