Implement NNAPI canonical interfaces
This CL implements the canonical IDevice, IPreparedModel, and IBuffer
interfaces for the 1.0, 1.1, 1.2, and 1.3 NN HIDL HAL interfaces.
Further, it introduces "Resilient" adapter interfaces to automatically
retrieve a handle to a recovered interface object after it has died and
rebooted.
This CL also updates the conversion code from returning nn::Result to
nn::GeneralResult, which includes a ErrorStatus code in the case of an
error.
Finally, this CL introduces a new static library
neuralnetworks_utils_hal_service which consists of a single function
::android::nn::hal::getDevices which can be used by the NNAPI runtime to
retrieve the HIDL services without knowing the underlying HIDL types.
Bug: 160668438
Test: mma
Test: NeuralNetworksTest_static
Change-Id: Iec6ae739df196b4034ffb35ea76781fd541ffec3
Merged-In: Iec6ae739df196b4034ffb35ea76781fd541ffec3
(cherry picked from commit 3670c385c4b12aef975ab67e5d2b0f5fe79134c2)
diff --git a/neuralnetworks/1.3/utils/Android.bp b/neuralnetworks/1.3/utils/Android.bp
index 279b250..d5d897d 100644
--- a/neuralnetworks/1.3/utils/Android.bp
+++ b/neuralnetworks/1.3/utils/Android.bp
@@ -20,6 +20,7 @@
srcs: ["src/*"],
local_include_dirs: ["include/nnapi/hal/1.3/"],
export_include_dirs: ["include"],
+ cflags: ["-Wthread-safety"],
static_libs: [
"neuralnetworks_types",
"neuralnetworks_utils_hal_common",
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
new file mode 100644
index 0000000..637179d
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Buffer.h
@@ -0,0 +1,52 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
+
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <memory>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Buffer final : public nn::IBuffer {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Buffer>> create(
+ sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token);
+
+ Buffer(PrivateConstructorTag tag, sp<V1_3::IBuffer> buffer,
+ nn::Request::MemoryDomainToken token);
+
+ nn::Request::MemoryDomainToken getToken() const override;
+
+ nn::GeneralResult<void> copyTo(const nn::Memory& dst) const override;
+ nn::GeneralResult<void> copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const override;
+
+ private:
+ const sp<V1_3::IBuffer> kBuffer;
+ const nn::Request::MemoryDomainToken kToken;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_BUFFER_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
new file mode 100644
index 0000000..d46b111
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Callbacks.h
@@ -0,0 +1,83 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
+
+#include <android/hardware/neuralnetworks/1.0/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.0/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.2/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Callbacks.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModelCallback final : public IPreparedModelCallback,
+ public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::GeneralResult<nn::SharedPreparedModel>;
+
+ Return<void> notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status,
+ const sp<V1_2::IPreparedModel>& preparedModel) override;
+ Return<void> notify_1_3(ErrorStatus status, const sp<IPreparedModel>& preparedModel) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+class ExecutionCallback final : public IExecutionCallback, public hal::utils::IProtectedCallback {
+ public:
+ using Data = nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>;
+
+ Return<void> notify(V1_0::ErrorStatus status) override;
+ Return<void> notify_1_2(V1_0::ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) override;
+ Return<void> notify_1_3(ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) override;
+
+ void notifyAsDeadObject() override;
+
+ Data get();
+
+ private:
+ void notifyInternal(Data result);
+
+ hal::utils::TransferValue<Data> mData;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_CALLBACKS_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
index 43987a9..64aa96e 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Conversions.h
@@ -25,54 +25,54 @@
namespace android::nn {
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType);
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType);
-Result<Priority> convert(const hal::V1_3::Priority& priority);
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType);
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType);
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority);
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities);
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_3::Capabilities::OperandPerformance& operandPerformance);
-Result<Operation> convert(const hal::V1_3::Operation& operation);
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
-Result<Operand> convert(const hal::V1_3::Operand& operand);
-Result<Model> convert(const hal::V1_3::Model& model);
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
-Result<Request> convert(const hal::V1_3::Request& request);
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation);
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime);
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand);
+GeneralResult<Model> convert(const hal::V1_3::Model& model);
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph);
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc);
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole);
+GeneralResult<Request> convert(const hal::V1_3::Request& request);
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool);
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint);
+GeneralResult<OptionalTimeoutDuration> convert(
const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration);
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& errorStatus);
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles);
} // namespace android::nn
namespace android::hardware::neuralnetworks::V1_3::utils {
-nn::Result<OperandType> convert(const nn::OperandType& operandType);
-nn::Result<OperationType> convert(const nn::OperationType& operationType);
-nn::Result<Priority> convert(const nn::Priority& priority);
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities);
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType);
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType);
+nn::GeneralResult<Priority> convert(const nn::Priority& priority);
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities);
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance);
-nn::Result<Operation> convert(const nn::Operation& operation);
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
-nn::Result<Operand> convert(const nn::Operand& operand);
-nn::Result<Model> convert(const nn::Model& model);
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph);
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole);
-nn::Result<Request> convert(const nn::Request& request);
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<Operation> convert(const nn::Operation& operation);
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime);
+nn::GeneralResult<Operand> convert(const nn::Operand& operand);
+nn::GeneralResult<Model> convert(const nn::Model& model);
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph);
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc);
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole);
