Introduce reusable execution to canonical interface -- HAL.
This CL modifies the canonical interface for reusable executions:
- Add new interface: IExecution with compute and computeFenced methods
- Add new method IPreparedModel::createExecution
In NNAPI runtime, the new interface IExecution is used to
memoize request-specific execution resources (e.g. converted HAL
request). The expected usage is that, IPreparedModel::createExecution
will be invoked in the first computation of a reusable NDK ANNExecution
object, and IExecution::compute* will be invoked repeatedly.
The IPreparedModel::execute* methods are preserved to avoid redundant
object creation and memoization overhead for a single-time
(non-reusable) execution.
For a vendor implementing the canonical interfaces, only the
IPreparedModel::execute* methods will be called because there is
currently no reusable execution at HAL interface. A DefaultExecution
implementation is provided to reduce the work needed on the vendor side.
Bug: 184073769
Test: NNT_static
Test: neuralnetworks_utils_hal_1_0_test
Test: neuralnetworks_utils_hal_1_1_test
Test: neuralnetworks_utils_hal_1_2_test
Test: neuralnetworks_utils_hal_1_3_test
Test: neuralnetworks_utils_hal_common_test
Test: neuralnetworks_utils_hal_aidl_test
Change-Id: I91790bb5ccf5ae648687fe603f88ffda2c9fd2b2
Merged-In: I91790bb5ccf5ae648687fe603f88ffda2c9fd2b2
(cherry picked from commit 727a7b2104b0962509fedffe720eec508b2ee6de)
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Execution.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Execution.h
new file mode 100644
index 0000000..e201e25
--- /dev/null
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/Execution.h
@@ -0,0 +1,64 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_EXECUTION_H
+
+#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include "PreparedModel.h"
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_0::utils {
+
+class Execution final : public nn::IExecution, public std::enable_shared_from_this<Execution> {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Execution>> create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation);
+
+ Execution(PrivateConstructorTag tag, std::shared_ptr<const PreparedModel> preparedModel,
+ Request request, hal::utils::RequestRelocation relocation);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+
+ private:
+ const std::shared_ptr<const PreparedModel> kPreparedModel;
+ const Request kRequest;
+ const hal::utils::RequestRelocation kRelocation;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_0_UTILS_EXECUTION_H
diff --git a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h
index 8853eea..48be595 100644
--- a/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h
+++ b/neuralnetworks/1.0/utils/include/nnapi/hal/1.0/PreparedModel.h
@@ -57,10 +57,17 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeInternal(
+ const V1_0::Request& request, const hal::utils::RequestRelocation& relocation) const;
+
private:
const sp<V1_0::IPreparedModel> kPreparedModel;
const hal::utils::DeathHandler kDeathHandler;
diff --git a/neuralnetworks/1.0/utils/src/Execution.cpp b/neuralnetworks/1.0/utils/src/Execution.cpp
new file mode 100644
index 0000000..7a3216b
--- /dev/null
+++ b/neuralnetworks/1.0/utils/src/Execution.cpp
@@ -0,0 +1,72 @@
+/*
+ * 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 "Execution.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/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_0::utils {
+
+nn::GeneralResult<std::shared_ptr<const Execution>> Execution::create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR() << "V1_0::utils::Execution::create must have non-null preparedModel";
+ }
+
+ return std::make_shared<const Execution>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(request), std::move(relocation));
+}
+
+Execution::Execution(PrivateConstructorTag /*tag*/,
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation)
+ : kPreparedModel(std::move(preparedModel)),
+ kRequest(std::move(request)),
+ kRelocation(std::move(relocation)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> Execution::compute(
+ const nn::OptionalTimePoint& /*deadline*/) const {
+ return kPreparedModel->executeInternal(kRequest, kRelocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> Execution::computeFenced(
+ const std::vector<nn::SyncFence>& /*waitFor*/, const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalDuration& /*timeoutDurationAfterFence*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IExecution::computeFenced is not supported on 1.0 HAL service";
+}
+
+} // namespace android::hardware::neuralnetworks::V1_0::utils
diff --git a/neuralnetworks/1.0/utils/src/PreparedModel.cpp b/neuralnetworks/1.0/utils/src/PreparedModel.cpp
index 858571d..7987ab4 100644
--- a/neuralnetworks/1.0/utils/src/PreparedModel.cpp
+++ b/neuralnetworks/1.0/utils/src/PreparedModel.cpp
@@ -19,6 +19,7 @@
#include "Burst.h"
#include "Callbacks.h"
#include "Conversions.h"
+#include "Execution.h"
#include "Utils.h"
#include <android/hardware/neuralnetworks/1.0/IPreparedModel.h>
@@ -61,22 +62,34 @@
const nn::OptionalDuration& /*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)));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation)));
const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+ return executeInternal(hidlRequest, relocation);
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeInternal(const V1_0::Request& request,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
+
const auto cb = sp<ExecutionCallback>::make();
const auto scoped = kDeathHandler.protectCallback(cb.get());
- const auto ret = kPreparedModel->execute(hidlRequest, cb);
+ const auto ret = kPreparedModel->execute(request, cb);
const auto status = HANDLE_TRANSPORT_FAILURE(ret);
HANDLE_HAL_STATUS(status) << "execution failed with " << toString(status);
auto result = NN_TRY(cb->get());
- NN_TRY(hal::utils::makeExecutionFailure(
- hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
-
+ if (relocation.output) {
+ relocation.output->flush();
+ }
return result;
}
@@ -91,6 +104,19 @@
<< "IPreparedModel::executeFenced is not supported on 1.0 HAL service";
}
+nn::GeneralResult<nn::SharedExecution> PreparedModel::createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming /*measure*/,
+ const nn::OptionalDuration& /*loopTimeoutDuration*/) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
+
+ auto hidlRequest = NN_TRY(convert(requestInShared));
+ return Execution::create(shared_from_this(), std::move(hidlRequest), std::move(relocation));
+}
+
nn::GeneralResult<nn::SharedBurst> PreparedModel::configureExecutionBurst() const {
return Burst::create(shared_from_this());
}
diff --git a/neuralnetworks/1.0/utils/test/PreparedModelTest.cpp b/neuralnetworks/1.0/utils/test/PreparedModelTest.cpp
index f19ed77..7820c06 100644
--- a/neuralnetworks/1.0/utils/test/PreparedModelTest.cpp
+++ b/neuralnetworks/1.0/utils/test/PreparedModelTest.cpp
@@ -19,6 +19,7 @@
#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
+#include <nnapi/IExecution.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
@@ -224,6 +225,150 @@
EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
}
+TEST(PreparedModelTest, reusableExecute) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, execute(_, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(Invoke(makeExecute(V1_0::ErrorStatus::NONE, V1_0::ErrorStatus::NONE)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteLaunchError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, execute(_, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecute(V1_0::ErrorStatus::GENERAL_FAILURE,
+ V1_0::ErrorStatus::GENERAL_FAILURE)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteReturnError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, execute(_, _))
+ .Times(1)
+ .WillOnce(Invoke(
+ makeExecute(V1_0::ErrorStatus::NONE, V1_0::ErrorStatus::GENERAL_FAILURE)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, execute(_, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, execute(_, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteCrash) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ const auto ret = [&mockPreparedModel]() -> hardware::Return<V1_0::ErrorStatus> {
+ mockPreparedModel->simulateCrash();
+ return V1_0::ErrorStatus::NONE;
+ };
+ EXPECT_CALL(*mockPreparedModel, execute(_, _)).Times(1).WillOnce(InvokeWithoutArgs(ret));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedNotSupported) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
TEST(PreparedModelTest, configureExecutionBurst) {
// setup test
const auto mockPreparedModel = MockPreparedModel::create();
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Execution.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Execution.h
new file mode 100644
index 0000000..9c66446
--- /dev/null
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Execution.h
@@ -0,0 +1,66 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_H
+
+#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include "PreparedModel.h"
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_2::utils {
+
+class Execution final : public nn::IExecution, public std::enable_shared_from_this<Execution> {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Execution>> create(
+ std::shared_ptr<const PreparedModel> preparedModel, V1_0::Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure);
+
+ Execution(PrivateConstructorTag tag, std::shared_ptr<const PreparedModel> preparedModel,
+ V1_0::Request request, hal::utils::RequestRelocation relocation,
+ V1_2::MeasureTiming measure);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+
+ private:
+ const std::shared_ptr<const PreparedModel> kPreparedModel;
+ const V1_0::Request kRequest;
+ const hal::utils::RequestRelocation kRelocation;
+ const MeasureTiming kMeasure;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_H
diff --git a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h
index fb11130..35abd79 100644
--- a/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h
+++ b/neuralnetworks/1.2/utils/include/nnapi/hal/1.2/PreparedModel.h
@@ -58,10 +58,18 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeInternal(
+ const V1_0::Request& request, MeasureTiming measure,
+ const hal::utils::RequestRelocation& relocation) const;
+
private:
