commit 0a2dfabd76a45c58d0a14567f0503369c4e6fbf3
author Sadik Armagan <sadik.armagan@arm.com> Wed Oct 06 16:41:44 2021 +0100
committer mike.kelly <mike.kelly@arm.com> Thu Nov 04 15:16:10 2021 +0000
tree 035340e9f663d599f83992846e1772b161640654
parent 1b46d132a3330692fcf9a603b21363a28f46ef03

IVGCVSW-5636 'Implement NNAPI caching functions'

* Cached serialized ArmNN model.

!armnn:6384

Signed-off-by: Sadik Armagan <sadik.armagan@arm.com>
Signed-off-by: Kevin May <kevin.may@arm.com>
Change-Id: I78120a7f8ea892a28c0ff25f1b54e67a4f912574

ArmnnPreparedModel_1_2.cpp

diff --git a/ArmnnPreparedModel_1_2.cpp b/ArmnnPreparedModel_1_2.cpp
index 2e37880..7cc7547 100644
--- a/ArmnnPreparedModel_1_2.cpp
+++ b/ArmnnPreparedModel_1_2.cpp
@@ -159,6 +159,47 @@
     , m_RequestInputsAndOutputsDumpDir(requestInputsAndOutputsDumpDir)
     , m_GpuProfilingEnabled(gpuProfilingEnabled)
     , m_AsyncModelExecutionEnabled(asyncModelExecutionEnabled)
+    , m_PreparedFromCache(false)
+{
+    // Enable profiling if required.
+    m_Runtime->GetProfiler(m_NetworkId)->EnableProfiling(m_GpuProfilingEnabled);
+
+    if (m_AsyncModelExecutionEnabled)
+    {
+        std::vector<std::shared_ptr<armnn::IWorkingMemHandle>> memHandles;
+        for (unsigned int i=0; i < numberOfThreads; ++i)
+        {
+            memHandles.emplace_back(m_Runtime->CreateWorkingMemHandle(networkId));
+        }
+
+        if (!m_Threadpool)
+        {
+            m_Threadpool = std::make_unique<armnn::Threadpool>(numberOfThreads, runtime, memHandles);
+        }
+        else
+        {
+            m_Threadpool->LoadMemHandles(memHandles);
+        }
+
+        m_WorkingMemHandle = memHandles.back();
+    }
+}
+
+template<typename HalVersion>
+ArmnnPreparedModel_1_2<HalVersion>::ArmnnPreparedModel_1_2(armnn::NetworkId networkId,
+                                                           armnn::IRuntime* runtime,
+                                                           const std::string& requestInputsAndOutputsDumpDir,
+                                                           const bool gpuProfilingEnabled,
+                                                           const bool asyncModelExecutionEnabled,
+                                                           const unsigned int numberOfThreads,
+                                                           const bool preparedFromCache)
+    : m_NetworkId(networkId)
+    , m_Runtime(runtime)
+    , m_RequestCount(0)
+    , m_RequestInputsAndOutputsDumpDir(requestInputsAndOutputsDumpDir)
+    , m_GpuProfilingEnabled(gpuProfilingEnabled)
+    , m_AsyncModelExecutionEnabled(asyncModelExecutionEnabled)
+    , m_PreparedFromCache(preparedFromCache)
 {
     // Enable profiling if required.
     m_Runtime->GetProfiler(m_NetworkId)->EnableProfiling(m_GpuProfilingEnabled);
@@ -384,7 +425,10 @@
                                                                       V1_2::MeasureTiming measureTiming,
                                                                       executeSynchronously_cb cb)
 {
-    ALOGV("ArmnnPreparedModel_1_2::executeSynchronously(): %s", GetModelSummary(m_Model).c_str());
+    if (!m_PreparedFromCache)
+    {
+        ALOGV("ArmnnPreparedModel_1_2::executeSynchronously(): %s", GetModelSummary(m_Model).c_str());
+    }
     m_RequestCount++;
 
     if (cb == nullptr)
@@ -400,7 +444,7 @@
         driverStart = Now();
     }
 
-    if (!android::nn::validateRequest(request, m_Model))
+    if (!m_PreparedFromCache && !android::nn::validateRequest(request, m_Model))
     {
         ALOGE("ArmnnPreparedModel_1_2::executeSynchronously invalid request model");
         cb(V1_0::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming);
@@ -530,11 +574,11 @@
 }
 
 template<typename HalVersion>
-bool ArmnnPreparedModel_1_2<HalVersion>::ExecuteWithDummyInputs()
+bool ArmnnPreparedModel_1_2<HalVersion>::ExecuteWithDummyInputs(unsigned int numInputs, unsigned int numOutputs)
 {
     std::vector<std::vector<char>> storage;
     armnn::InputTensors inputTensors;
-    for (unsigned int i = 0; i < getMainModel(m_Model).inputIndexes.size(); i++)
+    for (unsigned int i = 0; i < numInputs; i++)
     {
         const armnn::TensorInfo inputTensorInfo = m_Runtime->GetInputTensorInfo(m_NetworkId, i);
         storage.emplace_back(inputTensorInfo.GetNumBytes());
@@ -544,7 +588,7 @@
     }
 
     armnn::OutputTensors outputTensors;
-    for (unsigned int i = 0; i < getMainModel(m_Model).outputIndexes.size(); i++)
+    for (unsigned int i = 0; i < numOutputs; i++)
     {
         const armnn::TensorInfo outputTensorInfo = m_Runtime->GetOutputTensorInfo(m_NetworkId, i);
         storage.emplace_back(outputTensorInfo.GetNumBytes());
@@ -576,10 +620,13 @@
         ctx.driverStart = Now();
     }
 
-    ALOGV("ArmnnPreparedModel_1_2::execute(): %s", GetModelSummary(m_Model).c_str());
+    if (!m_PreparedFromCache)
+    {
+        ALOGV("ArmnnPreparedModel_1_2::execute(): %s", GetModelSummary(m_Model).c_str());
+    }
     m_RequestCount++;
 
-    if (!android::nn::validateRequest(request, m_Model))
+    if (!m_PreparedFromCache && !android::nn::validateRequest(request, m_Model))
     {
         callback(V1_0::ErrorStatus::INVALID_ARGUMENT, {}, g_NoTiming, "ArmnnPreparedModel_1_2::execute");
         return V1_0::ErrorStatus::INVALID_ARGUMENT;