+nn::GeneralResult<Request> convert(const nn::Request& request);
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool);
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint);
+nn::GeneralResult<OptionalTimeoutDuration> convert(
const nn::OptionalTimeoutDuration& optionalTimeoutDuration);
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus);
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles);
} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
new file mode 100644
index 0000000..2f6c46a
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Device.h
@@ -0,0 +1,91 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
+
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class Device final : public nn::IDevice {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const Device>> create(std::string name,
+ sp<V1_3::IDevice> device);
+
+ Device(PrivateConstructorTag tag, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities, std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded,
+ sp<V1_3::IDevice> device, hal::utils::DeathHandler deathHandler);
+
+ const std::string& getName() const override;
+ const std::string& getVersionString() const override;
+ nn::Version getFeatureLevel() const override;
+ nn::DeviceType getType() const override;
+ const std::vector<nn::Extension>& getSupportedExtensions() const override;
+ const nn::Capabilities& getCapabilities() const override;
+ std::pair<uint32_t, uint32_t> getNumberOfCacheFilesNeeded() const override;
+
+ nn::GeneralResult<void> wait() const override;
+
+ nn::GeneralResult<std::vector<bool>> getSupportedOperations(
+ const nn::Model& model) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedPreparedModel> prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache,
+ const nn::CacheToken& token) const override;
+
+ nn::GeneralResult<nn::SharedBuffer> allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const override;
+
+ private:
+ const std::string kName;
+ const std::string kVersionString;
+ const nn::DeviceType kDeviceType;
+ const std::vector<nn::Extension> kExtensions;
+ const nn::Capabilities kCapabilities;
+ const std::pair<uint32_t, uint32_t> kNumberOfCacheFilesNeeded;
+ const sp<V1_3::IDevice> kDevice;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_DEVICE_H
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
new file mode 100644
index 0000000..e0d69dd
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/PreparedModel.h
@@ -0,0 +1,71 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
+
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+class PreparedModel final : public nn::IPreparedModel {
+ struct PrivateConstructorTag {};
+
+ public:
+ static nn::GeneralResult<std::shared_ptr<const PreparedModel>> create(
+ sp<V1_3::IPreparedModel> preparedModel);
+
+ PreparedModel(PrivateConstructorTag tag, sp<V1_3::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler);
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const override;
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> executeFenced(
+ const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const override;
+
+ std::any getUnderlyingResource() const override;
+
+ private:
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeSynchronously(
+ const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const;
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> executeAsynchronously(
+ const Request& request, V1_2::MeasureTiming measure, const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const;
+
+ const sp<V1_3::IPreparedModel> kPreparedModel;
+ const hal::utils::DeathHandler kDeathHandler;
+};
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_PREPARED_MODEL_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
new file mode 100644
index 0000000..2bc3257
--- /dev/null
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Service.h
@@ -0,0 +1,31 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <string>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name);
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
+
+#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_3_UTILS_SERVICE_H
diff --git a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
index f8c975d..e61859d 100644
--- a/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
+++ b/neuralnetworks/1.3/utils/include/nnapi/hal/1.3/Utils.h
@@ -22,6 +22,7 @@
#include <android-base/logging.h>
#include <android/hardware/neuralnetworks/1.3/types.h>
#include <nnapi/Result.h>
+#include <nnapi/TypeUtils.h>
#include <nnapi/Types.h>
#include <nnapi/Validation.h>
#include <nnapi/hal/1.0/Conversions.h>
@@ -35,10 +36,14 @@
template <typename Type>
nn::Result<void> validate(const Type& halObject) {
- const auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeCanonical = nn::convert(halObject);
+ if (!maybeCanonical.has_value()) {
+ return nn::error() << maybeCanonical.error().message;
+ }
+ const auto version = NN_TRY(nn::validate(maybeCanonical.value()));
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return {};
}
@@ -55,9 +60,14 @@
template <typename Type>
decltype(nn::convert(std::declval<Type>())) validatedConvertToCanonical(const Type& halObject) {
auto canonical = NN_TRY(nn::convert(halObject));
- const auto version = NN_TRY(nn::validate(canonical));
+ const auto maybeVersion = nn::validate(canonical);
+ if (!maybeVersion.has_value()) {
+ return nn::error() << maybeVersion.error();
+ }
+ const auto version = maybeVersion.value();
if (version > utils::kVersion) {
- return NN_ERROR() << "";
+ return NN_ERROR() << "Insufficient version: " << version << " vs required "
+ << utils::kVersion;
}
return canonical;
}
diff --git a/neuralnetworks/1.3/utils/src/Buffer.cpp b/neuralnetworks/1.3/utils/src/Buffer.cpp
new file mode 100644
index 0000000..f3fe9b5
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Buffer.cpp
@@ -0,0 +1,93 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Buffer.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IBuffer.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/HandleError.h>
+
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <memory>
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<std::shared_ptr<const Buffer>> Buffer::create(
+ sp<V1_3::IBuffer> buffer, nn::Request::MemoryDomainToken token) {
+ if (buffer == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Buffer::create must have non-null buffer";
+ }
+ if (token == static_cast<nn::Request::MemoryDomainToken>(0)) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Buffer::create must have non-zero token";
+ }
+
+ return std::make_shared<const Buffer>(PrivateConstructorTag{}, std::move(buffer), token);
+}
+
+Buffer::Buffer(PrivateConstructorTag /*tag*/, sp<V1_3::IBuffer> buffer,
+ nn::Request::MemoryDomainToken token)
+ : kBuffer(std::move(buffer)), kToken(token) {
+ CHECK(kBuffer != nullptr);
+ CHECK(kToken != static_cast<nn::Request::MemoryDomainToken>(0));
+}
+
+nn::Request::MemoryDomainToken Buffer::getToken() const {
+ return kToken;
+}
+
+nn::GeneralResult<void> Buffer::copyTo(const nn::Memory& dst) const {
+ const auto hidlDst = NN_TRY(V1_0::utils::convert(dst));
+
+ const auto ret = kBuffer->copyTo(hidlDst);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "IBuffer::copyTo failed with " << toString(status);
+ }
+
+ return {};
+}
+
+nn::GeneralResult<void> Buffer::copyFrom(const nn::Memory& src,
+ const nn::Dimensions& dimensions) const {
+ const auto hidlSrc = NN_TRY(V1_0::utils::convert(src));
+ const auto hidlDimensions = hidl_vec<uint32_t>(dimensions);
+
+ const auto ret = kBuffer->copyFrom(hidlSrc, hidlDimensions);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "IBuffer::copyFrom failed with " << toString(status);
+ }
+
+ return {};
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Callbacks.cpp b/neuralnetworks/1.3/utils/src/Callbacks.cpp
new file mode 100644
index 0000000..ff81275
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Callbacks.cpp
@@ -0,0 +1,184 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Callbacks.h"
+
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IExecutionCallback.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModelCallback.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.0/Conversions.h>
+#include <nnapi/hal/1.0/PreparedModel.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/PreparedModel.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+#include <nnapi/hal/TransferValue.h>
+
+#include <utility>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ return NN_TRY(V1_0::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<V1_2::IPreparedModel>& preparedModel) {
+ return NN_TRY(V1_2::utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> convertPreparedModel(
+ const sp<IPreparedModel>& preparedModel) {
+ return NN_TRY(utils::PreparedModel::create(preparedModel));
+}
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionGeneralResults(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return hal::utils::makeExecutionFailure(
+ convertExecutionGeneralResultsHelper(outputShapes, timing));
+}
+
+} // namespace
+
+Return<void> PreparedModelCallback::notify(V1_0::ErrorStatus status,
+ const sp<V1_0::IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_2(V1_0::ErrorStatus status,
+ const sp<V1_2::IPreparedModel>& preparedModel) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+Return<void> PreparedModelCallback::notify_1_3(ErrorStatus status,
+ const sp<IPreparedModel>& preparedModel) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "preparedModel failed with " << toString(status));
+ } else if (preparedModel == nullptr) {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Returned preparedModel is nullptr");
+ } else {
+ notifyInternal(convertPreparedModel(preparedModel));
+ }
+ return Void();
+}
+
+void PreparedModelCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+PreparedModelCallback::Data PreparedModelCallback::get() {
+ return mData.take();
+}
+
+void PreparedModelCallback::notifyInternal(PreparedModelCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+// ExecutionCallback methods begin here
+
+Return<void> ExecutionCallback::notify(V1_0::ErrorStatus status) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal({});
+ }
+ return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_2(V1_0::ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != V1_0::ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+ }
+ return Void();
+}
+
+Return<void> ExecutionCallback::notify_1_3(ErrorStatus status,
+ const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ notifyInternal(NN_ERROR(canonical) << "execute failed with " << toString(status));
+ } else {
+ notifyInternal(convertExecutionGeneralResults(outputShapes, timing));
+ }
+ return Void();
+}
+
+void ExecutionCallback::notifyAsDeadObject() {
+ notifyInternal(NN_ERROR(nn::ErrorStatus::DEAD_OBJECT) << "Dead object");
+}
+
+ExecutionCallback::Data ExecutionCallback::get() {
+ return mData.take();
+}
+
+void ExecutionCallback::notifyInternal(ExecutionCallback::Data result) {
+ mData.put(std::move(result));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Conversions.cpp b/neuralnetworks/1.3/utils/src/Conversions.cpp
index 4c54e3b..0dc0785 100644
--- a/neuralnetworks/1.3/utils/src/Conversions.cpp
+++ b/neuralnetworks/1.3/utils/src/Conversions.cpp
@@ -27,6 +27,7 @@
#include <nnapi/hal/1.0/Conversions.h>
#include <nnapi/hal/1.2/Conversions.h>
#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
#include <algorithm>
#include <chrono>
@@ -79,7 +80,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convertVec(const hidl_vec<Type>& arguments) {
std::vector<ConvertOutput<Type>> canonical;
canonical.reserve(arguments.size());
for (const auto& argument : arguments) {
@@ -89,25 +90,25 @@
}
template <typename Type>
-Result<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
+GeneralResult<std::vector<ConvertOutput<Type>>> convert(const hidl_vec<Type>& arguments) {
return convertVec(arguments);
}
} // anonymous namespace
-Result<OperandType> convert(const hal::V1_3::OperandType& operandType) {
+GeneralResult<OperandType> convert(const hal::V1_3::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-Result<OperationType> convert(const hal::V1_3::OperationType& operationType) {
+GeneralResult<OperationType> convert(const hal::V1_3::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-Result<Priority> convert(const hal::V1_3::Priority& priority) {
+GeneralResult<Priority> convert(const hal::V1_3::Priority& priority) {
return static_cast<Priority>(priority);
}
-Result<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
+GeneralResult<Capabilities> convert(const hal::V1_3::Capabilities& capabilities) {
const bool validOperandTypes = std::all_of(
capabilities.operandPerformance.begin(), capabilities.operandPerformance.end(),
[](const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
@@ -115,13 +116,14 @@
return !maybeType.has_value() ? false : validOperandType(maybeType.value());
});
if (!validOperandTypes) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Invalid OperandType when converting OperandPerformance in Capabilities";
}
auto operandPerformance = NN_TRY(convert(capabilities.operandPerformance));
- auto table =
- NN_TRY(Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)));
+ auto table = NN_TRY(hal::utils::makeGeneralFailure(
+ Capabilities::OperandPerformanceTable::create(std::move(operandPerformance)),
+ nn::ErrorStatus::GENERAL_FAILURE));
return Capabilities{
.relaxedFloat32toFloat16PerformanceScalar =
@@ -134,7 +136,7 @@
};
}
-Result<Capabilities::OperandPerformance> convert(
+GeneralResult<Capabilities::OperandPerformance> convert(
const hal::V1_3::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -142,7 +144,7 @@
};
}
-Result<Operation> convert(const hal::V1_3::Operation& operation) {
+GeneralResult<Operation> convert(const hal::V1_3::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -150,11 +152,11 @@
};
}
-Result<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
+GeneralResult<Operand::LifeTime> convert(const hal::V1_3::OperandLifeTime& operandLifeTime) {
return static_cast<Operand::LifeTime>(operandLifeTime);
}
-Result<Operand> convert(const hal::V1_3::Operand& operand) {
+GeneralResult<Operand> convert(const hal::V1_3::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -166,7 +168,7 @@
};
}
-Result<Model> convert(const hal::V1_3::Model& model) {
+GeneralResult<Model> convert(const hal::V1_3::Model& model) {
return Model{
.main = NN_TRY(convert(model.main)),
.referenced = NN_TRY(convert(model.referenced)),
@@ -177,7 +179,7 @@
};
}
-Result<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
+GeneralResult<Model::Subgraph> convert(const hal::V1_3::Subgraph& subgraph) {
auto operations = NN_TRY(convert(subgraph.operations));
// Verify number of consumers.
@@ -186,9 +188,10 @@
CHECK(subgraph.operands.size() == numberOfConsumers.size());
for (size_t i = 0; i < subgraph.operands.size(); ++i) {
if (subgraph.operands[i].numberOfConsumers != numberOfConsumers[i]) {
- return NN_ERROR() << "Invalid numberOfConsumers for operand " << i << ", expected "
- << numberOfConsumers[i] << " but found "
- << subgraph.operands[i].numberOfConsumers;
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid numberOfConsumers for operand " << i << ", expected "
+ << numberOfConsumers[i] << " but found "
+ << subgraph.operands[i].numberOfConsumers;
}
}
@@ -200,11 +203,11 @@
};
}
-Result<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
+GeneralResult<BufferDesc> convert(const hal::V1_3::BufferDesc& bufferDesc) {
return BufferDesc{.dimensions = bufferDesc.dimensions};
}
-Result<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
+GeneralResult<BufferRole> convert(const hal::V1_3::BufferRole& bufferRole) {
return BufferRole{
.modelIndex = bufferRole.modelIndex,
.ioIndex = bufferRole.ioIndex,
@@ -212,7 +215,7 @@
};
}
-Result<Request> convert(const hal::V1_3::Request& request) {
+GeneralResult<Request> convert(const hal::V1_3::Request& request) {
return Request{
.inputs = NN_TRY(convert(request.inputs)),
.outputs = NN_TRY(convert(request.outputs)),
@@ -220,7 +223,7 @@
};
}
-Result<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
+GeneralResult<Request::MemoryPool> convert(const hal::V1_3::Request::MemoryPool& memoryPool) {
using Discriminator = hal::V1_3::Request::MemoryPool::hidl_discriminator;
switch (memoryPool.getDiscriminator()) {
case Discriminator::hidlMemory:
@@ -228,15 +231,16 @@
case Discriminator::token:
return static_cast<Request::MemoryDomainToken>(memoryPool.token());
}
- return NN_ERROR() << "Invalid Request::MemoryPool discriminator "
- << underlyingType(memoryPool.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid Request::MemoryPool discriminator "
+ << underlyingType(memoryPool.getDiscriminator());
}
-Result<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
+GeneralResult<OptionalTimePoint> convert(const hal::V1_3::OptionalTimePoint& optionalTimePoint) {
constexpr auto kTimePointMaxCount = TimePoint::max().time_since_epoch().count();
- const auto makeTimePoint = [](uint64_t count) -> Result<OptionalTimePoint> {
+ const auto makeTimePoint = [](uint64_t count) -> GeneralResult<OptionalTimePoint> {
if (count > kTimePointMaxCount) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimePoint because the count exceeds the max";
}
const auto nanoseconds = std::chrono::nanoseconds{count};
@@ -250,16 +254,17 @@
case Discriminator::nanosecondsSinceEpoch:
return makeTimePoint(optionalTimePoint.nanosecondsSinceEpoch());
}
- return NN_ERROR() << "Invalid OptionalTimePoint discriminator "
- << underlyingType(optionalTimePoint.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid OptionalTimePoint discriminator "
+ << underlyingType(optionalTimePoint.getDiscriminator());
}
-Result<OptionalTimeoutDuration> convert(
+GeneralResult<OptionalTimeoutDuration> convert(
const hal::V1_3::OptionalTimeoutDuration& optionalTimeoutDuration) {
constexpr auto kTimeoutDurationMaxCount = TimeoutDuration::max().count();
- const auto makeTimeoutDuration = [](uint64_t count) -> Result<OptionalTimeoutDuration> {
+ const auto makeTimeoutDuration = [](uint64_t count) -> GeneralResult<OptionalTimeoutDuration> {
if (count > kTimeoutDurationMaxCount) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimeoutDuration because the count exceeds the max";
}
return TimeoutDuration{count};
@@ -272,11 +277,12 @@
case Discriminator::nanoseconds:
return makeTimeoutDuration(optionalTimeoutDuration.nanoseconds());
}
- return NN_ERROR() << "Invalid OptionalTimeoutDuration discriminator "
- << underlyingType(optionalTimeoutDuration.getDiscriminator());
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid OptionalTimeoutDuration discriminator "
+ << underlyingType(optionalTimeoutDuration.getDiscriminator());
}
-Result<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
+GeneralResult<ErrorStatus> convert(const hal::V1_3::ErrorStatus& status) {
switch (status) {
case hal::V1_3::ErrorStatus::NONE:
case hal::V1_3::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -289,10 +295,11 @@
case hal::V1_3::ErrorStatus::RESOURCE_EXHAUSTED_PERSISTENT:
return static_cast<ErrorStatus>(status);
}
- return NN_ERROR() << "Invalid ErrorStatus " << underlyingType(status);
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Invalid ErrorStatus " << underlyingType(status);
}
-Result<std::vector<BufferRole>> convert(
+GeneralResult<std::vector<BufferRole>> convert(
const hardware::hidl_vec<hal::V1_3::BufferRole>& bufferRoles) {
return convertVec(bufferRoles);
}
@@ -304,32 +311,32 @@
using utils::convert;
-nn::Result<V1_0::PerformanceInfo> convert(
+nn::GeneralResult<V1_0::PerformanceInfo> convert(
const nn::Capabilities::PerformanceInfo& performanceInfo) {
return V1_0::utils::convert(performanceInfo);
}
-nn::Result<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
+nn::GeneralResult<V1_0::DataLocation> convert(const nn::DataLocation& dataLocation) {
return V1_0::utils::convert(dataLocation);
}
-nn::Result<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
+nn::GeneralResult<hidl_vec<uint8_t>> convert(const nn::Model::OperandValues& operandValues) {
return V1_0::utils::convert(operandValues);
}
-nn::Result<hidl_memory> convert(const nn::Memory& memory) {
+nn::GeneralResult<hidl_memory> convert(const nn::Memory& memory) {
return V1_0::utils::convert(memory);
}
-nn::Result<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
+nn::GeneralResult<V1_0::RequestArgument> convert(const nn::Request::Argument& argument) {
return V1_0::utils::convert(argument);
}
-nn::Result<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
+nn::GeneralResult<V1_2::Operand::ExtraParams> convert(const nn::Operand::ExtraParams& extraParams) {
return V1_2::utils::convert(extraParams);
}
-nn::Result<V1_2::Model::ExtensionNameAndPrefix> convert(
+nn::GeneralResult<V1_2::Model::ExtensionNameAndPrefix> convert(
const nn::Model::ExtensionNameAndPrefix& extensionNameAndPrefix) {
return V1_2::utils::convert(extensionNameAndPrefix);
}
@@ -338,7 +345,7 @@
using ConvertOutput = std::decay_t<decltype(convert(std::declval<Input>()).value())>;
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convertVec(const std::vector<Type>& arguments) {
hidl_vec<ConvertOutput<Type>> halObject(arguments.size());
for (size_t i = 0; i < arguments.size(); ++i) {
halObject[i] = NN_TRY(convert(arguments[i]));
@@ -347,42 +354,41 @@
}
template <typename Type>
-nn::Result<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
+nn::GeneralResult<hidl_vec<ConvertOutput<Type>>> convert(const std::vector<Type>& arguments) {
return convertVec(arguments);
}
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Memory& memory) {
Request::MemoryPool ret;
ret.hidlMemory(NN_TRY(convert(memory)));
return ret;
}
-nn::Result<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::Request::MemoryDomainToken& token) {
Request::MemoryPool ret;
ret.token(underlyingType(token));
return ret;
}
-nn::Result<Request::MemoryPool> makeMemoryPool(
- const std::shared_ptr<const nn::IBuffer>& /*buffer*/) {
- return NN_ERROR() << "Unable to make memory pool from IBuffer";
+nn::GeneralResult<Request::MemoryPool> makeMemoryPool(const nn::SharedBuffer& /*buffer*/) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Unable to make memory pool from IBuffer";
}
} // anonymous namespace
-nn::Result<OperandType> convert(const nn::OperandType& operandType) {
+nn::GeneralResult<OperandType> convert(const nn::OperandType& operandType) {
return static_cast<OperandType>(operandType);
}
-nn::Result<OperationType> convert(const nn::OperationType& operationType) {
+nn::GeneralResult<OperationType> convert(const nn::OperationType& operationType) {
return static_cast<OperationType>(operationType);
}
-nn::Result<Priority> convert(const nn::Priority& priority) {
+nn::GeneralResult<Priority> convert(const nn::Priority& priority) {
return static_cast<Priority>(priority);
}
-nn::Result<Capabilities> convert(const nn::Capabilities& capabilities) {
+nn::GeneralResult<Capabilities> convert(const nn::Capabilities& capabilities) {
std::vector<nn::Capabilities::OperandPerformance> operandPerformance;
operandPerformance.reserve(capabilities.operandPerformance.asVector().size());
std::copy_if(capabilities.operandPerformance.asVector().begin(),
@@ -403,7 +409,7 @@
};
}
-nn::Result<Capabilities::OperandPerformance> convert(
+nn::GeneralResult<Capabilities::OperandPerformance> convert(
const nn::Capabilities::OperandPerformance& operandPerformance) {
return Capabilities::OperandPerformance{
.type = NN_TRY(convert(operandPerformance.type)),
@@ -411,7 +417,7 @@
};
}
-nn::Result<Operation> convert(const nn::Operation& operation) {
+nn::GeneralResult<Operation> convert(const nn::Operation& operation) {
return Operation{
.type = NN_TRY(convert(operation.type)),
.inputs = operation.inputs,
@@ -419,14 +425,15 @@
};
}
-nn::Result<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
+nn::GeneralResult<OperandLifeTime> convert(const nn::Operand::LifeTime& operandLifeTime) {
if (operandLifeTime == nn::Operand::LifeTime::POINTER) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
return static_cast<OperandLifeTime>(operandLifeTime);
}
-nn::Result<Operand> convert(const nn::Operand& operand) {
+nn::GeneralResult<Operand> convert(const nn::Operand& operand) {
return Operand{
.type = NN_TRY(convert(operand.type)),
.dimensions = operand.dimensions,
@@ -439,9 +446,10 @@
};
}
-nn::Result<Model> convert(const nn::Model& model) {
+nn::GeneralResult<Model> convert(const nn::Model& model) {
if (!hal::utils::hasNoPointerData(model)) {
- return NN_ERROR() << "Model cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Model cannot be converted because it contains pointer-based memory";
}
return Model{
@@ -454,7 +462,7 @@
};
}
-nn::Result<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
+nn::GeneralResult<Subgraph> convert(const nn::Model::Subgraph& subgraph) {
auto operands = NN_TRY(convert(subgraph.operands));
// Update number of consumers.
@@ -473,11 +481,11 @@
};
}
-nn::Result<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
+nn::GeneralResult<BufferDesc> convert(const nn::BufferDesc& bufferDesc) {
return BufferDesc{.dimensions = bufferDesc.dimensions};
}
-nn::Result<BufferRole> convert(const nn::BufferRole& bufferRole) {
+nn::GeneralResult<BufferRole> convert(const nn::BufferRole& bufferRole) {
return BufferRole{
.modelIndex = bufferRole.modelIndex,
.ioIndex = bufferRole.ioIndex,
@@ -485,9 +493,10 @@
};
}
-nn::Result<Request> convert(const nn::Request& request) {
+nn::GeneralResult<Request> convert(const nn::Request& request) {
if (!hal::utils::hasNoPointerData(request)) {
- return NN_ERROR() << "Request cannot be converted because it contains pointer-based memory";
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Request cannot be converted because it contains pointer-based memory";
}
return Request{
@@ -497,30 +506,31 @@
};
}
-nn::Result<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
+nn::GeneralResult<Request::MemoryPool> convert(const nn::Request::MemoryPool& memoryPool) {
return std::visit([](const auto& o) { return makeMemoryPool(o); }, memoryPool);
}
-nn::Result<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
+nn::GeneralResult<OptionalTimePoint> convert(const nn::OptionalTimePoint& optionalTimePoint) {
OptionalTimePoint ret;
if (optionalTimePoint.has_value()) {
const auto count = optionalTimePoint.value().time_since_epoch().count();
if (count < 0) {
- return NN_ERROR() << "Unable to convert OptionalTimePoint because time since epoch "
- "count is negative";
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "Unable to convert OptionalTimePoint because time since epoch count is "
+ "negative";
}
ret.nanosecondsSinceEpoch(count);
}
return ret;
}
-nn::Result<OptionalTimeoutDuration> convert(
+nn::GeneralResult<OptionalTimeoutDuration> convert(
const nn::OptionalTimeoutDuration& optionalTimeoutDuration) {
OptionalTimeoutDuration ret;
if (optionalTimeoutDuration.has_value()) {
const auto count = optionalTimeoutDuration.value().count();
if (count < 0) {
- return NN_ERROR()
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
<< "Unable to convert OptionalTimeoutDuration because count is negative";
}
ret.nanoseconds(count);
@@ -528,7 +538,7 @@
return ret;
}
-nn::Result<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
+nn::GeneralResult<ErrorStatus> convert(const nn::ErrorStatus& errorStatus) {
switch (errorStatus) {
case nn::ErrorStatus::NONE:
case nn::ErrorStatus::DEVICE_UNAVAILABLE:
@@ -545,7 +555,7 @@
}
}
-nn::Result<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
+nn::GeneralResult<hidl_vec<BufferRole>> convert(const std::vector<nn::BufferRole>& bufferRoles) {
return convertVec(bufferRoles);
}
diff --git a/neuralnetworks/1.3/utils/src/Device.cpp b/neuralnetworks/1.3/utils/src/Device.cpp
new file mode 100644
index 0000000..c215f39
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Device.cpp
@@ -0,0 +1,269 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Device.h"
+
+#include "Buffer.h"
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "PreparedModel.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IDevice.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IBuffer.h>
+#include <nnapi/IDevice.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/OperandTypes.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.1/Conversions.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/1.2/Device.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <any>
+#include <functional>
+#include <memory>
+#include <optional>
+#include <string>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<hidl_vec<sp<IPreparedModel>>> convert(
+ const std::vector<nn::SharedPreparedModel>& preparedModels) {
+ hidl_vec<sp<IPreparedModel>> hidlPreparedModels(preparedModels.size());
+ for (size_t i = 0; i < preparedModels.size(); ++i) {
+ std::any underlyingResource = preparedModels[i]->getUnderlyingResource();
+ if (const auto* hidlPreparedModel =
+ std::any_cast<sp<IPreparedModel>>(&underlyingResource)) {
+ hidlPreparedModels[i] = *hidlPreparedModel;
+ } else {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "Unable to convert from nn::IPreparedModel to V1_3::IPreparedModel";
+ }
+ }
+ return hidlPreparedModels;
+}
+
+nn::GeneralResult<nn::SharedBuffer> convert(
+ nn::GeneralResult<std::shared_ptr<const Buffer>> result) {
+ return NN_TRY(std::move(result));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const Device>> Device::create(std::string name,
+ sp<V1_3::IDevice> device) {
+ if (name.empty()) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Device::create must have non-empty name";
+ }
+ if (device == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::Device::create must have non-null device";
+ }
+
+ auto versionString = NN_TRY(V1_2::utils::initVersionString(device.get()));
+ const auto deviceType = NN_TRY(V1_2::utils::initDeviceType(device.get()));
+ auto extensions = NN_TRY(V1_2::utils::initExtensions(device.get()));
+ auto capabilities = NN_TRY(V1_2::utils::initCapabilities(device.get()));
+ const auto numberOfCacheFilesNeeded =
+ NN_TRY(V1_2::utils::initNumberOfCacheFilesNeeded(device.get()));
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(device));
+ return std::make_shared<const Device>(
+ PrivateConstructorTag{}, std::move(name), std::move(versionString), deviceType,
+ std::move(extensions), std::move(capabilities), numberOfCacheFilesNeeded,
+ std::move(device), std::move(deathHandler));
+}
+
+Device::Device(PrivateConstructorTag /*tag*/, std::string name, std::string versionString,
+ nn::DeviceType deviceType, std::vector<nn::Extension> extensions,
+ nn::Capabilities capabilities,
+ std::pair<uint32_t, uint32_t> numberOfCacheFilesNeeded, sp<V1_3::IDevice> device,
+ hal::utils::DeathHandler deathHandler)
+ : kName(std::move(name)),
+ kVersionString(std::move(versionString)),
+ kDeviceType(deviceType),
+ kExtensions(std::move(extensions)),
+ kCapabilities(std::move(capabilities)),
+ kNumberOfCacheFilesNeeded(numberOfCacheFilesNeeded),
+ kDevice(std::move(device)),
+ kDeathHandler(std::move(deathHandler)) {}
+
+const std::string& Device::getName() const {
+ return kName;
+}
+
+const std::string& Device::getVersionString() const {
+ return kVersionString;
+}
+
+nn::Version Device::getFeatureLevel() const {
+ return nn::Version::ANDROID_R;
+}
+
+nn::DeviceType Device::getType() const {
+ return kDeviceType;
+}
+
+const std::vector<nn::Extension>& Device::getSupportedExtensions() const {
+ return kExtensions;
+}
+
+const nn::Capabilities& Device::getCapabilities() const {
+ return kCapabilities;
+}
+
+std::pair<uint32_t, uint32_t> Device::getNumberOfCacheFilesNeeded() const {
+ return kNumberOfCacheFilesNeeded;
+}
+
+nn::GeneralResult<void> Device::wait() const {
+ const auto ret = kDevice->ping();
+ return hal::utils::handleTransportError(ret);
+}
+
+nn::GeneralResult<std::vector<bool>> Device::getSupportedOperations(const nn::Model& model) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+
+ nn::GeneralResult<std::vector<bool>> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result, &model](ErrorStatus status, const hidl_vec<bool>& supportedOperations) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical)
+ << "IDevice::getSupportedOperations_1_3 failed with " << toString(status);
+ } else if (supportedOperations.size() != model.main.operations.size()) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "IDevice::getSupportedOperations_1_3 returned vector of size "
+ << supportedOperations.size() << " but expected "
+ << model.main.operations.size();
+ } else {
+ result = supportedOperations;
+ }
+ };
+
+ const auto ret = kDevice->getSupportedOperations_1_3(hidlModel, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModel(
+ const nn::Model& model, nn::ExecutionPreference preference, nn::Priority priority,
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ // Ensure that model is ready for IPC.
+ std::optional<nn::Model> maybeModelInShared;
+ const nn::Model& modelInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&model, &maybeModelInShared));
+
+ const auto hidlModel = NN_TRY(convert(modelInShared));
+ const auto hidlPreference = NN_TRY(V1_1::utils::convert(preference));
+ const auto hidlPriority = NN_TRY(convert(priority));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+ const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret =
+ kDevice->prepareModel_1_3(hidlModel, hidlPreference, hidlPriority, hidlDeadline,
+ hidlModelCache, hidlDataCache, hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModel_1_3 failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedPreparedModel> Device::prepareModelFromCache(
+ nn::OptionalTimePoint deadline, const std::vector<nn::NativeHandle>& modelCache,
+ const std::vector<nn::NativeHandle>& dataCache, const nn::CacheToken& token) const {
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlModelCache = NN_TRY(V1_2::utils::convert(modelCache));
+ const auto hidlDataCache = NN_TRY(V1_2::utils::convert(dataCache));
+ const auto hidlToken = token;
+
+ const auto cb = sp<PreparedModelCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret = kDevice->prepareModelFromCache_1_3(hidlDeadline, hidlModelCache, hidlDataCache,
+ hidlToken, cb);
+ const auto status = NN_TRY(hal::utils::handleTransportError(ret));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "prepareModelFromCache_1_3 failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::GeneralResult<nn::SharedBuffer> Device::allocate(
+ const nn::BufferDesc& desc, const std::vector<nn::SharedPreparedModel>& preparedModels,
+ const std::vector<nn::BufferRole>& inputRoles,
+ const std::vector<nn::BufferRole>& outputRoles) const {
+ const auto hidlDesc = NN_TRY(convert(desc));
+ const auto hidlPreparedModels = NN_TRY(convert(preparedModels));
+ const auto hidlInputRoles = NN_TRY(convert(inputRoles));
+ const auto hidlOutputRoles = NN_TRY(convert(outputRoles));
+
+ nn::GeneralResult<nn::SharedBuffer> result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE)
+ << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const sp<IBuffer>& buffer, uint32_t token) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "IDevice::allocate failed with " << toString(status);
+ } else if (buffer == nullptr) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned buffer is nullptr";
+ } else if (token == 0) {
+ result = NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "Returned token is invalid (0)";
+ } else {
+ result = convert(
+ Buffer::create(buffer, static_cast<nn::Request::MemoryDomainToken>(token)));
+ }
+ };
+
+ const auto ret =
+ kDevice->allocate(hidlDesc, hidlPreparedModels, hidlInputRoles, hidlOutputRoles, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/PreparedModel.cpp b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
new file mode 100644
index 0000000..df9b280
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/PreparedModel.cpp
@@ -0,0 +1,267 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "PreparedModel.h"
+
+#include "Callbacks.h"
+#include "Conversions.h"
+#include "Utils.h"
+
+#include <android/hardware/neuralnetworks/1.0/types.h>
+#include <android/hardware/neuralnetworks/1.1/types.h>
+#include <android/hardware/neuralnetworks/1.2/types.h>
+#include <android/hardware/neuralnetworks/1.3/IPreparedModel.h>
+#include <android/hardware/neuralnetworks/1.3/types.h>
+#include <nnapi/IPreparedModel.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/1.2/Conversions.h>
+#include <nnapi/hal/CommonUtils.h>
+#include <nnapi/hal/HandleError.h>
+#include <nnapi/hal/ProtectCallback.h>
+
+#include <memory>
+#include <tuple>
+#include <utility>
+#include <vector>
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+namespace {
+
+nn::GeneralResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+convertExecutionResultsHelper(const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(outputShapes)),
+ NN_TRY(validatedConvertToCanonical(timing)));
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> convertExecutionResults(
+ const hidl_vec<V1_2::OutputShape>& outputShapes, const V1_2::Timing& timing) {
+ return hal::utils::makeExecutionFailure(convertExecutionResultsHelper(outputShapes, timing));
+}
+
+nn::GeneralResult<hidl_vec<hidl_handle>> convertSyncFences(
+ const std::vector<nn::SyncFence>& syncFences) {
+ hidl_vec<hidl_handle> handles(syncFences.size());
+ for (size_t i = 0; i < syncFences.size(); ++i) {
+ handles[i] = NN_TRY(V1_2::utils::convert(syncFences[i].getHandle()));
+ }
+ return handles;
+}
+
+nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> convertFencedExecutionCallbackResults(
+ const V1_2::Timing& timingLaunched, const V1_2::Timing& timingFenced) {
+ return std::make_pair(NN_TRY(validatedConvertToCanonical(timingLaunched)),
+ NN_TRY(validatedConvertToCanonical(timingFenced)));
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+convertExecuteFencedResults(const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ auto resultSyncFence = nn::SyncFence::createAsSignaled();
+ if (syncFence.getNativeHandle() != nullptr) {
+ auto nativeHandle = NN_TRY(validatedConvertToCanonical(syncFence));
+ resultSyncFence = NN_TRY(hal::utils::makeGeneralFailure(
+ nn::SyncFence::create(std::move(nativeHandle)), nn::ErrorStatus::GENERAL_FAILURE));
+ }
+
+ if (callback == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "callback is null";
+ }
+
+ // Create callback which can be used to retrieve the execution error status and timings.
+ nn::ExecuteFencedInfoCallback resultCallback =
+ [callback]() -> nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> {
+ nn::GeneralResult<std::pair<nn::Timing, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const V1_2::Timing& timingLaunched,
+ const V1_2::Timing& timingFenced) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical = validatedConvertToCanonical(status).value_or(
+ nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "getExecutionInfo failed with " << toString(status);
+ } else {
+ result = convertFencedExecutionCallbackResults(timingLaunched, timingFenced);
+ }
+ };
+
+ const auto ret = callback->getExecutionInfo(cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+
+ return result;
+ };
+
+ return std::make_pair(std::move(resultSyncFence), std::move(resultCallback));
+}
+
+} // namespace
+
+nn::GeneralResult<std::shared_ptr<const PreparedModel>> PreparedModel::create(
+ sp<V1_3::IPreparedModel> preparedModel) {
+ if (preparedModel == nullptr) {
+ return NN_ERROR(nn::ErrorStatus::INVALID_ARGUMENT)
+ << "V1_3::utils::PreparedModel::create must have non-null preparedModel";
+ }
+
+ auto deathHandler = NN_TRY(hal::utils::DeathHandler::create(preparedModel));
+ return std::make_shared<const PreparedModel>(PrivateConstructorTag{}, std::move(preparedModel),
+ std::move(deathHandler));
+}
+
+PreparedModel::PreparedModel(PrivateConstructorTag /*tag*/, sp<V1_3::IPreparedModel> preparedModel,
+ hal::utils::DeathHandler deathHandler)
+ : kPreparedModel(std::move(preparedModel)), kDeathHandler(std::move(deathHandler)) {}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeSynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const auto cb = [&result](ErrorStatus status, const hidl_vec<V1_2::OutputShape>& outputShapes,
+ const V1_2::Timing& timing) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeSynchronously failed with " << toString(status);
+ } else {
+ result = convertExecutionResults(outputShapes, timing);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeSynchronously_1_3(request, measure, deadline,
+ loopTimeoutDuration, cb);
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+
+ return result;
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>
+PreparedModel::executeAsynchronously(const Request& request, V1_2::MeasureTiming measure,
+ const OptionalTimePoint& deadline,
+ const OptionalTimeoutDuration& loopTimeoutDuration) const {
+ const auto cb = sp<ExecutionCallback>::make();
+ const auto scoped = kDeathHandler.protectCallback(cb.get());
+
+ const auto ret =
+ kPreparedModel->execute_1_3(request, measure, deadline, loopTimeoutDuration, cb);
+ const auto status =
+ NN_TRY(hal::utils::makeExecutionFailure(hal::utils::handleTransportError(ret)));
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ return NN_ERROR(canonical) << "executeAsynchronously failed with " << toString(status);
+ }
+
+ return cb->get();
+}
+
+nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> PreparedModel::execute(
+ const nn::Request& request, nn::MeasureTiming measure,
+ const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared = NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared)));
+
+ const auto hidlRequest = NN_TRY(hal::utils::makeExecutionFailure(convert(requestInShared)));
+ const auto hidlMeasure =
+ NN_TRY(hal::utils::makeExecutionFailure(V1_2::utils::convert(measure)));
+ const auto hidlDeadline = NN_TRY(hal::utils::makeExecutionFailure(convert(deadline)));
+ const auto hidlLoopTimeoutDuration =
+ NN_TRY(hal::utils::makeExecutionFailure(convert(loopTimeoutDuration)));
+
+ nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ const bool preferSynchronous = true;
+
+ // Execute synchronously if allowed.
+ if (preferSynchronous) {
+ result = executeSynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Run asymchronous execution if execution has not already completed.
+ if (!result.has_value()) {
+ result = executeAsynchronously(hidlRequest, hidlMeasure, hidlDeadline,
+ hidlLoopTimeoutDuration);
+ }
+
+ // Flush output buffers if suxcessful execution.
+ if (result.has_value()) {
+ NN_TRY(hal::utils::makeExecutionFailure(
+ hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared)));
+ }
+
+ return result;
+}
+
+nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>>
+PreparedModel::executeFenced(const nn::Request& request, const std::vector<nn::SyncFence>& waitFor,
+ nn::MeasureTiming measure, const nn::OptionalTimePoint& deadline,
+ const nn::OptionalTimeoutDuration& loopTimeoutDuration,
+ const nn::OptionalTimeoutDuration& timeoutDurationAfterFence) const {
+ // Ensure that request is ready for IPC.
+ std::optional<nn::Request> maybeRequestInShared;
+ const nn::Request& requestInShared =
+ NN_TRY(hal::utils::flushDataFromPointerToShared(&request, &maybeRequestInShared));
+
+ const auto hidlRequest = NN_TRY(convert(requestInShared));
+ const auto hidlWaitFor = NN_TRY(convertSyncFences(waitFor));
+ const auto hidlMeasure = NN_TRY(V1_2::utils::convert(measure));
+ const auto hidlDeadline = NN_TRY(convert(deadline));
+ const auto hidlLoopTimeoutDuration = NN_TRY(convert(loopTimeoutDuration));
+ const auto hidlTimeoutDurationAfterFence = NN_TRY(convert(timeoutDurationAfterFence));
+
+ nn::GeneralResult<std::pair<nn::SyncFence, nn::ExecuteFencedInfoCallback>> result =
+ NN_ERROR(nn::ErrorStatus::GENERAL_FAILURE) << "uninitialized";
+ auto cb = [&result](ErrorStatus status, const hidl_handle& syncFence,
+ const sp<IFencedExecutionCallback>& callback) {
+ if (status != ErrorStatus::NONE) {
+ const auto canonical =
+ validatedConvertToCanonical(status).value_or(nn::ErrorStatus::GENERAL_FAILURE);
+ result = NN_ERROR(canonical) << "executeFenced failed with " << toString(status);
+ } else {
+ result = convertExecuteFencedResults(syncFence, callback);
+ }
+ };
+
+ const auto ret = kPreparedModel->executeFenced(hidlRequest, hidlWaitFor, hidlMeasure,
+ hidlDeadline, hidlLoopTimeoutDuration,
+ hidlTimeoutDurationAfterFence, cb);
+ NN_TRY(hal::utils::handleTransportError(ret));
+ auto [syncFence, callback] = NN_TRY(std::move(result));
+
+ // If executeFenced required the request memory to be moved into shared memory, block here until
+ // the fenced execution has completed and flush the memory back.
+ if (maybeRequestInShared.has_value()) {
+ const auto state = syncFence.syncWait({});
+ if (state != nn::SyncFence::FenceState::SIGNALED) {
+ return NN_ERROR() << "syncWait failed with " << state;
+ }
+ NN_TRY(hal::utils::unflushDataFromSharedToPointer(request, maybeRequestInShared));
+ }
+
+ return std::make_pair(std::move(syncFence), std::move(callback));
+}
+
+std::any PreparedModel::getUnderlyingResource() const {
+ sp<V1_3::IPreparedModel> resource = kPreparedModel;
+ return resource;
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils
diff --git a/neuralnetworks/1.3/utils/src/Service.cpp b/neuralnetworks/1.3/utils/src/Service.cpp
new file mode 100644
index 0000000..62887fb
--- /dev/null
+++ b/neuralnetworks/1.3/utils/src/Service.cpp
@@ -0,0 +1,41 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "Service.h"
+
+#include <nnapi/IDevice.h>
+#include <nnapi/Result.h>
+#include <nnapi/Types.h>
+#include <nnapi/hal/ResilientDevice.h>
+#include <string>
+#include "Device.h"
+
+namespace android::hardware::neuralnetworks::V1_3::utils {
+
+nn::GeneralResult<nn::SharedDevice> getDevice(const std::string& name) {
+ hal::utils::ResilientDevice::Factory makeDevice =
+ [name](bool blocking) -> nn::GeneralResult<nn::SharedDevice> {
+ auto service = blocking ? IDevice::getService(name) : IDevice::tryGetService(name);
+ if (service == nullptr) {
+ return NN_ERROR() << (blocking ? "getService" : "tryGetService") << " returned nullptr";
+ }
+ return Device::create(name, std::move(service));
+ };
+
+ return hal::utils::ResilientDevice::create(std::move(makeDevice));
+}
+
+} // namespace android::hardware::neuralnetworks::V1_3::utils