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
const V1_0::Request& request, MeasureTiming measure) const;
diff --git a/neuralnetworks/1.2/utils/src/Execution.cpp b/neuralnetworks/1.2/utils/src/Execution.cpp
new file mode 100644
index 0000000..18d1c90
--- /dev/null
+++ b/neuralnetworks/1.2/utils/src/Execution.cpp
@@ -0,0 +1,74 @@
+/*
+ * 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 "Execution.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/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_2::utils {
+
+nn::GeneralResult<std::shared_ptr<const Execution>> Execution::create(
+ std::shared_ptr<const PreparedModel> preparedModel, V1_0::Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR() << "V1_2::utils::Execution::create must have non-null preparedModel";
+ }
+
+ return std::make_shared<const Execution>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(request), std::move(relocation), measure);
+}
+
+Execution::Execution(PrivateConstructorTag /*tag*/,
+ std::shared_ptr<const PreparedModel> preparedModel, V1_0::Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure)
+ : kPreparedModel(std::move(preparedModel)),
+ kRequest(std::move(request)),
+ kRelocation(std::move(relocation)),
+ kMeasure(measure) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> Execution::compute(
+ const nn::OptionalTimePoint& /*deadline*/) const {
+ return kPreparedModel->executeInternal(kRequest, kMeasure, kRelocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> Execution::computeFenced(
+ const std::vector<nn::SyncFence>& /*waitFor*/, const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalDuration& /*timeoutDurationAfterFence*/) const {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IExecution::computeFenced is not supported on 1.2 HAL service";
+}
+
+} // namespace android::hardware::neuralnetworks::V1_2::utils
diff --git a/neuralnetworks/1.2/utils/src/PreparedModel.cpp b/neuralnetworks/1.2/utils/src/PreparedModel.cpp
index b209a44..e01401b 100644
--- a/neuralnetworks/1.2/utils/src/PreparedModel.cpp
+++ b/neuralnetworks/1.2/utils/src/PreparedModel.cpp
@@ -18,6 +18,7 @@
#include "Callbacks.h"
#include "Conversions.h"
+#include "Execution.h"
#include "ExecutionBurstController.h"
#include "ExecutionBurstUtils.h"
#include "Utils.h"
@@ -93,19 +94,31 @@
const nn::OptionalDuration& /*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)));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation)));
const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
const auto hidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
- auto result = kExecuteSynchronously ? executeSynchronously(hidlRequest, hidlMeasure)
- : executeAsynchronously(hidlRequest, hidlMeasure);
+ return executeInternal(hidlRequest, hidlMeasure, relocation);
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeInternal(const V1_0::Request& request, MeasureTiming measure,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
+
+ auto result = kExecuteSynchronously ? executeSynchronously(request, measure)
+ : executeAsynchronously(request, measure);
auto [outputShapes, timing] = NN_TRY(std::move(result));
- NN_TRY(hal::utils::makeExecutionFailure(
- hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
-
+ if (relocation.output) {
+ relocation.output->flush();
+ }
return std::make_pair(std::move(outputShapes), timing);
}
@@ -120,6 +133,21 @@
<< "IPreparedModel::executeFenced is not supported on 1.2 HAL service";
}
+nn::GeneralResult<nn::SharedExecution> PreparedModel::createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& /*loopTimeoutDuration*/) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
+
+ auto hidlRequest = NN_TRY(convert(requestInShared));
+ auto hidlMeasure = NN_TRY(convert(measure));
+ return Execution::create(shared_from_this(), std::move(hidlRequest), std::move(relocation),
+ hidlMeasure);
+}
+
nn::GeneralResult<nn::SharedBurst> PreparedModel::configureExecutionBurst() const {
auto self = shared_from_this();
auto fallback = [preparedModel = std::move(self)](
diff --git a/neuralnetworks/1.2/utils/test/PreparedModelTest.cpp b/neuralnetworks/1.2/utils/test/PreparedModelTest.cpp
index d297b1a..5e2ad79 100644
--- a/neuralnetworks/1.2/utils/test/PreparedModelTest.cpp
+++ b/neuralnetworks/1.2/utils/test/PreparedModelTest.cpp
@@ -21,6 +21,7 @@
#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
+#include <nnapi/IExecution.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
@@ -334,6 +335,248 @@
EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
}
+TEST(PreparedModelTest, reusableExecuteSync) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(
+ Invoke(makeExecuteSynchronously(V1_0::ErrorStatus::NONE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _))
+ .Times(1)
+ .WillOnce(Invoke(
+ makeExecuteSynchronously(V1_0::ErrorStatus::GENERAL_FAILURE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsync) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(Invoke(makeExecuteAsynchronously(
+ V1_0::ErrorStatus::NONE, V1_0::ErrorStatus::NONE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncLaunchError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteAsynchronously(V1_0::ErrorStatus::GENERAL_FAILURE,
+ V1_0::ErrorStatus::GENERAL_FAILURE, {},
+ kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncReturnError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteAsynchronously(
+ V1_0::ErrorStatus::NONE, V1_0::ErrorStatus::GENERAL_FAILURE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncCrash) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ const auto ret = [&mockPreparedModel]() -> hardware::Return<V1_0::ErrorStatus> {
+ mockPreparedModel->simulateCrash();
+ return V1_0::ErrorStatus::NONE;
+ };
+ EXPECT_CALL(*mockPreparedModel, execute_1_2(_, _, _)).Times(1).WillOnce(InvokeWithoutArgs(ret));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedNotSupported) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
TEST(PreparedModelTest, configureExecutionBurst) {
// setup test
const auto mockPreparedModel = MockPreparedModel::create();
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Execution.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Execution.h
new file mode 100644
index 0000000..06c33d4
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Execution.h
@@ -0,0 +1,66 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_EXECUTION_H
+
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+
+#include "PreparedModel.h"
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_3::utils {
+
+class Execution final : public nn::IExecution, public std::enable_shared_from_this<Execution> {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Execution>> create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure,
+ OptionalTimeoutDuration loopTimeoutDuration);
+
+ Execution(PrivateConstructorTag tag, std::shared_ptr<const PreparedModel> preparedModel,
+ Request request, hal::utils::RequestRelocation relocation,
+ V1_2::MeasureTiming measure, OptionalTimeoutDuration loopTimeoutDuration);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+
+ private:
+ const std::shared_ptr<const PreparedModel> kPreparedModel;
+ const Request kRequest;
+ const hal::utils::RequestRelocation kRelocation;
+ const V1_2::MeasureTiming kMeasure;
+ const OptionalTimeoutDuration kLoopTimeoutDuration;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_EXECUTION_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
index 690fecc..5acba71 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
@@ -57,10 +57,26 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeInternal(
+ const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration,
+ const hal::utils::RequestRelocation& relocation) const;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+ executeFencedInternal(const Request& request, const hidl_vec<hidl_handle>& waitFor,
+ V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration,
+ const OptionalTimeoutDuration& timeoutDurationAfterFence,
+ const hal::utils::RequestRelocation& relocation) const;
+
private:
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
diff --git a/neuralnetworks/1.3/utils/src/Execution.cpp b/neuralnetworks/1.3/utils/src/Execution.cpp
new file mode 100644
index 0000000..3d17cc3
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Execution.cpp
@@ -0,0 +1,84 @@
+/*
+ * 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 "Execution.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/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// 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::V1_3::utils {
+
+nn::GeneralResult<std::shared_ptr<const Execution>> Execution::create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure,
+ OptionalTimeoutDuration loopTimeoutDuration) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR() << "V1_3::utils::Execution::create must have non-null preparedModel";
+ }
+
+ return std::make_shared<const Execution>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(request), std::move(relocation), measure,
+ std::move(loopTimeoutDuration));
+}
+
+Execution::Execution(PrivateConstructorTag /*tag*/,
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, V1_2::MeasureTiming measure,
+ OptionalTimeoutDuration loopTimeoutDuration)
+ : kPreparedModel(std::move(preparedModel)),
+ kRequest(std::move(request)),
+ kRelocation(std::move(relocation)),
+ kMeasure(measure),
+ kLoopTimeoutDuration(std::move(loopTimeoutDuration)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> Execution::compute(
+ const nn::OptionalTimePoint& deadline) const {
+ const auto hidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+ return kPreparedModel->executeInternal(kRequest, kMeasure, hidlDeadline, kLoopTimeoutDuration,
+ kRelocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> Execution::computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const {
+ const auto hidlWaitFor = NN_TRY(hal::utils::convertSyncFences(waitFor));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+ return kPreparedModel->executeFencedInternal(kRequest, hidlWaitFor, kMeasure, hidlDeadline,
+ kLoopTimeoutDuration,
+ hidlTimeoutDurationAfterFence, kRelocation);
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/PreparedModel.cpp b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
index fd7f8f2..5163e8a 100644
--- a/neuralnetworks/1.3/utils/src/PreparedModel.cpp
