From ac42efd972b7d03da17f057b2ceaaac5d6e96b1a Mon Sep 17 00:00:00 2001
From: David Beck <david.beck@arm.com>
Date: Wed, 26 Sep 2018 17:41:13 +0100
Subject: IVGCVSW-1900 : CL backend folder structure

* moving backends/ClWorkloads to backends/cl
* and moving pure Cl workload related code to
  backends/cl/workloads

Change-Id: I019a3c6b4da5e7a23074bf03fb057e63199ad129
---
 .../ClDepthwiseConvolutionBaseWorkload.cpp         | 125 +++++++++++++++++++++
 1 file changed, 125 insertions(+)
 create mode 100644 src/backends/cl/workloads/ClDepthwiseConvolutionBaseWorkload.cpp

(limited to 'src/backends/cl/workloads/ClDepthwiseConvolutionBaseWorkload.cpp')

diff --git a/src/backends/cl/workloads/ClDepthwiseConvolutionBaseWorkload.cpp b/src/backends/cl/workloads/ClDepthwiseConvolutionBaseWorkload.cpp
new file mode 100644
index 0000000000..5a036db922
--- /dev/null
+++ b/src/backends/cl/workloads/ClDepthwiseConvolutionBaseWorkload.cpp
@@ -0,0 +1,125 @@
+//
+// Copyright © 2017 Arm Ltd. All rights reserved.
+// SPDX-License-Identifier: MIT
+//
+
+#include "ClDepthwiseConvolutionBaseWorkload.hpp"
+
+#include "TypeUtils.hpp"
+
+#include <backends/aclCommon/ArmComputeUtils.hpp>
+#include <backends/aclCommon/ArmComputeTensorUtils.hpp>
+#include <backends/cl/ClTensorHandle.hpp>
+#include <backends/CpuTensorHandle.hpp>
+
+namespace armnn
+{
+
+using namespace armcomputetensorutils;
+
+arm_compute::Status ClDepthwiseConvolutionWorkloadValidate(const TensorInfo& input,
+    const TensorInfo& output,
+    const DepthwiseConvolution2dDescriptor& descriptor,
+    const TensorInfo& weights,
+    const boost::optional<TensorInfo>& biases)
+{
+    const arm_compute::TensorInfo aclInputInfo = BuildArmComputeTensorInfo(input, descriptor.m_DataLayout);
+    const arm_compute::TensorInfo aclOutputInfo = BuildArmComputeTensorInfo(output, descriptor.m_DataLayout);
+    const arm_compute::TensorInfo aclWeightsInfo = BuildArmComputeTensorInfo(weights, descriptor.m_DataLayout);
+
+    arm_compute::TensorInfo aclBiasesInfo;
+    arm_compute::TensorInfo *optionalAclBiasesInfo = nullptr;
+
+    if (descriptor.m_BiasEnabled)
+    {
+        BOOST_ASSERT(biases.is_initialized());
+
+        aclBiasesInfo = BuildArmComputeTensorInfo(biases.get(), descriptor.m_DataLayout);
+        optionalAclBiasesInfo = &aclBiasesInfo;
+    }
+
+    const arm_compute::PadStrideInfo aclPadStrideInfo = BuildArmComputePadStrideInfo(descriptor);
+    const unsigned int aclDepthMultiplier = weights.GetShape()[0];
+
+    return arm_compute::CLDepthwiseConvolutionLayer::validate(&aclInputInfo,
+                                                              &aclWeightsInfo,
+                                                              optionalAclBiasesInfo,
+                                                              &aclOutputInfo,
+                                                              aclPadStrideInfo,
+                                                              aclDepthMultiplier);
+}
+
+template<armnn::DataType... dataTypes>
+ClDepthwiseConvolutionBaseWorkload<dataTypes...>::ClDepthwiseConvolutionBaseWorkload(
+    const DepthwiseConvolution2dQueueDescriptor& descriptor,
+    const WorkloadInfo& info)
+    : TypedWorkload<DepthwiseConvolution2dQueueDescriptor, dataTypes...>(descriptor, info)
+{
+    auto& weightInfo = m_Data.m_Weight->GetTensorInfo();
+
+    m_KernelTensor = std::make_unique<arm_compute::CLTensor>();
+    BuildArmComputeTensor(*m_KernelTensor, weightInfo);
+
+    if (m_Data.m_Parameters.m_BiasEnabled)
+    {
+        m_BiasTensor = std::make_unique<arm_compute::CLTensor>();
+        BuildArmComputeTensor(*m_BiasTensor, m_Data.m_Bias->GetTensorInfo());
+    }
+
+    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);
+
+    std::string name = std::string("ClDepthwiseConvolution") +
+            GetDataTypeName(m_Data.m_Weight->GetTensorInfo().GetDataType()) + "Workload";
+    m_Data.ValidateInputsOutputs(name, 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();
+
+    const unsigned int depthMultiplier = weightInfo.GetShape()[0];
+
+    //Check for optimisation opportunities.
+    bool use3x3Optimisation = (weightInfo.GetShape()[3] == 3) && (weightInfo.GetShape()[2] == 3);
+    if (use3x3Optimisation)
+    {
+        m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer3x3>();
+        static_cast<arm_compute::CLDepthwiseConvolutionLayer3x3*>(m_DepthwiseConvolutionLayer.get())->configure(
+            &input,
+            m_KernelTensor.get(),
+            m_BiasTensor.get(),
+            &output,
+            padStrideInfo,
+            depthMultiplier);
+    }
+    else
+    {
+        m_DepthwiseConvolutionLayer = std::make_unique<arm_compute::CLDepthwiseConvolutionLayer>();
+        static_cast<arm_compute::CLDepthwiseConvolutionLayer*>(m_DepthwiseConvolutionLayer.get())->configure(
+            &input,
+            m_KernelTensor.get(),
+            m_BiasTensor.get(),
+            &output,
+            padStrideInfo,
+            depthMultiplier);
+    }
+
+    BOOST_ASSERT(m_DepthwiseConvolutionLayer);
+}
+
+template<armnn::DataType... dataTypes>
+void ClDepthwiseConvolutionBaseWorkload<dataTypes...>::FreeUnusedTensors()
+{
+    FreeTensorIfUnused(m_KernelTensor);
+    FreeTensorIfUnused(m_BiasTensor);
+}
+
+// Generate known implementations for linker
+template class ClDepthwiseConvolutionBaseWorkload<DataType::Float16, DataType::Float32>;
+template class ClDepthwiseConvolutionBaseWorkload<DataType::QuantisedAsymm8>;
+
+} // namespace armnn
-- 
cgit v1.2.1