From 10b4dfd8e9ccd7a03df7bb053ee1c644cb37f8ab Mon Sep 17 00:00:00 2001
From: David Beck <david.beck@arm.com>
Date: Wed, 19 Sep 2018 12:03:20 +0100
Subject: IVGCVSW-1897 : build infrastructure for the src/backends folder

Change-Id: I7ebafb675ccc77ad54d1deb01412a8379a5356bb
---
 .../ClWorkloads/ClConvolution2dUint8Workload.cpp   | 81 ++++++++++++++++++++++
 1 file changed, 81 insertions(+)
 create mode 100644 src/backends/ClWorkloads/ClConvolution2dUint8Workload.cpp

(limited to 'src/backends/ClWorkloads/ClConvolution2dUint8Workload.cpp')

diff --git a/src/backends/ClWorkloads/ClConvolution2dUint8Workload.cpp b/src/backends/ClWorkloads/ClConvolution2dUint8Workload.cpp
new file mode 100644
index 0000000000..e6783b698a
--- /dev/null
+++ b/src/backends/ClWorkloads/ClConvolution2dUint8Workload.cpp
@@ -0,0 +1,81 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ClConvolution2dUint8Workload.hpp"
+#include "backends/ClTensorHandle.hpp"
+#include "backends/CpuTensorHandle.hpp"
+#include "backends/ArmComputeTensorUtils.hpp"
+#include "backends/ClLayerSupport.hpp"
+
+#include "ClWorkloadUtils.hpp"
+
+namespace armnn
+{
+using namespace armcomputetensorutils;
+
+ClConvolution2dUint8Workload::ClConvolution2dUint8Workload(const Convolution2dQueueDescriptor& descriptor,
+    const WorkloadInfo& info, std::shared_ptr<arm_compute::MemoryManagerOnDemand>& memoryManager)
+    : Uint8Workload<Convolution2dQueueDescriptor>(descriptor, info)
+    , m_ConvolutionLayer(memoryManager)
+{
+    // todo: check tensor shapes match
+    const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+    m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
+    BuildArmComputeTensor(*m_KernelTensor, weightInfo);
+
+    arm_compute::PadStrideInfo padStrideInfo(m_Data.m_Parameters.m_StrideX,
+                                             m_Data.m_Parameters.m_StrideY,
+                                             m_Data.m_Parameters.m_PadLeft,
+                                             m_Data.m_Parameters.m_PadRight,
+                                             m_Data.m_Parameters.m_PadTop,
+                                             m_Data.m_Parameters.m_PadBottom,
+                                             arm_compute::DimensionRoundingType::FLOOR);
+
+    if (m_Data.m_Parameters.m_BiasEnabled)
+    {
+        m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
+        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo());
+    }
+
+    m_Data.ValidateInputsOutputs("ClConvolution2dUint8Workload", 1, 1);
+
+    arm_compute::ICLTensor& input  = static_cast<IClTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
+    arm_compute::ICLTensor& output = static_cast<IClTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
+
+    m_ConvolutionLayer.configure(&input,
+                                 m_KernelTensor.get(),
+                                 m_BiasTensor.get(),
+                                 &output,
+                                 padStrideInfo);
+
+    InitialiseArmComputeClTensorData(*m_KernelTensor, m_Data.m_Weight->GetConstTensor<uint8_t>());
+
+    if (m_BiasTensor)
+    {
+        InitialiseArmComputeClTensorData(*m_BiasTensor, m_Data.m_Bias->GetConstTensor<int32_t>());
+    }
+
+    // Force Compute Library to perform the necessary copying and reshaping, after which
+    // delete all the input tensors that will no longer be needed
+    m_ConvolutionLayer.prepare();
+    FreeUnusedTensors();
+}
+
+void ClConvolution2dUint8Workload::Execute() const
+{
+    ARMNN_SCOPED_PROFILING_EVENT_CL("ClConvolution2dUint8Workload_Execute");
+
+    m_ConvolutionLayer.run();
+}
+
+void ClConvolution2dUint8Workload::FreeUnusedTensors()
+{
+    FreeTensorIfUnused(m_KernelTensor);
+    FreeTensorIfUnused(m_BiasTensor);
+}
+
+} //namespace armnn
+
-- 
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