+++ b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
@@ -18,6 +18,7 @@
#include "Callbacks.h"
#include "Conversions.h"
+#include "Execution.h"
#include "Utils.h"
#include <android/hardware/neuralnetworks/1.0/types.h>
@@ -139,8 +140,10 @@
const nn::OptionalDuration& 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)));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation)));
const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
const auto hidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
@@ -148,16 +151,27 @@
const auto hidlLoopTimeoutDuration =
NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+ return executeInternal(hidlRequest, hidlMeasure, hidlDeadline, hidlLoopTimeoutDuration,
+ relocation);
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeInternal(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
+
auto result = kExecuteSynchronously
- ? executeSynchronously(hidlRequest, hidlMeasure, hidlDeadline,
- hidlLoopTimeoutDuration)
- : executeAsynchronously(hidlRequest, hidlMeasure, hidlDeadline,
- hidlLoopTimeoutDuration);
+ ? executeSynchronously(request, measure, deadline, loopTimeoutDuration)
+ : executeAsynchronously(request, measure, deadline, loopTimeoutDuration);
auto [outputShapes, timing] = NN_TRY(std::move(result));
- NN_TRY(hal::utils::makeExecutionFailure(
- hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
-
+ if (relocation.output) {
+ relocation.output->flush();
+ }
return std::make_pair(std::move(outputShapes), timing);
}
@@ -168,8 +182,9 @@
const nn::OptionalDuration& 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));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
const auto hidlRequest = NN_TRY(convert(requestInShared));
const auto hidlWaitFor = NN_TRY(hal::utils::convertSyncFences(waitFor));
@@ -178,27 +193,58 @@
const auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+ return executeFencedInternal(hidlRequest, hidlWaitFor, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration, hidlTimeoutDurationAfterFence,
+ relocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFencedInternal(const Request& request, const hidl_vec<hidl_handle>& waitFor,
+ V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration,
+ const OptionalTimeoutDuration& timeoutDurationAfterFence,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
+
auto cb = hal::utils::CallbackValue(fencedExecutionCallback);
- const auto ret = kPreparedModel->executeFenced(hidlRequest, hidlWaitFor, hidlMeasure,
- hidlDeadline, hidlLoopTimeoutDuration,
- hidlTimeoutDurationAfterFence, cb);
+ const auto ret =
+ kPreparedModel->executeFenced(request, waitFor, measure, deadline, loopTimeoutDuration,
+ timeoutDurationAfterFence, cb);
HANDLE_TRANSPORT_FAILURE(ret);
auto [syncFence, callback] = NN_TRY(cb.take());
// 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()) {
+ if (relocation.output) {
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));
+ relocation.output->flush();
}
return std::make_pair(std::move(syncFence), std::move(callback));
}
+nn::GeneralResult<nn::SharedExecution> PreparedModel::createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
+
+ auto hidlRequest = NN_TRY(convert(requestInShared));
+ auto hidlMeasure = NN_TRY(convert(measure));
+ auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+ return Execution::create(shared_from_this(), std::move(hidlRequest), std::move(relocation),
+ hidlMeasure, std::move(hidlLoopTimeoutDuration));
+}
+
nn::GeneralResult<nn::SharedBurst> PreparedModel::configureExecutionBurst() const {
auto self = shared_from_this();
auto fallback = [preparedModel = std::move(self)](
diff --git a/neuralnetworks/1.3/utils/test/PreparedModelTest.cpp b/neuralnetworks/1.3/utils/test/PreparedModelTest.cpp
index 5303c2a..6dbbd6b 100644
--- a/neuralnetworks/1.3/utils/test/PreparedModelTest.cpp
+++ b/neuralnetworks/1.3/utils/test/PreparedModelTest.cpp
@@ -22,6 +22,7 @@
#include <android/hardware/neuralnetworks/1.3/IFencedExecutionCallback.h>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
+#include <nnapi/IExecution.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
@@ -462,6 +463,363 @@
EXPECT_EQ(result.error().code, nn::ErrorStatus::DEAD_OBJECT);
}
+TEST(PreparedModelTest, reusableExecuteSync) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously_1_3(_, _, _, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(
+ Invoke(makeExecuteSynchronously(V1_3::ErrorStatus::NONE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(
+ makeExecuteSynchronously(V1_3::ErrorStatus::GENERAL_FAILURE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsync) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(Invoke(makeExecuteAsynchronously(
+ V1_3::ErrorStatus::NONE, V1_3::ErrorStatus::NONE, {}, kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncLaunchError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteAsynchronously(V1_3::ErrorStatus::GENERAL_FAILURE,
+ V1_3::ErrorStatus::GENERAL_FAILURE, {},
+ kNoTiming)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncReturnError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteAsynchronously(
+ V1_3::ErrorStatus::NONE, V1_3::ErrorStatus::GENERAL_FAILURE, {}, kNoTiming)));
+
+ // run test
+ const auto result = preparedModel->execute({}, {}, {}, {});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteAsyncCrash) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/false).value();
+ const auto ret = [&mockPreparedModel]() -> hardware::Return<V1_3::ErrorStatus> {
+ mockPreparedModel->simulateCrash();
+ return V1_3::ErrorStatus::NONE;
+ };
+ EXPECT_CALL(*mockPreparedModel, execute_1_3(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(ret));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteFenced) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ const auto mockCallback = MockFencedExecutionCallback::create();
+ EXPECT_CALL(*mockCallback, getExecutionInfo(_))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(Invoke(makeExecuteFencedCallbackReturn(V1_3::ErrorStatus::NONE,
+ kNoTiming, kNoTiming)));
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(
+ Invoke(makeExecuteFencedReturn(V1_3::ErrorStatus::NONE, {}, mockCallback)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ const auto& [syncFence, callback] = computeResult.value();
+ EXPECT_EQ(syncFence.syncWait({}), nn::SyncFence::FenceState::SIGNALED);
+ ASSERT_NE(callback, nullptr);
+
+ // get results from callback
+ const auto callbackResult = callback();
+ ASSERT_TRUE(callbackResult.has_value()) << "Failed with " << callbackResult.error().code
+ << ": " << callbackResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedCallbackError) {
+ // setup call
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ const auto mockCallback = MockFencedExecutionCallback::create();
+ EXPECT_CALL(*mockCallback, getExecutionInfo(_))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteFencedCallbackReturn(V1_3::ErrorStatus::GENERAL_FAILURE,
+ kNoTiming, kNoTiming)));
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeExecuteFencedReturn(V1_3::ErrorStatus::NONE, {}, mockCallback)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code << ": "
+ << computeResult.error().message;
+ const auto& [syncFence, callback] = computeResult.value();
+ EXPECT_NE(syncFence.syncWait({}), nn::SyncFence::FenceState::ACTIVE);
+ ASSERT_NE(callback, nullptr);
+
+ // verify callback failure
+ const auto callbackResult = callback();
+ ASSERT_FALSE(callbackResult.has_value());
+ EXPECT_EQ(callbackResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedError) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(
+ makeExecuteFencedReturn(V1_3::ErrorStatus::GENERAL_FAILURE, {}, nullptr)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedDeadObject) {
+ // setup test
+ const auto mockPreparedModel = createMockPreparedModel();
+ const auto preparedModel =
+ PreparedModel::create(mockPreparedModel, /*executeSynchronously=*/true).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
TEST(PreparedModelTest, configureExecutionBurst) {
// setup test
const auto mockPreparedModel = MockPreparedModel::create();
diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Execution.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Execution.h
new file mode 100644
index 0000000..a77ea98
--- /dev/null
+++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/Execution.h
@@ -0,0 +1,65 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_EXECUTION_H
+
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+
+#include "PreparedModel.h"
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
+// lifetimes across processes and for protecting asynchronous calls across HIDL.
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+
+class Execution final : public nn::IExecution, public std::enable_shared_from_this<Execution> {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Execution>> create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, bool measure, int64_t loopTimeoutDuration);
+
+ Execution(PrivateConstructorTag tag, std::shared_ptr<const PreparedModel> preparedModel,
+ Request request, hal::utils::RequestRelocation relocation, bool measure,
+ int64_t loopTimeoutDuration);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+
+ private:
+ const std::shared_ptr<const PreparedModel> kPreparedModel;
+ const Request kRequest;
+ const hal::utils::RequestRelocation kRelocation;
+ const bool kMeasure;
+ const int64_t kLoopTimeoutDuration;
+};
+
+} // namespace aidl::android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_EXECUTION_H
diff --git a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/PreparedModel.h b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/PreparedModel.h
index abce6cc..4035764 100644
--- a/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/PreparedModel.h
+++ b/neuralnetworks/aidl/utils/include/nnapi/hal/aidl/PreparedModel.h
@@ -18,6 +18,7 @@
#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_AIDL_UTILS_PREPARED_MODEL_H
#include <aidl/android/hardware/neuralnetworks/IPreparedModel.h>
+#include <aidl/android/hardware/neuralnetworks/Request.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
#include <nnapi/Types.h>
@@ -34,7 +35,8 @@
namespace aidl::android::hardware::neuralnetworks::utils {
// Class that adapts aidl_hal::IPreparedModel to nn::IPreparedModel.
