IVGCVSW-1899 : Neon backend folder structure

armnn:149855

Change-Id: I26e8cf83422a65049386a5ebdb6d0001627aefaa

1 files changed, 110 insertions, 0 deletions

diff --git a/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp
new file mode 100644
index 0000000000..8cebb4f48f
--- /dev/null
+++ b/src/backends/neon/workloads/NeonFullyConnectedWorkload.cpp
@@ -0,0 +1,110 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "NeonFullyConnectedWorkload.hpp"
+
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/aclCommon/ArmComputeUtils.hpp>
+#include <backends/CpuTensorHandle.hpp>
+
+namespace armnn
+{
+using namespace armcomputetensorutils;
+
+arm_compute::Status NeonFullyConnectedWorkloadValidate(const TensorInfo& input,
+                                                       const TensorInfo& output,
+                                                       const TensorInfo& weights,
+                                                       const TensorInfo& biases,
+                                                       const FullyConnectedDescriptor& descriptor)
+{
+    const arm_compute::TensorInfo aclInput = BuildArmComputeTensorInfo(input);
+    const arm_compute::TensorInfo aclOutput = BuildArmComputeTensorInfo(output);
+    const arm_compute::TensorInfo aclWeights = BuildArmComputeTensorInfo(weights);
+
+    arm_compute::TensorInfo aclBiases;
+    arm_compute::TensorInfo *optionalAclBiases = nullptr;
+    if (descriptor.m_BiasEnabled)
+    {
+        aclBiases  = BuildArmComputeTensorInfo(biases);
+        optionalAclBiases = &aclBiases;
+    }
+
+    const arm_compute::FullyConnectedLayerInfo fullyConnectedLayerInfo =
+        ConvertFullyConnectedDescriptorToAclFullyConnectedLayerInfo(descriptor);
+
+
+    return arm_compute::NEFullyConnectedLayer::validate(&aclInput,
+                                                        &aclWeights,
+                                                        optionalAclBiases,
+                                                        &aclOutput,
+                                                        fullyConnectedLayerInfo);
+}
+
+NeonFullyConnectedWorkload::NeonFullyConnectedWorkload(const FullyConnectedQueueDescriptor& descriptor,
+    const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
+    : BaseWorkload<FullyConnectedQueueDescriptor>(descriptor, info)
+    , m_FullyConnectedLayer(memoryManager)
+{
+    m_Data.ValidateInputsOutputs("NeonFullyConnectedWorkload", 1, 1);
+
+    arm_compute::ITensor& input = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ITensor& output = boost::polymorphic_downcast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    m_WeightsTensor = std::make_unique<arm_compute::Tensor>();
+    BuildArmComputeTensor(*m_WeightsTensor, m_Data.m_Weight->GetTensorInfo());
+
+    if (m_Data.m_Parameters.m_BiasEnabled)
+    {
+        m_BiasesTensor = std::make_unique<arm_compute::Tensor>();
+        BuildArmComputeTensor(*m_BiasesTensor, m_Data.m_Bias->GetTensorInfo());
+    }
+
+    // Construct
+    arm_compute::FullyConnectedLayerInfo fc_info;
+    fc_info.transpose_weights = m_Data.m_Parameters.m_TransposeWeightMatrix;
+    m_FullyConnectedLayer.configure(&input, m_WeightsTensor.get(), m_BiasesTensor.get(), &output, fc_info);
+
+    // Allocate
+    if (m_Data.m_Weight->GetTensorInfo().GetDataType() == DataType::QuantisedAsymm8)
+    {
+        InitialiseArmComputeTensorData(*m_WeightsTensor, m_Data.m_Weight->GetConstTensor<uint8_t>());
+    }
+    else
+    {
+        InitializeArmComputeTensorDataForFloatTypes(*m_WeightsTensor, m_Data.m_Weight);
+    }
+
+    if (m_BiasesTensor)
+    {
+        if (m_Data.m_Bias->GetTensorInfo().GetDataType() == DataType::Signed32)
+        {
+            InitialiseArmComputeTensorData(*m_BiasesTensor, m_Data.m_Bias->GetConstTensor<int32_t>());
+        }
+        else
+        {
+            InitializeArmComputeTensorDataForFloatTypes(*m_BiasesTensor, m_Data.m_Bias);
+        }
+    }
+
+    // Force Compute Library to perform the necessary copying and reshaping, after which
+    // delete all the input tensors that will no longer be needed
+    m_FullyConnectedLayer.prepare();
+    FreeUnusedTensors();
+}
+
+void NeonFullyConnectedWorkload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonFullyConnectedWorkload_Execute");
+    m_FullyConnectedLayer.run();
+}
+
+void NeonFullyConnectedWorkload::FreeUnusedTensors()
+{
+    FreeTensorIfUnused(m_WeightsTensor);
+    FreeTensorIfUnused(m_BiasesTensor);
+}
+
+} //namespace armnn
+