commit fca75c39b1d375b7b3c8f08b6b160aa2e6f260bb
author narpra01 <narumol.prangnawarat@arm.com> Fri Nov 16 12:38:41 2018 +0000
committer Aron Virginas-Tar <aron.virginas-tar@arm.com> Fri Nov 16 14:05:35 2018 +0000
tree 924ff5f8c49cb8282f7842cac816a869bcb8dd9b
parent 81f2232a7e1145f80aaa2e382bb02c7653a058aa

IVGCVSW-2155 - Always call NEConvolutionLayer in NeonConvolution2dWorkload
 * Remove check for preferDirectConvolution
 * Remove IsNeonDirectConvolutionPreferred
 * Remove unused tests and functions

Change-Id: I3f0868f41403ec5fa740889e7bdcb4415ad77bda

src/backends/neon/workloads/NeonConvolution2dWorkload.cpp

diff --git a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
index 781c91a..151132f 100644
--- a/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
+++ b/src/backends/neon/workloads/NeonConvolution2dWorkload.cpp
@@ -82,30 +82,14 @@
                                              m_Data.m_Parameters.m_PadBottom,
                                              arm_compute::DimensionRoundingType::FLOOR);
 
-    const bool preferDirectConvolution =
-        IsNeonDirectConvolutionPreferred(m_Data.m_Weight->GetTensorInfo(),
-                                         m_Data.m_Parameters);
+    auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
+    convolutionLayer->configure(&input,
+                                m_KernelTensor.get(),
+                                m_BiasTensor.get(),
+                                &output,
+                                padStrideInfo);
+    m_ConvolutionLayer.reset(convolutionLayer.release());
 
-    if (preferDirectConvolution)
-    {
-        auto directConvolutionLayer = std::make_unique<arm_compute::NEDirectConvolutionLayer>(memoryManager);
-        directConvolutionLayer->configure(&input,
-                                          m_KernelTensor.get(),
-                                          m_BiasTensor.get(),
-                                          &output,
-                                          padStrideInfo);
-        m_ConvolutionLayer.reset(directConvolutionLayer.release());
-    }
-    else
-    {
-        auto convolutionLayer = std::make_unique<arm_compute::NEConvolutionLayer>(memoryManager);
-        convolutionLayer->configure(&input,
-                                    m_KernelTensor.get(),
-                                    m_BiasTensor.get(),
-                                    &output,
-                                    padStrideInfo);
-        m_ConvolutionLayer.reset(convolutionLayer.release());
-    }
     BOOST_ASSERT(m_ConvolutionLayer);
 
     InitializeArmComputeTensorData(*m_KernelTensor, m_Data.m_Weight);