-class PreparedModel final : public nn::IPreparedModel {
+class PreparedModel final : public nn::IPreparedModel,
+ public std::enable_shared_from_this<PreparedModel> {
struct PrivateConstructorTag {};
public:
@@ -55,10 +57,25 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeInternal(
+ const Request& request, bool measure, int64_t deadline, int64_t loopTimeoutDuration,
+ const hal::utils::RequestRelocation& relocation) const;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+ executeFencedInternal(const Request& request,
+ const std::vector<ndk::ScopedFileDescriptor>& waitFor, bool measure,
+ int64_t deadline, int64_t loopTimeoutDuration,
+ int64_t timeoutDurationAfterFence,
+ const hal::utils::RequestRelocation& relocation) const;
+
private:
const std::shared_ptr<aidl_hal::IPreparedModel> kPreparedModel;
};
diff --git a/neuralnetworks/aidl/utils/src/Burst.cpp b/neuralnetworks/aidl/utils/src/Burst.cpp
index 0b475bc..b20f6ae 100644
--- a/neuralnetworks/aidl/utils/src/Burst.cpp
+++ b/neuralnetworks/aidl/utils/src/Burst.cpp
@@ -148,8 +148,10 @@
// 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)));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation)));
const auto aidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
const auto aidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
@@ -174,6 +176,10 @@
}
CHECK_EQ(request.pools.size(), memoryIdentifierTokens.size());
+ if (relocation.input) {
+ relocation.input->flush();
+ }
+
ExecutionResult executionResult;
const auto ret =
kBurst->executeSynchronously(aidlRequest, memoryIdentifierTokens, aidlMeasure,
@@ -188,9 +194,9 @@
auto [outputShapes, timing] = NN_TRY(hal::utils::makeExecutionFailure(
convertExecutionResults(executionResult.outputShapes, executionResult.timing)));
- NN_TRY(hal::utils::makeExecutionFailure(
- hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
-
+ if (relocation.output) {
+ relocation.output->flush();
+ }
return std::make_pair(std::move(outputShapes), timing);
}
diff --git a/neuralnetworks/aidl/utils/src/Execution.cpp b/neuralnetworks/aidl/utils/src/Execution.cpp
new file mode 100644
index 0000000..2aee8a6
--- /dev/null
+++ b/neuralnetworks/aidl/utils/src/Execution.cpp
@@ -0,0 +1,79 @@
+/*
+ * 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 "Execution.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <aidl/android/hardware/neuralnetworks/Request.h>
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+
+#include <memory>
+#include <utility>
+#include <vector>
+
+// See hardware/interfaces/neuralnetworks/utils/README.md for more information on HIDL interface
+// lifetimes across processes and for protecting asynchronous calls across HIDL.
+
+namespace aidl::android::hardware::neuralnetworks::utils {
+
+nn::GeneralResult<std::shared_ptr<const Execution>> Execution::create(
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, bool measure, int64_t loopTimeoutDuration) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR() << "aidl::utils::Execution::create must have non-null preparedModel";
+ }
+
+ return std::make_shared<const Execution>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(request), std::move(relocation), measure,
+ loopTimeoutDuration);
+}
+
+Execution::Execution(PrivateConstructorTag /*tag*/,
+ std::shared_ptr<const PreparedModel> preparedModel, Request request,
+ hal::utils::RequestRelocation relocation, bool measure,
+ int64_t loopTimeoutDuration)
+ : kPreparedModel(std::move(preparedModel)),
+ kRequest(std::move(request)),
+ kRelocation(std::move(relocation)),
+ kMeasure(measure),
+ kLoopTimeoutDuration(loopTimeoutDuration) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> Execution::compute(
+ const nn::OptionalTimePoint& deadline) const {
+ const auto aidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+ return kPreparedModel->executeInternal(kRequest, kMeasure, aidlDeadline, kLoopTimeoutDuration,
+ kRelocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> Execution::computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const {
+ const auto aidlWaitFor = NN_TRY(convert(waitFor));
+ const auto aidlDeadline = NN_TRY(convert(deadline));
+ const auto aidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+ return kPreparedModel->executeFencedInternal(kRequest, aidlWaitFor, kMeasure, aidlDeadline,
+ kLoopTimeoutDuration,
+ aidlTimeoutDurationAfterFence, kRelocation);
+}
+
+} // namespace aidl::android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/aidl/utils/src/PreparedModel.cpp b/neuralnetworks/aidl/utils/src/PreparedModel.cpp
index 003965b..1915607 100644
--- a/neuralnetworks/aidl/utils/src/PreparedModel.cpp
+++ b/neuralnetworks/aidl/utils/src/PreparedModel.cpp
@@ -19,8 +19,11 @@
#include "Burst.h"
#include "Callbacks.h"
#include "Conversions.h"
+#include "Execution.h"
+#include "ProtectCallback.h"
#include "Utils.h"
+#include <aidl/android/hardware/neuralnetworks/Request.h>
#include <android/binder_auto_utils.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/Result.h>
@@ -74,18 +77,31 @@
const nn::OptionalDuration& 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)));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation)));
const auto aidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
const auto aidlMeasure = NN_TRY(hal::utils::makeExecutionFailure(convert(measure)));
const auto aidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
const auto aidlLoopTimeoutDuration =
NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+ return executeInternal(aidlRequest, aidlMeasure, aidlDeadline, aidlLoopTimeoutDuration,
+ relocation);
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeInternal(const Request& request, bool measure, int64_t deadline,
+ int64_t loopTimeoutDuration,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
ExecutionResult executionResult;
- const auto ret = kPreparedModel->executeSynchronously(
- aidlRequest, aidlMeasure, aidlDeadline, aidlLoopTimeoutDuration, &executionResult);
+ const auto ret = kPreparedModel->executeSynchronously(request, measure, deadline,
+ loopTimeoutDuration, &executionResult);
HANDLE_ASTATUS(ret) << "executeSynchronously failed";
if (!executionResult.outputSufficientSize) {
auto canonicalOutputShapes =
@@ -96,9 +112,9 @@
auto [outputShapes, timing] = NN_TRY(hal::utils::makeExecutionFailure(
convertExecutionResults(executionResult.outputShapes, executionResult.timing)));
- NN_TRY(hal::utils::makeExecutionFailure(
- hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
-
+ if (relocation.output) {
+ relocation.output->flush();
+ }
return std::make_pair(std::move(outputShapes), timing);
}
@@ -109,8 +125,9 @@
const nn::OptionalDuration& 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));
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
const auto aidlRequest = NN_TRY(convert(requestInShared));
const auto aidlWaitFor = NN_TRY(convert(waitFor));
@@ -118,11 +135,25 @@
const auto aidlDeadline = NN_TRY(convert(deadline));
const auto aidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
const auto aidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+ return executeFencedInternal(aidlRequest, aidlWaitFor, aidlMeasure, aidlDeadline,
+ aidlLoopTimeoutDuration, aidlTimeoutDurationAfterFence,
+ relocation);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFencedInternal(const Request& request,
+ const std::vector<ndk::ScopedFileDescriptor>& waitFor,
+ bool measure, int64_t deadline, int64_t loopTimeoutDuration,
+ int64_t timeoutDurationAfterFence,
+ const hal::utils::RequestRelocation& relocation) const {
+ if (relocation.input) {
+ relocation.input->flush();
+ }
FencedExecutionResult result;
- const auto ret = kPreparedModel->executeFenced(aidlRequest, aidlWaitFor, aidlMeasure,
- aidlDeadline, aidlLoopTimeoutDuration,
- aidlTimeoutDurationAfterFence, &result);
+ const auto ret =
+ kPreparedModel->executeFenced(request, waitFor, measure, deadline, loopTimeoutDuration,
+ timeoutDurationAfterFence, &result);
HANDLE_ASTATUS(ret) << "executeFenced failed";
auto resultSyncFence = nn::SyncFence::createAsSignaled();
@@ -137,12 +168,12 @@
// 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()) {
+ if (relocation.output) {
const auto state = resultSyncFence.syncWait({});
if (state != nn::SyncFence::FenceState::SIGNALED) {
return NN_ERROR() << "syncWait failed with " << state;
}
- NN_TRY(hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared));
+ relocation.output->flush();
}
// Create callback which can be used to retrieve the execution error status and timings.
