Merge changes from topic "aosp-nnapi-burst-compat-lib" am: 593f0ecaf4 (226d3a68) · Commits · e / os / android_hardware_interfaces

neuralnetworks/1.2/utils/Android.bp

+6 −1

Original line number	Diff line number	Diff line
		@@ -27,7 +27,6 @@ cc_library_static {
		name: "neuralnetworks_utils_hal_1_2",
		defaults: ["neuralnetworks_utils_defaults"],
		srcs: ["src/*"],
		exclude_srcs: ["src/ExecutionBurst*"],
		local_include_dirs: ["include/nnapi/hal/1.2/"],
		export_include_dirs: ["include"],
		cflags: ["-Wthread-safety"],
		@@ -41,10 +40,16 @@ cc_library_static {
		"android.hardware.neuralnetworks@1.0",
		"android.hardware.neuralnetworks@1.1",
		"android.hardware.neuralnetworks@1.2",
		"libfmq",
		],
		export_static_lib_headers: [
		"neuralnetworks_utils_hal_common",
		],
		product_variables: {
		debuggable: { // eng and userdebug builds
		cflags: ["-DNN_DEBUGGABLE"],
		},
		},
		}

		cc_test {

neuralnetworks/1.2/utils/include/nnapi/hal/1.2/Conversions.h

+1 −0

Original line number	Diff line number	Diff line
		@@ -52,6 +52,7 @@ GeneralResult<Capabilities> convert(const hal::V1_2::Capabilities& capabilities)
		GeneralResult<Model> convert(const hal::V1_2::Model& model);
		GeneralResult<MeasureTiming> convert(const hal::V1_2::MeasureTiming& measureTiming);
		GeneralResult<Timing> convert(const hal::V1_2::Timing& timing);
		GeneralResult<SharedMemory> convert(const hardware::hidl_memory& memory);

		GeneralResult<std::vector<Extension>> convert(
		const hardware::hidl_vec<hal::V1_2::Extension>& extensions);

neuralnetworks/1.2/utils/include/nnapi/hal/1.2/ExecutionBurstController.h

+113 −110

Original line number	Diff line number	Diff line
		@@ -14,23 +14,28 @@
		* limitations under the License.
		*/

		#ifndef ANDROID_FRAMEWORKS_ML_NN_COMMON_EXECUTION_BURST_CONTROLLER_H
		#define ANDROID_FRAMEWORKS_ML_NN_COMMON_EXECUTION_BURST_CONTROLLER_H
		#ifndef ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_BURST_CONTROLLER_H
		#define ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_BURST_CONTROLLER_H

		#include "ExecutionBurstUtils.h"

		#include <android-base/macros.h>
		#include <android-base/thread_annotations.h>
		#include <android/hardware/neuralnetworks/1.0/types.h>
		#include <android/hardware/neuralnetworks/1.1/types.h>
		#include <android/hardware/neuralnetworks/1.2/IBurstCallback.h>
		#include <android/hardware/neuralnetworks/1.2/IBurstContext.h>
		#include <android/hardware/neuralnetworks/1.2/IPreparedModel.h>
		#include <android/hardware/neuralnetworks/1.2/types.h>
		#include <fmq/MessageQueue.h>
		#include <hidl/MQDescriptor.h>
		#include <nnapi/IBurst.h>
		#include <nnapi/IPreparedModel.h>
		#include <nnapi/Result.h>
		#include <nnapi/Types.h>
		#include <nnapi/hal/ProtectCallback.h>

		#include <atomic>
		#include <chrono>
		#include <functional>
		#include <map>
		#include <memory>
		#include <mutex>
		@@ -39,147 +44,145 @@
		#include <utility>
		#include <vector>

		namespace android::nn {
		namespace android::hardware::neuralnetworks::V1_2::utils {

		/**
		* The ExecutionBurstController class manages both the serialization and
		* deserialization of data across FMQ, making it appear to the runtime as a
		* regular synchronous inference. Additionally, this class manages the burst's
		* memory cache.
		* The ExecutionBurstController class manages both the serialization and deserialization of data
		* across FMQ, making it appear to the runtime as a regular synchronous inference. Additionally,
		* this class manages the burst's memory cache.
		*/
		class ExecutionBurstController {
		DISALLOW_IMPLICIT_CONSTRUCTORS(ExecutionBurstController);
		class ExecutionBurstController final : public nn::IBurst {
		struct PrivateConstructorTag {};

		public:
		using FallbackFunction =
		std::function<nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>>(
		const nn::Request&, nn::MeasureTiming)>;

		/**
		* NN runtime burst callback object and memory cache.
		* NN runtime memory cache.
		*
		* MemoryCache associates a Memory object with a slot number to be passed across FMQ. The
		* ExecutionBurstServer can use this callback to retrieve a hidl_memory corresponding to the
		* slot via HIDL.
		*
		* ExecutionBurstCallback associates a hidl_memory object with a slot number
		* to be passed across FMQ. The ExecutionBurstServer can use this callback
		* to retrieve this hidl_memory corresponding to the slot via HIDL.
		* Whenever a hidl_memory object is copied, it will duplicate the underlying file descriptor.
		* Because the NN runtime currently copies the hidl_memory on each execution, it is difficult to
		* associate hidl_memory objects with previously cached hidl_memory objects. For this reason,
		* callers of this class must pair each hidl_memory object with an associated key. For
		* efficiency, if two hidl_memory objects represent the same underlying buffer, they must use
		* the same key.
		*
		* Whenever a hidl_memory object is copied, it will duplicate the underlying
		* file descriptor. Because the NN runtime currently copies the hidl_memory
		* on each execution, it is difficult to associate hidl_memory objects with
		* previously cached hidl_memory objects. For this reason, callers of this
		* class must pair each hidl_memory object with an associated key. For
		* efficiency, if two hidl_memory objects represent the same underlying
		* buffer, they must use the same key.
		* This class is thread-safe.
		*/
		class ExecutionBurstCallback : public hardware::neuralnetworks::V1_2::IBurstCallback {
		DISALLOW_COPY_AND_ASSIGN(ExecutionBurstCallback);
		class MemoryCache : public std::enable_shared_from_this<MemoryCache> {
		struct PrivateConstructorTag {};

		public:
		ExecutionBurstCallback() = default;
		using Task = std::function<void()>;
		using Cleanup = base::ScopeGuard<Task>;
		using SharedCleanup = std::shared_ptr<const Cleanup>;
		using WeakCleanup = std::weak_ptr<const Cleanup>;

		hardware::Return<void> getMemories(const hardware::hidl_vec<int32_t>& slots,
		getMemories_cb cb) override;
		// Custom constructor to pre-allocate cache sizes.
		MemoryCache();

		/**
		* This function performs one of two different actions:
		* 1) If a key corresponding to a memory resource is unrecognized by the
		* ExecutionBurstCallback object, the ExecutionBurstCallback object
		* will allocate a slot, bind the memory to the slot, and return the
		* slot identifier.
		* 2) If a key corresponding to a memory resource is recognized by the
		* ExecutionBurstCallback object, the ExecutionBurstCallback object
		* will return the existing slot identifier.
		* Add a burst context to the MemoryCache object.
		*
		* @param memories Memory resources used in an inference.
		* @param keys Unique identifiers where each element corresponds to a
		* memory resource element in "memories".
		* @return Unique slot identifiers where each returned slot element
		* corresponds to a memory resource element in "memories".
		* If this method is called, it must be called before the MemoryCache::cacheMemory or
		* MemoryCache::getMemory is used.
		*
		* @param burstContext Burst context to be added to the MemoryCache object.
		*/
		std::vector<int32_t> getSlots(const hardware::hidl_vec<hardware::hidl_memory>& memories,
		const std::vector<intptr_t>& keys);
		void setBurstContext(sp<IBurstContext> burstContext);

