IVGCVSW-1897 : build infrastructure for the src/backends folder

Change-Id: I7ebafb675ccc77ad54d1deb01412a8379a5356bb

1 files changed, 0 insertions, 135 deletions

diff --git a/src/armnn/backends/ArmComputeTensorUtils.cpp b/src/armnn/backends/ArmComputeTensorUtils.cpp
deleted file mode 100644
index ba9fb40cfc..0000000000
--- a/src/armnn/backends/ArmComputeTensorUtils.cpp
+++ /dev/null
@@ -1,135 +0,0 @@
-//
-// Copyright © 2017 Arm Ltd. All rights reserved.
-// SPDX-License-Identifier: MIT
-//
-#include "ArmComputeTensorUtils.hpp"
-#include "ArmComputeUtils.hpp"
-
-#include <armnn/Descriptors.hpp>
-
-namespace armnn
-{
-namespace armcomputetensorutils
-{
-
-arm_compute::DataType GetArmComputeDataType(armnn::DataType dataType)
-{
-    switch(dataType)
-    {
-        case armnn::DataType::Float16:
-            return arm_compute::DataType::F16;
-        case armnn::DataType::Float32:
-            return arm_compute::DataType::F32;
-        case armnn::DataType::QuantisedAsymm8:
-            return arm_compute::DataType::QASYMM8;
-        case armnn::DataType::Signed32:
-            return arm_compute::DataType::S32;
-        default:
-            BOOST_ASSERT_MSG(false, "Unknown data type");
-            return arm_compute::DataType::UNKNOWN;
-    }
-}
-
-arm_compute::TensorShape BuildArmComputeTensorShape(const armnn::TensorShape& tensorShape)
-{
-    arm_compute::TensorShape shape;
-
-    // armnn tensors are (batch, channels, height, width).
-    // arm_compute tensors are (width, height, channels, batch).
-    for (unsigned int i = 0; i < tensorShape.GetNumDimensions(); i++)
-    {
-        // Note that our dimensions are stored in the opposite order to ACL's.
-        shape.set(tensorShape.GetNumDimensions() - i - 1, tensorShape[i]);
-
-        // TensorShape::set() flattens leading ones, so that batch size 1 cannot happen.
-        // arm_compute tensors expect this.
-    }
-
-    // prevent arm_compute issue where tensor is flattened to nothing
-    if (shape.num_dimensions() == 0)
-    {
-        shape.set_num_dimensions(1);
-    }
-
-    return shape;
-}
-
-// Utility function used to build a TensorInfo object, that can be used to initialise
-// ARM Compute Tensor and CLTensor allocators.
-arm_compute::TensorInfo BuildArmComputeTensorInfo(const armnn::TensorInfo& tensorInfo)
-{
-    const arm_compute::TensorShape aclTensorShape = BuildArmComputeTensorShape(tensorInfo.GetShape());
-    const arm_compute::DataType aclDataType = GetArmComputeDataType(tensorInfo.GetDataType());
-    const arm_compute::QuantizationInfo aclQuantizationInfo(tensorInfo.GetQuantizationScale(),
-                                                            tensorInfo.GetQuantizationOffset());
-
-    return arm_compute::TensorInfo(aclTensorShape, 1, aclDataType, aclQuantizationInfo);
-}
-
-arm_compute::PoolingLayerInfo BuildArmComputePoolingLayerInfo(const Pooling2dDescriptor& descriptor)
-{
-    using arm_compute::PoolingType;
-    using arm_compute::DimensionRoundingType;
-    using arm_compute::PadStrideInfo;
-    using arm_compute::PoolingLayerInfo;
-    using arm_compute::Size2D;
-
-    // Resolve ARM Compute layer parameters.
-    const PoolingType poolingType = ConvertPoolingAlgorithmToAclPoolingType(descriptor.m_PoolType);
-
-    bool isGlobalPooling = (descriptor.m_StrideX==0 && descriptor.m_StrideY==0);
-    //use specific constructor if global pooling
-    if(isGlobalPooling)
-    {
-        return arm_compute::PoolingLayerInfo(poolingType);
-    }
-
-    const DimensionRoundingType rounding = ConvertOutputShapeRoundingToAclDimensionRoundingType(
-                                                                                    descriptor.m_OutputShapeRounding);
-    const PadStrideInfo padStrideInfo(descriptor.m_StrideX,
-                                      descriptor.m_StrideY,
-                                      descriptor.m_PadLeft,
-                                      descriptor.m_PadRight,
-                                      descriptor.m_PadTop,
-                                      descriptor.m_PadBottom,
-                                      rounding);
-
-    const bool excludePadding = (descriptor.m_PaddingMethod == PaddingMethod::Exclude);
-
-    const Size2D poolSize(descriptor.m_PoolWidth, descriptor.m_PoolHeight);
-
-    return arm_compute::PoolingLayerInfo(poolingType, poolSize, padStrideInfo, excludePadding);
-}
-
-arm_compute::NormalizationLayerInfo BuildArmComputeNormalizationLayerInfo(const NormalizationDescriptor& descriptor)
-{
-    const arm_compute::NormType normType =
-        ConvertNormalizationAlgorithmChannelToAclNormType(descriptor.m_NormChannelType);
-    return arm_compute::NormalizationLayerInfo(normType,
-                                               descriptor.m_NormSize,
-                                               descriptor.m_Alpha,
-                                               descriptor.m_Beta,
-                                               descriptor.m_K,
-                                               false);
-}
-
-arm_compute::PermutationVector BuildArmComputePermutationVector(const armnn::PermutationVector& perm)
-{
-    arm_compute::PermutationVector aclPerm;
-
-    unsigned int start = 0;
-    while ((start < perm.GetSize()) && (start == perm[start]))
-    {
-        ++start;
-    }
-
-    for (unsigned int i = start; i < perm.GetSize(); ++i)
-    {
-        aclPerm.set(i - start, perm[i] - start);
-    }
-
-    return aclPerm;
-}
-
-} // namespace armcomputetensorutils
-} // namespace armnn