@@ -159,6 +190,22 @@
return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
}
+nn::GeneralResult<nn::SharedExecution> PreparedModel::createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ hal::utils::RequestRelocation relocation;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::convertRequestFromPointerToShared(
+ &request, &maybeRequestInShared, &relocation));
+
+ auto aidlRequest = NN_TRY(convert(requestInShared));
+ auto aidlMeasure = NN_TRY(convert(measure));
+ auto aidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+ return Execution::create(shared_from_this(), std::move(aidlRequest), std::move(relocation),
+ aidlMeasure, aidlLoopTimeoutDuration);
+}
+
nn::GeneralResult<nn::SharedBurst> PreparedModel::configureExecutionBurst() const {
std::shared_ptr<IBurst> burst;
const auto ret = kPreparedModel->configureExecutionBurst(&burst);
diff --git a/neuralnetworks/aidl/utils/test/PreparedModelTest.cpp b/neuralnetworks/aidl/utils/test/PreparedModelTest.cpp
index ff98a7d..8bb5c90 100644
--- a/neuralnetworks/aidl/utils/test/PreparedModelTest.cpp
+++ b/neuralnetworks/aidl/utils/test/PreparedModelTest.cpp
@@ -21,6 +21,7 @@
#include <aidl/android/hardware/neuralnetworks/IFencedExecutionCallback.h>
#include <gmock/gmock.h>
#include <gtest/gtest.h>
+#include <nnapi/IExecution.h>
#include <nnapi/IPreparedModel.h>
#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
@@ -253,6 +254,225 @@
EXPECT_EQ(result.error().code, nn::ErrorStatus::DEAD_OBJECT);
}
+TEST(PreparedModelTest, reusableExecuteSync) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ const auto mockExecutionResult = ExecutionResult{
+ .outputSufficientSize = true,
+ .outputShapes = {},
+ .timing = kNoTiming,
+ };
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(
+ DoAll(SetArgPointee<4>(mockExecutionResult), InvokeWithoutArgs(makeStatusOk)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->compute({});
+ EXPECT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncError) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeGeneralFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteSyncDeadObject) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeSynchronously(_, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->compute({});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(PreparedModelTest, reusableExecuteFenced) {
+ // setup call
+ const uint32_t kNumberOfComputations = 2;
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ const auto mockCallback = MockFencedExecutionCallback::create();
+ EXPECT_CALL(*mockCallback, getExecutionInfo(_, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(DoAll(SetArgPointee<0>(kNoTiming), SetArgPointee<1>(kNoTiming),
+ SetArgPointee<2>(ErrorStatus::NONE), Invoke(makeStatusOk)));
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(kNumberOfComputations)
+ .WillRepeatedly(Invoke(makeFencedExecutionResult(mockCallback)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute repeatedly
+ for (uint32_t i = 0; i < kNumberOfComputations; i++) {
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code
+ << ": " << computeResult.error().message;
+ const auto& [syncFence, callback] = computeResult.value();
+ EXPECT_EQ(syncFence.syncWait({}), nn::SyncFence::FenceState::SIGNALED);
+ ASSERT_NE(callback, nullptr);
+
+ // get results from callback
+ const auto callbackResult = callback();
+ ASSERT_TRUE(callbackResult.has_value()) << "Failed with " << callbackResult.error().code
+ << ": " << callbackResult.error().message;
+ }
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedCallbackError) {
+ // setup call
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ const auto mockCallback = MockFencedExecutionCallback::create();
+ EXPECT_CALL(*mockCallback, getExecutionInfo(_, _, _))
+ .Times(1)
+ .WillOnce(Invoke(DoAll(SetArgPointee<0>(kNoTiming), SetArgPointee<1>(kNoTiming),
+ SetArgPointee<2>(ErrorStatus::GENERAL_FAILURE),
+ Invoke(makeStatusOk))));
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(Invoke(makeFencedExecutionResult(mockCallback)));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_TRUE(computeResult.has_value()) << "Failed with " << computeResult.error().code << ": "
+ << computeResult.error().message;
+ const auto& [syncFence, callback] = computeResult.value();
+ EXPECT_NE(syncFence.syncWait({}), nn::SyncFence::FenceState::ACTIVE);
+ ASSERT_NE(callback, nullptr);
+
+ // verify callback failure
+ const auto callbackResult = callback();
+ ASSERT_FALSE(callbackResult.has_value());
+ EXPECT_EQ(callbackResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedError) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedTransportFailure) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeGeneralTransportFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(PreparedModelTest, reusableExecuteFencedDeadObject) {
+ // setup test
+ const auto mockPreparedModel = MockPreparedModel::create();
+ const auto preparedModel = PreparedModel::create(mockPreparedModel).value();
+ EXPECT_CALL(*mockPreparedModel, executeFenced(_, _, _, _, _, _, _))
+ .Times(1)
+ .WillOnce(InvokeWithoutArgs(makeDeadObjectFailure));
+
+ // create execution
+ const auto createResult = preparedModel->createReusableExecution({}, {}, {});
+ ASSERT_TRUE(createResult.has_value())
+ << "Failed with " << createResult.error().code << ": " << createResult.error().message;
+ ASSERT_NE(createResult.value(), nullptr);
+
+ // invoke compute
+ const auto computeResult = createResult.value()->computeFenced({}, {}, {});
+ ASSERT_FALSE(computeResult.has_value());
+ EXPECT_EQ(computeResult.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
TEST(PreparedModelTest, configureExecutionBurst) {
// setup test
const auto mockPreparedModel = MockPreparedModel::create();
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
index 8fe6b90..fdc90df 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/CommonUtils.h
@@ -20,6 +20,7 @@
#include <cutils/native_handle.h>
#include <hidl/HidlSupport.h>
#include <nnapi/Result.h>
+#include <nnapi/SharedMemory.h>
#include <nnapi/Types.h>
#include <functional>
#include <vector>
@@ -59,19 +60,70 @@
nn::GeneralResult<std::reference_wrapper<const nn::Model>> flushDataFromPointerToShared(
const nn::Model* model, std::optional<nn::Model>* maybeModelInSharedOut);
+// Record a relocation mapping between pointer-based data and shared memory.
+// Only two specializations of this template may exist:
+// - RelocationInfo<const void*> for request inputs
+// - RelocationInfo<void*> for request outputs
+template <typename PointerType>
+struct RelocationInfo {
+ PointerType data;
+ size_t length;
+ size_t offset;
+};
+using InputRelocationInfo = RelocationInfo<const void*>;
+using OutputRelocationInfo = RelocationInfo<void*>;
+
+// Keep track of the relocation mapping between pointer-based data and shared memory pool,
+// and provide method to copy the data between pointers and the shared memory pool.
+// Only two specializations of this template may exist:
+// - RelocationTracker<InputRelocationInfo> for request inputs
+// - RelocationTracker<OutputRelocationInfo> for request outputs
+template <typename RelocationInfoType>
+class RelocationTracker {
+ public:
+ static nn::GeneralResult<std::unique_ptr<RelocationTracker>> create(
+ std::vector<RelocationInfoType> relocationInfos, nn::SharedMemory memory) {
+ auto mapping = NN_TRY(map(memory));
+ return std::make_unique<RelocationTracker<RelocationInfoType>>(
+ std::move(relocationInfos), std::move(memory), std::move(mapping));
+ }
+
+ RelocationTracker(std::vector<RelocationInfoType> relocationInfos, nn::SharedMemory memory,
+ nn::Mapping mapping)
+ : kRelocationInfos(std::move(relocationInfos)),
+ kMemory(std::move(memory)),
+ kMapping(std::move(mapping)) {}
+
+ // Specializations defined in CommonUtils.cpp.
+ // For InputRelocationTracker, this method will copy pointer data to the shared memory pool.
+ // For OutputRelocationTracker, this method will copy shared memory data to the pointers.
+ void flush() const;
+
+ private:
+ const std::vector<RelocationInfoType> kRelocationInfos;
+ const nn::SharedMemory kMemory;
+ const nn::Mapping kMapping;
+};
+using InputRelocationTracker = RelocationTracker<InputRelocationInfo>;
+using OutputRelocationTracker = RelocationTracker<OutputRelocationInfo>;
+
+struct RequestRelocation {
+ std::unique_ptr<InputRelocationTracker> input;
+ std::unique_ptr<OutputRelocationTracker> output;
+};
+
// Relocate pointer-based data to shared memory. If `request` has no
// Request::Argument::LifeTime::POINTER data, the function returns with a reference to `request`. If
// `request` has Request::Argument::LifeTime::POINTER data, the request is copied to
// `maybeRequestInSharedOut` with the POINTER data relocated to a memory pool, and the function
-// returns with a reference to `*maybeRequestInSharedOut`.
-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::GeneralResult<void> unflushDataFromSharedToPointer(
- const nn::Request& request, const std::optional<nn::Request>& maybeRequestInShared);
+// returns with a reference to `*maybeRequestInSharedOut`. The `relocationOut` will be set to track
+// the input and output relocations.
+//
+// Unlike `flushDataFromPointerToShared`, this method will not copy the input pointer data to the
+// shared memory pool. Use `relocationOut` to flush the input or output data after the call.
+nn::GeneralResult<std::reference_wrapper<const nn::Request>> convertRequestFromPointerToShared(
+ const nn::Request* request, std::optional<nn::Request>* maybeRequestInSharedOut,
+ RequestRelocation* relocationOut);
nn::GeneralResult<std::vector<uint32_t>> countNumberOfConsumers(
size_t numberOfOperands, const std::vector<nn::Operation>& operations);
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/InvalidExecution.h b/neuralnetworks/utils/common/include/nnapi/hal/InvalidExecution.h
new file mode 100644
index 0000000..5b00221
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/InvalidExecution.h
@@ -0,0 +1,41 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_INVALID_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_INVALID_EXECUTION_H
+
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+class InvalidExecution final : public nn::IExecution {
+ public:
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_INVALID_EXECUTION_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/InvalidPreparedModel.h b/neuralnetworks/utils/common/include/nnapi/hal/InvalidPreparedModel.h
index 3e1dca7..de30aae 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/InvalidPreparedModel.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/InvalidPreparedModel.h
@@ -40,6 +40,10 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientExecution.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientExecution.h
new file mode 100644
index 0000000..d0084e8
--- /dev/null
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientExecution.h
@@ -0,0 +1,66 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_EXECUTION_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_EXECUTION_H
+
+#include <android-base/thread_annotations.h>
+#include <nnapi/IExecution.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 ResilientExecution final : public nn::IExecution,
+ public std::enable_shared_from_this<ResilientExecution> {
+ struct PrivateConstructorTag {};
+
+ public:
+ using Factory = std::function<nn::GeneralResult<nn::SharedExecution>()>;
+
+ static nn::GeneralResult<std::shared_ptr<const ResilientExecution>> create(
+ Factory makeExecution);
+
+ ResilientExecution(PrivateConstructorTag tag, Factory makeExecution,
+ nn::SharedExecution execution);
+
+ nn::SharedExecution getExecution() const;
+ nn::GeneralResult<nn::SharedExecution> recover(const nn::IExecution* failingExecution) const;
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> compute(
+ const nn::OptionalTimePoint& deadline) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> computeFenced(
+ const std::vector<nn::SyncFence>& waitFor, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+
+ private:
+ bool isValidInternal() const EXCLUDES(mMutex);
+
+ const Factory kMakeExecution;
+ mutable std::mutex mMutex;
+ mutable nn::SharedExecution mExecution GUARDED_BY(mMutex);
+};
+
+} // namespace android::hardware::neuralnetworks::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_RESILIENT_EXECUTION_H
diff --git a/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h b/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h
index a6c1b19..86533ed 100644
--- a/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h
+++ b/neuralnetworks/utils/common/include/nnapi/hal/ResilientPreparedModel.h
@@ -58,12 +58,19 @@
const nn::OptionalDuration& loopTimeoutDuration,
const nn::OptionalDuration& timeoutDurationAfterFence) const override;
+ nn::GeneralResult<nn::SharedExecution> createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const override;
+
nn::GeneralResult<nn::SharedBurst> configureExecutionBurst() const override;
std::any getUnderlyingResource() const override;
private:
bool isValidInternal() const EXCLUDES(mMutex);
+ nn::GeneralResult<nn::SharedExecution> createReusableExecutionInternal(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const;
nn::GeneralResult<nn::SharedBurst> configureExecutionBurstInternal() const;
const Factory kMakePreparedModel;
diff --git a/neuralnetworks/utils/common/src/CommonUtils.cpp b/neuralnetworks/utils/common/src/CommonUtils.cpp
index 4d26795..eaeb9ad 100644
--- a/neuralnetworks/utils/common/src/CommonUtils.cpp
+++ b/neuralnetworks/utils/common/src/CommonUtils.cpp
@@ -200,10 +200,31 @@
return **maybeModelInSharedOut;
}
-nn::GeneralResult<std::reference_wrapper<const nn::Request>> flushDataFromPointerToShared(
- const nn::Request* request, std::optional<nn::Request>* maybeRequestInSharedOut) {
+template <>
+void InputRelocationTracker::flush() const {
+ // Copy from pointers to shared memory.
+ uint8_t* memoryPtr = static_cast<uint8_t*>(std::get<void*>(kMapping.pointer));
+ for (const auto& [data, length, offset] : kRelocationInfos) {
+ std::memcpy(memoryPtr + offset, data, length);
+ }
+}
+
+template <>
+void OutputRelocationTracker::flush() const {
+ // Copy from shared memory to pointers.
+ const uint8_t* memoryPtr = static_cast<const uint8_t*>(
+ std::visit([](auto ptr) { return static_cast<const void*>(ptr); }, kMapping.pointer));
+ for (const auto& [data, length, offset] : kRelocationInfos) {
+ std::memcpy(data, memoryPtr + offset, length);
+ }
+}
+
+nn::GeneralResult<std::reference_wrapper<const nn::Request>> convertRequestFromPointerToShared(
+ const nn::Request* request, std::optional<nn::Request>* maybeRequestInSharedOut,
+ RequestRelocation* relocationOut) {
CHECK(request != nullptr);
CHECK(maybeRequestInSharedOut != nullptr);
+ CHECK(relocationOut != nullptr);
if (hasNoPointerData(*request)) {
return *request;
@@ -213,8 +234,11 @@
// to the caller through `maybeRequestInSharedOut` if the function succeeds.
nn::Request requestInShared = *request;
+ RequestRelocation relocation;
+
// Change input pointers to shared memory.
- nn::ConstantMemoryBuilder inputBuilder(requestInShared.pools.size());
+ nn::MutableMemoryBuilder inputBuilder(requestInShared.pools.size());
+ std::vector<InputRelocationInfo> inputRelocationInfos;
for (auto& input : requestInShared.inputs) {
const auto& location = input.location;
if (input.lifetime != nn::Request::Argument::LifeTime::POINTER) {
@@ -225,17 +249,21 @@
const void* data = std::visit([](auto ptr) { return static_cast<const void*>(ptr); },
location.pointer);
CHECK(data != nullptr);
- input.location = inputBuilder.append(data, location.length);
+ input.location = inputBuilder.append(location.length);
+ inputRelocationInfos.push_back({data, input.location.length, input.location.offset});
}
// Allocate input memory.
if (!inputBuilder.empty()) {
auto memory = NN_TRY(inputBuilder.finish());
- requestInShared.pools.push_back(std::move(memory));
+ requestInShared.pools.push_back(memory);
+ relocation.input = NN_TRY(
+ InputRelocationTracker::create(std::move(inputRelocationInfos), std::move(memory)));
}
// Change output pointers to shared memory.
nn::MutableMemoryBuilder outputBuilder(requestInShared.pools.size());
+ std::vector<OutputRelocationInfo> outputRelocationInfos;
for (auto& output : requestInShared.outputs) {
const auto& location = output.location;
if (output.lifetime != nn::Request::Argument::LifeTime::POINTER) {
@@ -243,62 +271,25 @@
}
output.lifetime = nn::Request::Argument::LifeTime::POOL;
+ void* data = std::get<void*>(location.pointer);
+ CHECK(data != nullptr);
output.location = outputBuilder.append(location.length);
+ outputRelocationInfos.push_back({data, output.location.length, output.location.offset});
}
// Allocate output memory.
if (!outputBuilder.empty()) {
auto memory = NN_TRY(outputBuilder.finish());
- requestInShared.pools.push_back(std::move(memory));
+ requestInShared.pools.push_back(memory);
+ relocation.output = NN_TRY(OutputRelocationTracker::create(std::move(outputRelocationInfos),
+ std::move(memory)));
}
*maybeRequestInSharedOut = requestInShared;
+ *relocationOut = std::move(relocation);
return **maybeRequestInSharedOut;
}
-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::SharedMemory>(maybeRequestInShared->pools.back())) {
- return {};
- }
- const auto& requestInShared = *maybeRequestInShared;
-
- // Map the memory.
- const auto& outputMemory = std::get<nn::SharedMemory>(requestInShared.pools.back());
- const auto [pointer, size, context] = NN_TRY(map(outputMemory));
- const uint8_t* constantPointer =
- std::visit([](const auto& o) { return static_cast<const uint8_t*>(o); }, pointer);
-
- // Flush each output pointer.
- CHECK_EQ(request.outputs.size(), requestInShared.outputs.size());
- for (size_t i = 0; i < request.outputs.size(); ++i) {
- const auto& location = request.outputs[i].location;
- const auto& locationInShared = requestInShared.outputs[i].location;
- if (!std::holds_alternative<void*>(location.pointer)) {
- continue;
- }
-
- // Get output pointer and size.
- void* data = std::get<void*>(location.pointer);
- CHECK(data != nullptr);
- const size_t length = location.length;
-
- // Get output pool location.
- CHECK(requestInShared.outputs[i].lifetime == nn::Request::Argument::LifeTime::POOL);
- const size_t index = locationInShared.poolIndex;
- const size_t offset = locationInShared.offset;
- const size_t outputPoolIndex = requestInShared.pools.size() - 1;
- CHECK(locationInShared.length == length);
- CHECK(index == outputPoolIndex);
-
- // Flush memory.
- std::memcpy(data, constantPointer + offset, length);
- }
-
- return {};
-}
-
nn::GeneralResult<std::vector<uint32_t>> countNumberOfConsumers(
size_t numberOfOperands, const std::vector<nn::Operation>& operations) {
return makeGeneralFailure(nn::countNumberOfConsumers(numberOfOperands, operations));
diff --git a/neuralnetworks/utils/common/src/InvalidExecution.cpp b/neuralnetworks/utils/common/src/InvalidExecution.cpp
new file mode 100644
index 0000000..c4edd25
--- /dev/null
+++ b/neuralnetworks/utils/common/src/InvalidExecution.cpp
@@ -0,0 +1,40 @@
+/*
+ * 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 "InvalidExecution.h"
+
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> InvalidExecution::compute(
+ const nn::OptionalTimePoint& /*deadline*/) const {
+ return NN_ERROR() << "InvalidExecution";
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+InvalidExecution::computeFenced(const std::vector<nn::SyncFence>& /*waitFor*/,
+ const nn::OptionalTimePoint& /*deadline*/,
+ const nn::OptionalDuration& /*timeoutDurationAfterFence*/) const {
+ return NN_ERROR() << "InvalidExecution";
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/src/InvalidPreparedModel.cpp b/neuralnetworks/utils/common/src/InvalidPreparedModel.cpp
index 9081e1f..8195462 100644
--- a/neuralnetworks/utils/common/src/InvalidPreparedModel.cpp
+++ b/neuralnetworks/utils/common/src/InvalidPreparedModel.cpp
@@ -42,6 +42,12 @@
return NN_ERROR() << "InvalidPreparedModel";
}
+nn::GeneralResult<nn::SharedExecution> InvalidPreparedModel::createReusableExecution(
+ const nn::Request& /*request*/, nn::MeasureTiming /*measure*/,
+ const nn::OptionalDuration& /*loopTimeoutDuration*/) const {
+ return NN_ERROR() << "InvalidPreparedModel";
+}
+
nn::GeneralResult<nn::SharedBurst> InvalidPreparedModel::configureExecutionBurst() const {
return NN_ERROR() << "InvalidPreparedModel";
}
diff --git a/neuralnetworks/utils/common/src/ResilientExecution.cpp b/neuralnetworks/utils/common/src/ResilientExecution.cpp
new file mode 100644
index 0000000..46b404a
--- /dev/null
+++ b/neuralnetworks/utils/common/src/ResilientExecution.cpp
@@ -0,0 +1,126 @@
+/*
+ * 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 "ResilientExecution.h"
+
+#include "InvalidBurst.h"
+#include "ResilientBurst.h"
+
+#include <android-base/logging.h>
+#include <android-base/thread_annotations.h>
+#include <nnapi/IExecution.h>
+#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+
+#include <functional>
+#include <memory>
+#include <mutex>
+#include <sstream>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::utils {
+namespace {
+
+template <typename FnType>
+auto protect(const ResilientExecution& resilientExecution, const FnType& fn)
+ -> decltype(fn(*resilientExecution.getExecution())) {
+ auto execution = resilientExecution.getExecution();
+ auto result = fn(*execution);
+
+ // Immediately return if prepared model is not dead.
+ if (result.has_value() || result.error().code != nn::ErrorStatus::DEAD_OBJECT) {
+ return result;
+ }
+
+ // Attempt recovery and return if it fails.
+ auto maybeExecution = resilientExecution.recover(execution.get());
+ if (!maybeExecution.has_value()) {
+ const auto& [message, code] = maybeExecution.error();
+ std::ostringstream oss;
+ oss << ", and failed to recover dead prepared model with error " << code << ": " << message;
+ result.error().message += oss.str();
+ return result;
+ }
+ execution = std::move(maybeExecution).value();
+
+ return fn(*execution);
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const ResilientExecution>> ResilientExecution::create(
+ Factory makeExecution) {
+ if (makeExecution == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "utils::ResilientExecution::create must have non-empty makeExecution";
+ }
+ auto execution = NN_TRY(makeExecution());
+ CHECK(execution != nullptr);
+ return std::make_shared<ResilientExecution>(PrivateConstructorTag{}, std::move(makeExecution),
+ std::move(execution));
+}
+
+ResilientExecution::ResilientExecution(PrivateConstructorTag /*tag*/, Factory makeExecution,
+ nn::SharedExecution execution)
+ : kMakeExecution(std::move(makeExecution)), mExecution(std::move(execution)) {
+ CHECK(kMakeExecution != nullptr);
+ CHECK(mExecution != nullptr);
+}
+
+nn::SharedExecution ResilientExecution::getExecution() const {
+ std::lock_guard guard(mMutex);
+ return mExecution;
+}
+
+nn::GeneralResult<nn::SharedExecution> ResilientExecution::recover(
+ const nn::IExecution* failingExecution) const {
+ std::lock_guard guard(mMutex);
+
+ // Another caller updated the failing prepared model.
+ if (mExecution.get() != failingExecution) {
+ return mExecution;
+ }
+
+ mExecution = NN_TRY(kMakeExecution());
+ return mExecution;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+ResilientExecution::compute(const nn::OptionalTimePoint& deadline) const {
+ const auto fn = [&deadline](const nn::IExecution& execution) {
+ return execution.compute(deadline);
+ };
+ return protect(*this, fn);
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+ResilientExecution::computeFenced(const std::vector<nn::SyncFence>& waitFor,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalDuration& timeoutDurationAfterFence) const {
+ const auto fn = [&waitFor, &deadline,
+ &timeoutDurationAfterFence](const nn::IExecution& execution) {
+ return execution.computeFenced(waitFor, deadline, timeoutDurationAfterFence);
+ };
+ return protect(*this, fn);
+}
+
+bool ResilientExecution::isValidInternal() const {
+ return true;
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp b/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp
index 5dd5f99..1ae19bc 100644
--- a/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp
+++ b/neuralnetworks/utils/common/src/ResilientPreparedModel.cpp
@@ -17,7 +17,9 @@
#include "ResilientPreparedModel.h"
#include "InvalidBurst.h"
+#include "InvalidExecution.h"
#include "ResilientBurst.h"
+#include "ResilientExecution.h"
#include <android-base/logging.h>
#include <android-base/thread_annotations.h>
@@ -127,6 +129,21 @@
return protect(*this, fn);
}
+nn::GeneralResult<nn::SharedExecution> ResilientPreparedModel::createReusableExecution(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const {
+#if 0
+ auto self = shared_from_this();
+ ResilientExecution::Factory makeExecution =
+ [preparedModel = std::move(self), request, measure, loopTimeoutDuration] {
+ return preparedModel->createReusableExecutionInternal(request, measure, loopTimeoutDuration);
+ };
+ return ResilientExecution::create(std::move(makeExecution));
+#else
+ return createReusableExecutionInternal(request, measure, loopTimeoutDuration);
+#endif
+}
+
nn::GeneralResult<nn::SharedBurst> ResilientPreparedModel::configureExecutionBurst() const {
#if 0
auto self = shared_from_this();
@@ -140,6 +157,19 @@
#endif
}
+nn::GeneralResult<nn::SharedExecution> ResilientPreparedModel::createReusableExecutionInternal(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration) const {
+ if (!isValidInternal()) {
+ return std::make_shared<const InvalidExecution>();
+ }
+ const auto fn = [&request, measure,
+ &loopTimeoutDuration](const nn::IPreparedModel& preparedModel) {
+ return preparedModel.createReusableExecution(request, measure, loopTimeoutDuration);
+ };
+ return protect(*this, fn);
+}
+
std::any ResilientPreparedModel::getUnderlyingResource() const {
return getPreparedModel()->getUnderlyingResource();
}
diff --git a/neuralnetworks/utils/common/test/MockExecution.h b/neuralnetworks/utils/common/test/MockExecution.h
new file mode 100644
index 0000000..91e3428
--- /dev/null
+++ b/neuralnetworks/utils/common/test/MockExecution.h
@@ -0,0 +1,38 @@
+/*
+ * 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.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_TEST_MOCK_EXECUTION
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_TEST_MOCK_EXECUTION
+
+#include <gmock/gmock.h>
+#include <gtest/gtest.h>
+#include <nnapi/IExecution.h>
+
+namespace android::nn {
+
+class MockExecution final : public IExecution {
+ public:
+ MOCK_METHOD((ExecutionResult<std::pair<std::vector<OutputShape>, Timing>>), compute,
+ (const OptionalTimePoint& deadline), (const, override));
+ MOCK_METHOD((GeneralResult<std::pair<SyncFence, ExecuteFencedInfoCallback>>), computeFenced,
+ (const std::vector<SyncFence>& waitFor, const OptionalTimePoint& deadline,
+ const OptionalDuration& timeoutDurationAfterFence),
+ (const, override));
+};
+
+} // namespace android::nn
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_UTILS_COMMON_TEST_MOCK_EXECUTION
diff --git a/neuralnetworks/utils/common/test/MockPreparedModel.h b/neuralnetworks/utils/common/test/MockPreparedModel.h
index c004861..c8ce006 100644
--- a/neuralnetworks/utils/common/test/MockPreparedModel.h
+++ b/neuralnetworks/utils/common/test/MockPreparedModel.h
@@ -35,6 +35,10 @@
const OptionalDuration& loopTimeoutDuration,
const OptionalDuration& timeoutDurationAfterFence),
(const, override));
+ MOCK_METHOD((GeneralResult<SharedExecution>), createReusableExecution,
+ (const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalDuration& loopTimeoutDuration),
+ (const, override));
MOCK_METHOD(GeneralResult<SharedBurst>, configureExecutionBurst, (), (const, override));
MOCK_METHOD(std::any, getUnderlyingResource, (), (const, override));
};
diff --git a/neuralnetworks/utils/common/test/ResilientExecution.cpp b/neuralnetworks/utils/common/test/ResilientExecution.cpp
new file mode 100644
index 0000000..c0737fb
--- /dev/null
+++ b/neuralnetworks/utils/common/test/ResilientExecution.cpp
@@ -0,0 +1,260 @@
+/*
+ * 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 <gmock/gmock.h>
+#include <nnapi/TypeUtils.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientExecution.h>
+#include <utility>
+#include "MockExecution.h"
+
+namespace android::hardware::neuralnetworks::utils {
+namespace {
+
+using ::testing::_;
+using ::testing::InvokeWithoutArgs;
+using ::testing::Return;
+
+using SharedMockExecution = std::shared_ptr<const nn::MockExecution>;
+using MockExecutionFactory = ::testing::MockFunction<nn::GeneralResult<nn::SharedExecution>()>;
+
+SharedMockExecution createMockExecution() {
+ return std::make_shared<const nn::MockExecution>();
+}
+
+std::tuple<SharedMockExecution, std::unique_ptr<MockExecutionFactory>,
+ std::shared_ptr<const ResilientExecution>>
+setup() {
+ auto mockExecution = std::make_shared<const nn::MockExecution>();
+
+ auto mockExecutionFactory = std::make_unique<MockExecutionFactory>();
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(Return(mockExecution));
+
+ auto buffer = ResilientExecution::create(mockExecutionFactory->AsStdFunction()).value();
+ return std::make_tuple(std::move(mockExecution), std::move(mockExecutionFactory),
+ std::move(buffer));
+}
+
+constexpr auto makeError = [](nn::ErrorStatus status) {
+ return [status](const auto&... /*args*/) { return nn::error(status); };
+};
+const auto kReturnGeneralFailure = makeError(nn::ErrorStatus::GENERAL_FAILURE);
+const auto kReturnDeadObject = makeError(nn::ErrorStatus::DEAD_OBJECT);
+
+const auto kNoExecutionError =
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>{};
+const auto kNoFencedExecutionError =
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>(
+ std::make_pair(nn::SyncFence::createAsSignaled(), nullptr));
+
+} // namespace
+
+TEST(ResilientExecutionTest, invalidExecutionFactory) {
+ // setup call
+ const auto invalidExecutionFactory = ResilientExecution::Factory{};
+
+ // run test
+ const auto result = ResilientExecution::create(invalidExecutionFactory);
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::INVALID_ARGUMENT);
+}
+
+TEST(ResilientExecutionTest, executionFactoryFailure) {
+ // setup call
+ const auto invalidExecutionFactory = kReturnGeneralFailure;
+
+ // run test
+ const auto result = ResilientExecution::create(invalidExecutionFactory);
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(ResilientExecutionTest, getExecution) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+
+ // run test
+ const auto result = execution->getExecution();
+
+ // verify result
+ EXPECT_TRUE(result == mockExecution);
+}
+
+TEST(ResilientExecutionTest, compute) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, compute(_)).Times(1).WillOnce(Return(kNoExecutionError));
+
+ // run test
+ const auto result = execution->compute({});
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+}
+
+TEST(ResilientExecutionTest, computeError) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, compute(_)).Times(1).WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = execution->compute({});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(ResilientExecutionTest, computeDeadObjectFailedRecovery) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, compute(_)).Times(1).WillOnce(kReturnDeadObject);
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = execution->compute({});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(ResilientExecutionTest, computeDeadObjectSuccessfulRecovery) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, compute(_)).Times(1).WillOnce(kReturnDeadObject);
+ const auto recoveredMockExecution = createMockExecution();
+ EXPECT_CALL(*recoveredMockExecution, compute(_)).Times(1).WillOnce(Return(kNoExecutionError));
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(Return(recoveredMockExecution));
+
+ // run test
+ const auto result = execution->compute({});
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+}
+
+TEST(ResilientExecutionTest, computeFenced) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, computeFenced(_, _, _))
+ .Times(1)
+ .WillOnce(Return(kNoFencedExecutionError));
+
+ // run test
+ const auto result = execution->computeFenced({}, {}, {});
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+}
+
+TEST(ResilientExecutionTest, computeFencedError) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, computeFenced(_, _, _)).Times(1).WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = execution->computeFenced({}, {}, {});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
+TEST(ResilientExecutionTest, computeFencedDeadObjectFailedRecovery) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, computeFenced(_, _, _)).Times(1).WillOnce(kReturnDeadObject);
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = execution->computeFenced({}, {}, {});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::DEAD_OBJECT);
+}
+
+TEST(ResilientExecutionTest, computeFencedDeadObjectSuccessfulRecovery) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ EXPECT_CALL(*mockExecution, computeFenced(_, _, _)).Times(1).WillOnce(kReturnDeadObject);
+ const auto recoveredMockExecution = createMockExecution();
+ EXPECT_CALL(*recoveredMockExecution, computeFenced(_, _, _))
+ .Times(1)
+ .WillOnce(Return(kNoFencedExecutionError));
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(Return(recoveredMockExecution));
+
+ // run test
+ const auto result = execution->computeFenced({}, {}, {});
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+}
+
+TEST(ResilientExecutionTest, recover) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ const auto recoveredMockExecution = createMockExecution();
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(Return(recoveredMockExecution));
+
+ // run test
+ const auto result = execution->recover(mockExecution.get());
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+ EXPECT_TRUE(result.value() == recoveredMockExecution);
+}
+
+TEST(ResilientExecutionTest, recoverFailure) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ const auto recoveredMockExecution = createMockExecution();
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = execution->recover(mockExecution.get());
+
+ // verify result
+ EXPECT_FALSE(result.has_value());
+}
+
+TEST(ResilientExecutionTest, someoneElseRecovered) {
+ // setup call
+ const auto [mockExecution, mockExecutionFactory, execution] = setup();
+ const auto recoveredMockExecution = createMockExecution();
+ EXPECT_CALL(*mockExecutionFactory, Call()).Times(1).WillOnce(Return(recoveredMockExecution));
+ execution->recover(mockExecution.get());
+
+ // run test
+ const auto result = execution->recover(mockExecution.get());
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+ EXPECT_TRUE(result.value() == recoveredMockExecution);
+}
+
+} // namespace android::hardware::neuralnetworks::utils
diff --git a/neuralnetworks/utils/common/test/ResilientPreparedModelTest.cpp b/neuralnetworks/utils/common/test/ResilientPreparedModelTest.cpp
index 6d86e10..d396ca8 100644
--- a/neuralnetworks/utils/common/test/ResilientPreparedModelTest.cpp
+++ b/neuralnetworks/utils/common/test/ResilientPreparedModelTest.cpp
@@ -55,6 +55,7 @@
const auto kReturnGeneralFailure = makeError(nn::ErrorStatus::GENERAL_FAILURE);
const auto kReturnDeadObject = makeError(nn::ErrorStatus::DEAD_OBJECT);
+const auto kNoCreateReusableExecutionError = nn::GeneralResult<nn::SharedExecution>{};
const auto kNoExecutionError =
nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>{};
const auto kNoFencedExecutionError =
@@ -231,6 +232,36 @@
<< "Failed with " << result.error().code << ": " << result.error().message;
}
+TEST(ResilientPreparedModelTest, createReusableExecution) {
+ // setup call
+ const auto [mockPreparedModel, mockPreparedModelFactory, preparedModel] = setup();
+ EXPECT_CALL(*mockPreparedModel, createReusableExecution(_, _, _))
+ .Times(1)
+ .WillOnce(Return(kNoCreateReusableExecutionError));
+
+ // run test
+ const auto result = preparedModel->createReusableExecution({}, {}, {});
+
+ // verify result
+ ASSERT_TRUE(result.has_value())
+ << "Failed with " << result.error().code << ": " << result.error().message;
+}
+
+TEST(ResilientPreparedModelTest, createReusableExecutionError) {
+ // setup call
+ const auto [mockPreparedModel, mockPreparedModelFactory, preparedModel] = setup();
+ EXPECT_CALL(*mockPreparedModel, createReusableExecution(_, _, _))
+ .Times(1)
+ .WillOnce(kReturnGeneralFailure);
+
+ // run test
+ const auto result = preparedModel->createReusableExecution({}, {}, {});
+
+ // verify result
+ ASSERT_FALSE(result.has_value());
+ EXPECT_EQ(result.error().code, nn::ErrorStatus::GENERAL_FAILURE);
+}
+
TEST(ResilientPreparedModelTest, getUnderlyingResource) {
// setup call
const auto [mockPreparedModel, mockPreparedModelFactory, preparedModel] = setup();