		/*
		* This function performs two different actions:
		* 1) Removes an entry from the cache (if present), including the local
		* storage of the hidl_memory object. Note that this call does not
		* free any corresponding hidl_memory object in ExecutionBurstServer,
		* which is separately freed via IBurstContext::freeMemory.
		* 2) Return whether a cache entry was removed and which slot was removed if
		* found. If the key did not to correspond to any entry in the cache, a
		* slot number of 0 is returned. The slot number and whether the entry
		* existed is useful so the same slot can be freed in the
		* ExecutionBurstServer's cache via IBurstContext::freeMemory.
		/**
		* Cache a memory object in the MemoryCache object.
		*
		* @param memory Memory object to be cached while the returned `SharedCleanup` is alive.
		* @return A pair of (1) a unique identifier for the cache entry and (2) a ref-counted
		* "hold" object which preserves the cache as long as the hold object is alive.
		*/
		std::pair<int32_t, SharedCleanup> cacheMemory(const nn::SharedMemory& memory);

		/**
		* Get the memory object corresponding to a slot identifier.
		*
		* @param slot Slot which identifies the memory object to retrieve.
		* @return The memory object corresponding to slot, otherwise GeneralError.
		*/
		std::pair<bool, int32_t> freeMemory(intptr_t key);
		nn::GeneralResult<nn::SharedMemory> getMemory(int32_t slot);

		private:
		int32_t getSlotLocked(const hardware::hidl_memory& memory, intptr_t key);
		int32_t allocateSlotLocked();
		void freeMemory(const nn::SharedMemory& memory);
		int32_t allocateSlotLocked() REQUIRES(mMutex);

		std::mutex mMutex;
		std::stack<int32_t, std::vector<int32_t>> mFreeSlots;
		std::map<intptr_t, int32_t> mMemoryIdToSlot;
		std::vector<hardware::hidl_memory> mMemoryCache;
		std::condition_variable mCond;
		sp<IBurstContext> mBurstContext GUARDED_BY(mMutex);
		std::stack<int32_t, std::vector<int32_t>> mFreeSlots GUARDED_BY(mMutex);
		std::map<nn::SharedMemory, int32_t> mMemoryIdToSlot GUARDED_BY(mMutex);
		std::vector<nn::SharedMemory> mMemoryCache GUARDED_BY(mMutex);
		std::vector<WeakCleanup> mCacheCleaner GUARDED_BY(mMutex);
		};

		/**
		* HIDL Callback class to pass memory objects to the Burst server when given corresponding
		* slots.
		*/
		class ExecutionBurstCallback : public IBurstCallback {
		public:
		// Precondition: memoryCache must be non-null.
		explicit ExecutionBurstCallback(const std::shared_ptr<MemoryCache>& memoryCache);

		// See IBurstCallback::getMemories for information on this method.
		Return<void> getMemories(const hidl_vec<int32_t>& slots, getMemories_cb cb) override;

		private:
		const std::weak_ptr<MemoryCache> kMemoryCache;
		};

		/**
		* Creates a burst controller on a prepared model.
		*
		* Prefer this over ExecutionBurstController's constructor.
		*
		* @param preparedModel Model prepared for execution to execute on.
		* @param pollingTimeWindow How much time (in microseconds) the
		* ExecutionBurstController is allowed to poll the FMQ before waiting on
		* the blocking futex. Polling may result in lower latencies at the
		* potential cost of more power usage.
		* @param pollingTimeWindow How much time (in microseconds) the ExecutionBurstController is
		* allowed to poll the FMQ before waiting on the blocking futex. Polling may result in lower
		* latencies at the potential cost of more power usage.
		* @return ExecutionBurstController Execution burst controller object.
		*/
		static std::unique_ptr<ExecutionBurstController> create(
		const sp<hardware::neuralnetworks::V1_2::IPreparedModel>& preparedModel,
		static nn::GeneralResult<std::shared_ptr<const ExecutionBurstController>> create(
		const sp<IPreparedModel>& preparedModel, FallbackFunction fallback,
		std::chrono::microseconds pollingTimeWindow);

		// prefer calling ExecutionBurstController::create
		ExecutionBurstController(const std::shared_ptr<RequestChannelSender>& requestChannelSender,
		const std::shared_ptr<ResultChannelReceiver>& resultChannelReceiver,
		const sp<hardware::neuralnetworks::V1_2::IBurstContext>& burstContext,
		const sp<ExecutionBurstCallback>& callback,
		const sp<hardware::hidl_death_recipient>& deathHandler = nullptr);
		ExecutionBurstController(PrivateConstructorTag tag, FallbackFunction fallback,
		std::unique_ptr<RequestChannelSender> requestChannelSender,
		std::unique_ptr<ResultChannelReceiver> resultChannelReceiver,
		sp<ExecutionBurstCallback> callback, sp<IBurstContext> burstContext,
		std::shared_ptr<MemoryCache> memoryCache,
		neuralnetworks::utils::DeathHandler deathHandler);

		// explicit destructor to unregister the death recipient
		~ExecutionBurstController();
		// See IBurst::cacheMemory for information on this method.
		OptionalCacheHold cacheMemory(const nn::SharedMemory& memory) const override;

		/**
		* Execute a request on a model.
		*
		* @param request Arguments to be executed on a model.
		* @param measure Whether to collect timing measurements, either YES or NO
		* @param memoryIds Identifiers corresponding to each memory object in the
		* request's pools.
		* @return A tuple of:
		* - result code of the execution
		* - dynamic output shapes from the execution
		* - any execution time measurements of the execution
		* - whether or not a failed burst execution should be re-run using a
		* different path (e.g., IPreparedModel::executeSynchronously)
		*/
		std::tuple<int, std::vector<hardware::neuralnetworks::V1_2::OutputShape>,
		hardware::neuralnetworks::V1_2::Timing, bool>
		compute(const hardware::neuralnetworks::V1_0::Request& request,
		hardware::neuralnetworks::V1_2::MeasureTiming measure,
		const std::vector<intptr_t>& memoryIds);

		/**
		* Propagate a user's freeing of memory to the service.
		*
		* @param key Key corresponding to the memory object.
		*/
		void freeMemory(intptr_t key);
		// See IBurst::execute for information on this method.
		nn::ExecutionResult<std::pair<std::vector<nn::OutputShape>, nn::Timing>> execute(
		const nn::Request& request, nn::MeasureTiming measure) const override;

		private:
		std::mutex mMutex;
		const std::shared_ptr<RequestChannelSender> mRequestChannelSender;
		const std::shared_ptr<ResultChannelReceiver> mResultChannelReceiver;
		const sp<hardware::neuralnetworks::V1_2::IBurstContext> mBurstContext;
		const sp<ExecutionBurstCallback> mMemoryCache;
		const sp<hardware::hidl_death_recipient> mDeathHandler;
		mutable std::atomic_flag mExecutionInFlight = ATOMIC_FLAG_INIT;
		const FallbackFunction kFallback;
		const std::unique_ptr<RequestChannelSender> mRequestChannelSender;
		const std::unique_ptr<ResultChannelReceiver> mResultChannelReceiver;
		const sp<ExecutionBurstCallback> mBurstCallback;
		const sp<IBurstContext> mBurstContext;
		const std::shared_ptr<MemoryCache> mMemoryCache;
		// `kDeathHandler` must come after `mRequestChannelSender` and `mResultChannelReceiver` because
		// it holds references to both objects.
		const neuralnetworks::utils::DeathHandler kDeathHandler;
		};

		} // namespace android::nn
		} // namespace android::hardware::neuralnetworks::V1_2::utils

		#endif // ANDROID_FRAMEWORKS_ML_NN_COMMON_EXECUTION_BURST_CONTROLLER_H
		#endif // ANDROID_HARDWARE_INTERFACES_NEURALNETWORKS_1_2_UTILS_EXECUTION_BURST_CONTROLLER_H