Implement NNAPI canonical interfaces
This CL implements the canonical IDevice, IPreparedModel, and IBuffer
interfaces for the 1.0, 1.1, 1.2, and 1.3 NN HIDL HAL interfaces.
Further, it introduces "Resilient" adapter interfaces to automatically
retrieve a handle to a recovered interface object after it has died and
rebooted.
This CL also updates the conversion code from returning nn::Result to
nn::GeneralResult, which includes a ErrorStatus code in the case of an
error.
Finally, this CL introduces a new static library
neuralnetworks_utils_hal_service which consists of a single function
::android::nn::hal::getDevices which can be used by the NNAPI runtime to
retrieve the HIDL services without knowing the underlying HIDL types.
Bug: 160668438
Test: mma
Test: NeuralNetworksTest_static
Change-Id: Iec6ae739df196b4034ffb35ea76781fd541ffec3
Merged-In: Iec6ae739df196b4034ffb35ea76781fd541ffec3
(cherry picked from commit 3670c385c4b12aef975ab67e5d2b0f5fe79134c2)
diff --git a/neuralnetworks/1.3/utils/src/PreparedModel.cpp b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..df9b280
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
@@ -0,0 +1,267 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
+ const hidl_vec<V1_2::OutputShape>& outputShapes, const V1_2::Timing& timing) {
+ return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
+}
+
+nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
+ const std::vector<nn::SyncFence>& syncFences) {
+ hidl_vec<hidl_handle> handles(syncFences.size());
+ for (size_t i = 0; i < syncFences.size(); ++i) {
+ handles[i] = NN_TRY(V1_2::utils::convert(syncFences[i].getHandle()));
+ }
+ return handles;
+}
+
+nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> convertFencedExecutionCallbackResults(
+ const V1_2::Timing& timingLaunched, const V1_2::Timing& timingFenced) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(timingLaunched)),
+ NN_TRY(validatedConvertToCanonical(timingFenced)));
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+convertExecuteFencedResults(const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ auto resultSyncFence = nn::SyncFence::createAsSignaled();
+ if (syncFence.getNativeHandle() != nullptr) {
+ auto nativeHandle = NN_TRY(validatedConvertToCanonical(syncFence));
+ resultSyncFence = NN_TRY(hal::utils::makeGeneralFailure(
+ nn::SyncFence::create(std::move(nativeHandle)), nn::ErrorStatus::GENERAL_FAILURE));
+ }
+
+ if (callback == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "callback is null";
+ }
+
+ // Create callback which can be used to retrieve the execution error status and timings.
+ nn::ExecuteFencedInfoCallback resultCallback =
+ [callback]() -> nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> {
+ nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const V1_2::Timing& timingLaunched,
+ const V1_2::Timing& timingFenced) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical = validatedConvertToCanonical(status).value_or(
+ nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getExecutionInfo failed with " << toString(status);
+ } else {
+ result = convertFencedExecutionCallbackResults(timingLaunched, timingFenced);
+ }
+ };
+
+ const auto ret = callback->getExecutionInfo(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+ };
+
+ return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+ sp<V1_3::IPreparedModel> preparedModel) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::PreparedModel::create must have non-null preparedModel";
+ }
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+ return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_3::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler)
+ : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeSynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
+ } else {
+ result = convertExecutionResults(outputShapes, timing);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeSynchronously_1_3(request, measure, deadline,
+ loopTimeoutDuration, cb);
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+
+ return result;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeAsynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ const auto cb = sp<ExecutionCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret =
+ kPreparedModel->execute_1_3(request, measure, deadline, loopTimeoutDuration, cb);
+ const auto status =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "executeAsynchronously failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+ const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+ const auto hidlMeasure =
+ NN_TRY(hal::utils::makeExecutionFailure(V1_2::utils::convert(measure)));
+ const auto hidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+ const auto hidlLoopTimeoutDuration =
+ NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const bool preferSynchronous = true;
+
+ // Execute synchronously if allowed.
+ if (preferSynchronous) {
+ result = executeSynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Run asymchronous execution if execution has not already completed.
+ if (!result.has_value()) {
+ result = executeAsynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Flush output buffers if suxcessful execution.
+ if (result.has_value()) {
+ NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+ }
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared));
+
+ const auto hidlRequest = NN_TRY(convert(requestInShared));
+ const auto hidlWaitFor = NN_TRY(convertSyncFences(waitFor));
+ const auto hidlMeasure = NN_TRY(V1_2::utils::convert(measure));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+ const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeFenced failed with " << toString(status);
+ } else {
+ result = convertExecuteFencedResults(syncFence, callback);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeFenced(hidlRequest, hidlWaitFor, hidlMeasure,
+ hidlDeadline, hidlLoopTimeoutDuration,
+ hidlTimeoutDurationAfterFence, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+ auto [syncFence, callback] = NN_TRY(std::move(result));
+
+ // If executeFenced required the request memory to be moved into shared memory, block here until
+ // the fenced execution has completed and flush the memory back.
+ if (maybeRequestInShared.has_value()) {
+ const auto state = syncFence.syncWait({});
+ if (state != nn::SyncFence::FenceState::SIGNALED) {
+ return NN_ERROR() << "syncWait failed with " << state;
+ }
+ NN_TRY(hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared));
+ }
+
+ return std::make_pair(std::move(syncFence), std::move(callback));
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+ sp<V1_3::IPreparedModel> resource = kPreparedModel;
+ return resource;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils