IVGCVSW-4447 Add Hal 1_3 Support
* Add new 1.3 files HalPolicy, ArmnnDriver, ArmnnDriverImpl
* Add new .rc file for 1.3 service
* Add ArmnnPreparedModel_1_3 and implement new functions
* Update Android.mk with 1.3 driver and service
* Refactor ifdef to include ARMNN_ANDROID_NN_V1_3
* Create Utils getMainModel for new 1.3 Model Main Subgraph
* Use android Utils to convertToV1_X in ArmnnPrepapredModel_1_3
* Refactor HAL 1.2 convert functions into ConversionUtils_1_2.hpp
* Replace ArmnnBurstExecutorWithCache with call to ExecutionBurstServer
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I514069e9e1b16bcd1c4abfb5d563d25ac22d02e3
diff --git a/ArmnnPreparedModel_1_3.hpp b/ArmnnPreparedModel_1_3.hpp
new file mode 100644
index 0000000..247149c
--- /dev/null
+++ b/ArmnnPreparedModel_1_3.hpp
@@ -0,0 +1,137 @@
+//
+// Copyright © 2020 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#pragma once
+
+#include "ArmnnDriver.hpp"
+#include "ArmnnDriverImpl.hpp"
+#include "RequestThread.hpp"
+#include "ModelToINetworkConverter.hpp"
+
+#include <NeuralNetworks.h>
+#include <armnn/ArmNN.hpp>
+
+#include <string>
+#include <vector>
+
+namespace armnn_driver
+{
+using CallbackAsync_1_3 = std::function<
+ void(V1_3::ErrorStatus errorStatus,
+ std::vector<::android::hardware::neuralnetworks::V1_2::OutputShape> outputShapes,
+ const ::android::hardware::neuralnetworks::V1_2::Timing& timing,
+ std::string callingFunction)>;
+
+struct ExecutionContext_1_3
+{
+ ::android::hardware::neuralnetworks::V1_2::MeasureTiming measureTimings =
+ ::android::hardware::neuralnetworks::V1_2::MeasureTiming::NO;
+ TimePoint driverStart;
+};
+
+using CallbackContext_1_3 = CallbackContext<CallbackAsync_1_3, ExecutionContext_1_3>;
+
+using executeFenced_cb = std::function<void(::android::hardware::neuralnetworks::V1_3::ErrorStatus status,
+ const ::android::hardware::hidl_handle& syncFence,
+ const ::android::sp<::android::hardware::neuralnetworks::V1_3::IFencedExecutionCallback>& callback)>;
+
+template <typename HalVersion>
+class ArmnnPreparedModel_1_3 : public V1_3::IPreparedModel
+{
+public:
+ using HalModel = typename V1_3::Model;
+
+ ArmnnPreparedModel_1_3(armnn::NetworkId networkId,
+ armnn::IRuntime* runtime,
+ const HalModel& model,
+ const std::string& requestInputsAndOutputsDumpDir,
+ const bool gpuProfilingEnabled);
+
+ virtual ~ArmnnPreparedModel_1_3();
+
+ Return<V1_0::ErrorStatus> execute(const V1_0::Request& request,
+ const sp<V1_0::IExecutionCallback>& callback) override;
+
+ Return<V1_0::ErrorStatus> execute_1_2(const V1_0::Request& request, MeasureTiming measure,
+ const sp<V1_2::IExecutionCallback>& callback) override;
+
+ Return<V1_3::ErrorStatus> execute_1_3(const V1_3::Request& request,
+ V1_2::MeasureTiming measure,
+ const V1_3::OptionalTimePoint&,
+ const sp<V1_3::IExecutionCallback>& callback) override;
+
+ Return<void> executeSynchronously(const V1_0::Request &request,
+ MeasureTiming measure,
+ V1_3::IPreparedModel::executeSynchronously_cb cb) override;
+
+ Return<void> executeSynchronously_1_3(const V1_3::Request &request,
+ MeasureTiming measure,
+ const V1_3::OptionalTimePoint& deadline,
+ V1_3::IPreparedModel::executeSynchronously_1_3_cb cb) override;
+
+ Return<void> executeFenced(const V1_3::Request& request,
+ const android::hardware::hidl_vec<android::hardware::hidl_handle>& wait_for,
+ MeasureTiming measure,
+ const V1_3::OptionalTimePoint& deadline,
+ const V1_3::OptionalTimeoutDuration& duration,
+ executeFenced_cb callback) override;
+
+ Return<void> configureExecutionBurst(
+ const sp<V1_2::IBurstCallback>& callback,
+ const android::hardware::MQDescriptorSync<V1_2::FmqRequestDatum>& requestChannel,
+ const android::hardware::MQDescriptorSync<V1_2::FmqResultDatum>& resultChannel,
+ configureExecutionBurst_cb cb) override;
+
+ template<typename CallbackContext>
+ Return<void> ExecuteSynchronously(const V1_3::Request& request, CallbackContext cbCtx);
+
+ /// execute the graph prepared from the request
+ template<typename CallbackContext>
+ bool ExecuteGraph(std::shared_ptr<std::vector<::android::nn::RunTimePoolInfo>>& pMemPools,
+ armnn::InputTensors& inputTensors,
+ armnn::OutputTensors& outputTensors,
+ CallbackContext callback);
+
+ /// Executes this model with dummy inputs (e.g. all zeroes).
+ /// \return false on failure, otherwise true
+ bool ExecuteWithDummyInputs();
+
+private:
+ Return <V1_3::ErrorStatus> Execute(const V1_3::Request& request,
+ MeasureTiming measureTiming,
+ CallbackAsync_1_3 callback);
+
+ Return<V1_3::ErrorStatus> PrepareMemoryForInputs(
+ armnn::InputTensors& inputs,
+ const V1_3::Request& request,
+ const std::vector<android::nn::RunTimePoolInfo>& memPools);
+
+ Return<V1_3::ErrorStatus> PrepareMemoryForOutputs(
+ armnn::OutputTensors& outputs,
+ std::vector<OutputShape> &outputShapes,
+ const V1_3::Request& request,
+ const std::vector<android::nn::RunTimePoolInfo>& memPools);
+
+ std::tuple<V1_3::ErrorStatus, hidl_vec<OutputShape>, Timing, std::string> PrepareMemoryForIO(
+ armnn::InputTensors& inputs,
+ armnn::OutputTensors& outputs,
+ std::vector<android::nn::RunTimePoolInfo>& memPools,
+ const V1_3::Request& request);
+
+ template <typename TensorBindingCollection>
+ void DumpTensorsIfRequired(char const* tensorNamePrefix, const TensorBindingCollection& tensorBindings);
+
+ armnn::NetworkId m_NetworkId;
+ armnn::IRuntime* m_Runtime;
+ V1_3::Model m_Model;
+ // There must be a single RequestThread for all ArmnnPreparedModel objects to ensure serial execution of workloads
+ // It is specific to this class, so it is declared as static here
+ static RequestThread<ArmnnPreparedModel_1_3, HalVersion, CallbackContext_1_3> m_RequestThread;
+ uint32_t m_RequestCount;
+ const std::string& m_RequestInputsAndOutputsDumpDir;
+ const bool m_GpuProfilingEnabled;
+};
+
+}