From 9e53a35b66b1ec7ceee7c712380a13596175b83b Mon Sep 17 00:00:00 2001
From: arovir01 <Aron.Virginas-Tar@arm.com>
Date: Fri, 31 Aug 2018 15:26:35 +0100
Subject: IVGCVSW-1784: Rename float32 workloads for ACL

Change-Id: I98bdfe9cb12c663d1d5cfa456e2cc967d70ab22b
---
 .../NeonDepthwiseConvolutionFloat32Workload.cpp    | 94 ----------------------
 1 file changed, 94 deletions(-)
 delete mode 100644 src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp

(limited to 'src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp')

diff --git a/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp b/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp
deleted file mode 100644
index f94cd903b6..0000000000
--- a/src/armnn/backends/NeonWorkloads/NeonDepthwiseConvolutionFloat32Workload.cpp
+++ /dev/null
@@ -1,94 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// See LICENSE file in the project root for full license information.
-//
-
-#include "NeonDepthwiseConvolutionFloat32Workload.hpp"
-#include "backends/NeonLayerSupport.hpp"
-#include "backends/CpuTensorHandle.hpp"
-#include "backends/ArmComputeTensorUtils.hpp"
-
-
-namespace armnn
-{
-using namespace armcomputetensorutils;
-
-NeonDepthwiseConvolutionFloat32Workload::NeonDepthwiseConvolutionFloat32Workload(
-    const DepthwiseConvolution2dQueueDescriptor& descriptor,
-    const WorkloadInfo& info)
-    : FloatWorkload<DepthwiseConvolution2dQueueDescriptor>(descriptor, info)
-{
-    const TensorInfo& weightInfo = m_Data.m_Weight->GetTensorInfo();
-
-    m_KernelTensor = std::make_unique<arm_compute::Tensor>();
-    BuildArmComputeTensor(*m_KernelTensor, weightInfo);
-
-    if (m_Data.m_Parameters.m_BiasEnabled)
-    {
-        m_BiasTensor = std::make_unique<arm_compute::Tensor>();
-        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);
-
-    m_Data.ValidateInputsOutputs("NeonDepthwiseConvolutionFloat32Workload", 1, 1);
-
-    arm_compute::ITensor& input  = static_cast<INeonTensorHandle*>(m_Data.m_Inputs[0])->GetTensor();
-    arm_compute::ITensor& output = static_cast<INeonTensorHandle*>(m_Data.m_Outputs[0])->GetTensor();
-
-    bool use3x3Optimisation = weightInfo.GetShape()[3] == 3 && weightInfo.GetShape()[2] == 3;
-    if (use3x3Optimisation)
-    {
-        m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer3x3>();
-        static_cast<arm_compute::NEDepthwiseConvolutionLayer3x3*>(
-            m_pDepthwiseConvolutionLayer.get())->configure(&input,
-                                                           m_KernelTensor.get(),
-                                                           m_BiasTensor.get(),
-                                                           &output,
-                                                           padStrideInfo);
-    }
-    else
-    {
-        m_pDepthwiseConvolutionLayer = std::make_unique<arm_compute::NEDepthwiseConvolutionLayer>();
-        static_cast<arm_compute::NEDepthwiseConvolutionLayer*>(
-            m_pDepthwiseConvolutionLayer.get())->configure(&input,
-                                                           m_KernelTensor.get(),
-                                                           m_BiasTensor.get(),
-                                                           &output,
-                                                           padStrideInfo);
-    }
-
-    BOOST_ASSERT(m_pDepthwiseConvolutionLayer);
-
-    InitializeArmComputeTensorDataForFloatTypes(*m_KernelTensor, m_Data.m_Weight);
-
-    if (m_BiasTensor)
-    {
-        InitializeArmComputeTensorDataForFloatTypes(*m_BiasTensor, m_Data.m_Bias);
-    }
-
-    m_pDepthwiseConvolutionLayer->prepare();
-    FreeUnusedTensors();
-}
-
-void NeonDepthwiseConvolutionFloat32Workload::Execute() const
-{
-    ARMNN_SCOPED_PROFILING_EVENT_NEON("NeonDepthwiseConvolutionFloat32Workload_Execute");
-    BOOST_ASSERT(m_pDepthwiseConvolutionLayer);
-
-    m_pDepthwiseConvolutionLayer->run();
-}
-
-void NeonDepthwiseConvolutionFloat32Workload::FreeUnusedTensors()
-{
-    FreeTensorIfUnused(m_KernelTensor);
-    FreeTensorIfUnused(m_BiasTensor);
-}
-
-} //namespace armnn
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